Industry 4.0

 

Industry 4.0

 

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Contents

Contents. 2

Abstract 5

CHAPTER ONE.. 6

1.1 Introduction. 6

1.2 Research Objectives. 15

1.3 Research Questions. 15

CHAPTER TWO.. 16

2.1 LITERATURE REVIEW… 16

2.1.1 Industry 4.0 in Manufacturing and Logistics. 17

2.1.2 COVID-19 – The pandemic & it’s effects. 19

2.1.3 Adaptations due to Covid-19. 21

2.1.4 Adaptation of Technology to mitigate the effects of COVID in Manufacturing. 23

CHAPTER THREE.. 26

METHODOLOGY.. 26

3.1 Introduction. 26

3.2 Research Process. 26

3.3 Research Design. 27

3.3.1 Philosophy of Research. 28

3.3.2 Approach of Research. 30

3.3.3 Strategy of Research. 30

3.3.4 Methodology of Research. 31

3.4 Undertaken Research. 33

CHAPTER FOUR.. 40

4.1 RESULTS AND DATA ANALYSIS. 40

4.1.1 Introduction. 40

4.1.2 P1 Transcript 40

4.1.3 P2 Transcript 43

4.1.4 P3 Transcript 45

4.1.5 P4 Transcript 48

4.1.6 P5 Transcript 49

4.1.7 P6 Transcript 50

CHAPTER FIVE.. 53

5.1 FINDINGS AND DISCUSSION.. 53

5.1.1 Findings. 53

5.1.2 Discussion. 55

CHAPTER 6. 59

6.1 CONCLUSION.. 59

6.2 Limitation of the Study. 59

6.3 Limitations of the Scope, Quality, and Validity of the Analysis Undertaken. 60

6.4 Recommendations. 61

References. 65

 

 

 

 

 

Abstract

Industry 4.0 also called the Fourth Industrial Revolution is characterized by a connection of technologies that are blurring the lines between the physical, digital and biological worlds. Industry 4.0 technologies are playing a major role in transforming the supply chain, making it more efficient, agile, and responsive to customer needs. The concept of Industry 4.0 was first introduced in Germany in 2011, and it has since gained traction internationally as a way to describe the fourth industrial revolution. This industrial revolution is characterized by a number of new technologies that are transforming traditional manufacturing and production processes. The Fourth Industrial Revolution is known to have a number of benefits including; they can help to optimize supply chains by reducing waste and improving visibility into the entire system that they can help to improve the quality of products and services. For instance, by using sensors and other devices to collect data throughout the production process, companies can identify problems and potential errors much more quickly and easily and can also be used to create customized products that are better able to meet the needs of individual customers. Industry 4.0 technologies can also help to improve the working conditions for employees. On the other hand, some challenges include; ensuring compatibility between different Industry 4.0 technologies and systems and the technologies are able to seamlessly integrate with existing supply chain systems and infrastructure. This paper comprises of six chapters namely; introduction, literature review, methodology, data analysis, findings and conclusion.

 

 

 

CHAPTER ONE

1.1 Introduction

The Fourth Industrial Revolution, also known as Industry 4.0, is the ongoing digital transformation of traditional manufacturing and industrial practices and is characterized by a fusion of technologies that is blurring the lines between the physical, digital and biological worlds. The adoption of Industry 4.0 technologies in supply chains is still in its early stages, but there is potential for significant impact to help supply chain managers to increase visibility, optimize operations and reduce costs. One way that Industry 4.0 technologies can help to increase visibility in supply chains is through the use of sensors (Dalenogare et al., 2018). Sensors can be used to track the location of inventory, as well as the condition of inventory. This information can then be used to make decisions about where inventory should be located and how it should be managed. In addition, the use of sensors can also help to identify potential problems in the supply chain, such as bottlenecks, and allow for proactive decision-making to avoid these problems. Another way that Industry 4.0 technologies can help to optimize operations in supply chains is through the use of predictive analytics. Predictive analytics can be used to identify trends and patterns in data, which can then be used to make decisions about future operations. For example, predictive analytics can be used to identify patterns in customer demand, which can then be used to determine the best time to produce and ship products (Bai et al., 2020). In addition, predictive analytics can also be used to identify potential problems in the supply chain, such as disruptions, and allow for proactive decision-making to avoid these problems. Finally, the use of Industry 4.0 technologies can also help to reduce costs in supply chains. The use of robotics, for example, can help to automate tasks which can lead to cost savings. In addition, the use of 3D printing can help to reduce the need for inventory, as well as the lead time required to produce products.

Supply chain management is a critical function for any business that relies on the production and delivery of goods and services. In recent years, the supply chain has become increasingly complex and globalized, making it more important than ever for businesses to have efficient and effective supply chain management systems in place. Industry 4.0 technologies are playing a major role in transforming the supply chain, making it more efficient, agile, and responsive to customer needs. The concept of Industry 4.0 was first introduced in Germany in 2011, and it has since gained traction internationally as a way to describe the fourth industrial revolution. This industrial revolution is characterized by a number of new technologies that are transforming traditional manufacturing and production processes (Koh, Orzes & Jia, 2019). Industry 4.0 technologies include things like 3D printing, robotics, artificial intelligence, and the Internet of Things. These technologies are having a major impact on the supply chain, making it more efficient and responsive to customer needs. For example, 3D printing technology is being used to create custom parts and products on demand, reducing the need for businesses to maintain large inventories of finished goods. Robotics and artificial intelligence are being used to automate tasks throughout the supply chain, from manufacturing to logistics to customer service. And the Internet of Things is providing businesses with real-time data on the status of their supply chain, allowing them to make more informed decisions. The adoption of Industry 4.0 technologies is essential for businesses that want to remain competitive in the 21st century. These technologies are transforming the supply chain and making it more efficient, agile, and responsive to customer needs.

Industry 4.0 technologies are increasingly being used in supply chains to improve efficiency and effectiveness. The following are motivations for working on this dissertation topic. First, there is a need to understand how these technologies can be used to improve supply chains. This understanding can be used to help companies make better decisions about which technologies to adopt and how to implement them. Additionally, this understanding can help policymakers make decisions about investing in these technologies and regulating their use. Second, there is a need to understand the impact of Industry 4.0 technologies on supply chains (Fatorachian & Kazemi, 2021). These technologies have the potential to greatly improve the efficiency of supply chains, but there is a risk that they could also disrupt existing supply chains and lead to Job loss. It is important to understand both the potential benefits and risks of these technologies in order to make informed decisions about their use. Finally, there is a need to address the challenges associated with implementing Industry 4.0 technologies in supply chains. These technologies often require significant investment and can be disruptive to existing operations. Additionally, there is a lack of standardization across these technologies, which makes it difficult to compare and select the best option for a particular supply chain. These challenges need to be addressed in order to make Industry 4.0 technologies more accessible and effective.

Technologies such as big data, the Internet of Things, advanced analytics, and robotics are being combined and applied in new ways across the manufacturing sector, from factory floors to the back office (Frank, Dalenogare & Ayala, 2019). Big data, the Internet of Things, advanced analytics, and robotics are being utilized in new ways across all aspects of manufacturing. These technologies have the ability to streamline processes, increase efficiency and optimize workflows. In terms of the factory floor, these technologies can be used to monitor machinery, identify issues and predict maintenance needs. In the back office, these technologies can be used to manage inventory, track orders, and optimize production schedules. By utilizing these technologies, manufacturers are able to increase productivity, improve quality and reduce costs. The use of big data and the Internet of Things has allowed manufacturers to collect massive amounts of data from various sources. This data can be used to identify patterns, trends, and correlations. Advanced analytics can then be used to make predictions and recommendations. For example, data from sensors on the factory floor can be used to identify when a machine is about to malfunction. This information can then be used to schedule maintenance before the issue occurs. Robotics is also being used in new ways across the manufacturing sector. Robotics can be used to automate repetitive tasks, freeing up employees to focus on more complex tasks. Robotics can also be used for dangerous or difficult tasks, such as working in extreme temperatures or difficult-to-reach places. By utilizing robotics, manufacturers are able to improve safety, increase productivity and reduce costs. These Fourth Industrial Revolutionary Industry 4.0 technologies are changing the face of manufacturing and are having a profound impact on supply chains. In many ways, the supply chain is at the heart of Industry 4.0. By connecting disparate systems and data sources and applying advanced analytics, supply chain managers can gain new insights into the movement of goods and materials. This can help to optimize processes, reduce costs and improve customer service. The adoption of Industry 4.0 technologies is still in its early stages, but there are already some clear benefits to be gained. The use of data analytics in the supply chain can lead to a 5-7% improvement in efficiency. It is evident that the use of robotics can cut costs by up to 30%. One of the most important trends is the move towards the integration of data across the entire supply chain. In the past, data has been siloed within individual businesses (Zheng et al., 2021). However, Industry 4.0 technologies are making it possible to share data between different parts of the supply chain. This results in a more efficient and effective supply chain overall. Another trend that is emerging is the move towards more automated supply chains. Industry 4.0 technologies are enabling businesses to automate more of their processes. This results in a more efficient supply chain that is less reliant on human labor.

In a world where the industrial and commercial supply chains are becoming increasingly complex and difficult to manage, many experts are heralding the rise of Industry 4.0 technologies as a way to help make these systems more efficient and effective. Industry 4.0, also known as the fourth industrial revolution, encompasses a variety of new technologies and approaches that are designed to help manufacturing and other industrial companies to be more agile, adaptive, and responsive to the needs of their customers. One of the major benefits of Industry 4.0 technologies is that they can help to optimize supply chains by reducing waste and improving visibility into the entire system (Fatorachian & Kazemi, 2021). For example, by using data analytics and machine learning, Industry 4.0 technologies can help companies to identify bottlenecks and other inefficiencies in their supply chains. By doing so, they can then take steps to address these issues and improve the overall performance of their operations. Additionally, Industry 4.0 technologies can also help companies to better forecast demand and reduce inventory levels, both of which can lead to significant cost savings. Another benefit of Industry 4.0 technologies is that they can help to improve the quality of products and services. For instance, by using sensors and other devices to collect data throughout the production process, companies can identify problems and potential errors much more quickly and easily (Thames & Schaefer, 2017). This, in turn, can lead to quicker and more effective corrective action, as well as improved overall quality control. Additionally, many Industry 4.0 technologies, such as 3D printing, can also be used to create customized products that are better able to meet the needs of individual customers. Industry 4.0 technologies can also help to improve the working conditions for employees. For example, by automating tasks that are dull, dirty, or dangerous, these technologies can help to improve safety conditions and make jobs more interesting and rewarding. Additionally, Industry 4.0 technologies can also help to provide employees with better access to information and training, which can lead to increased job satisfaction and improved retention rates.

Despite the potential benefits, there are also challenges associated with the adoption of Industry 4.0 technologies in supply chains. One of the challenges associated with the adoption of Industry 4.0 technologies in supply chains is ensuring compatibility between different Industry 4.0 technologies and systems (Mohamed, 2018). This is because different Industry 4.0 technologies might not be compatible with each other, which could lead to issues such as data inconsistencies and errors. Furthermore, incompatible Industry 4.0 technologies could also result in increased costs associated with the need to purchase different technologies or upgrade existing ones. The second challenge associated with the adoption of Industry 4.0 technologies in supply chains is ensuring that these technologies are able to seamlessly integrate with existing supply chain systems and infrastructure. This is important because a lack of integration could lead to disruptions in the supply chain and a decrease in overall efficiency. Furthermore, it might also be necessary to make changes to existing systems and infrastructure in order to accommodate Industry 4.0 technologies, which could lead to additional costs. The third challenge associated with the adoption of Industry 4.0 technologies in supply chains is managing and safeguarding data security and privacy when using these technologies (Raj et al., 2020). This is because Industry 4.0 technologies often make use of sensors and other devices that collect data, which could include sensitive information such as customer data and proprietary company information. If this data is not properly secured, it could be leaked or stolen, which could have serious consequences for the company and the individuals involved.

The fourth challenge associated with the adoption of Industry 4.0 technologies in supply chains is addressing potential workforce disruptions that could result from the automation of certain supply chain tasks and processes. This is because the automation of tasks and processes could lead to job losses, as well as a change in the skillset that is required for certain positions. As such, it is important to ensure that any workforce disruptions that do occur are managed in a way that minimizes the negative impact on employees and the company as a whole (Enrique et al., 2021). The fifth challenge associated with the adoption of Industry 4.0 technologies in supply chains is obtaining the necessary funding to implement these technologies. This is because the implementation of Industry 4.0 technologies can be costly, and companies might not have the financial resources to cover the costs. As such, it is important to secure funding from sources such as investors or government grants in order to ensure that the implementation of Industry 4.0 technologies is successful. The sixth challenge associated with the adoption of Industry 4.0 technologies in supply chains is managing the expectations of stakeholders in terms of the benefits that these technologies can bring to the supply chain. This is because it is important to ensure that stakeholders are realistic in their expectations and that they understand the potential limitations of Industry 4.0 technologies. Otherwise, there could be disappointment among stakeholders if the expected benefits are not realized. The seventh challenge associated with the adoption of Industry 4.0 technologies in supply chains is ensuring that these technologies are used in a way that is ethical and responsible (Masood, T., & Sonntag, 2020). This is because industry 4.0 technologies have the potential to be used for unethical or irresponsible purposes, such as spying on employees or customers or engaging in price gouging. As such, it is important to put in place safeguards to ensure that Industry 4.0 technologies are used in a way that is ethical and responsible. The final challenge associated with the adoption of Industry 4.0 technologies in supply chains is addressing potential disruptions to the supply chain that could result from the adoption of these technologies. This is because the adoption of Industry 4.0 technologies could lead to changes in the way that the supply chain operates, which could, in turn, lead to disruptions. As such, it is important to plan for and manage any potential disruptions that could occur so that the supply chain can continue to operate smoothly.

A supply chain is a network of suppliers and customers that are involved in the production, transportation, and distribution of a product or service. In the past, supply chains were often inflexible and difficult to scale. However, with the adoption of Industry 4.0 technologies, supply chains are becoming more agile and flexible, making it easier for businesses to scale up or down as needed. Industry 4.0 technologies are transforming supply chains from linear, static systems into agile, dynamic networks. This shift is enabling businesses to scale up or down as needed in response to changing customer demands. In the past, supply chains were often designed around the principle of mass production, with little flexibility built in. This inflexibility made it difficult for businesses to respond to changes in customer demand. The benefits of an agile and flexible supply chain include the ability to respond quickly to changes in demand, reduce inventory levels, and improve overall efficiency (Hahn, 2020). Additionally, these supply chains are more resilient and can better handle disruptions. There are several reasons why Industry 4.0 technologies are making supply chains more agile and flexible. First, Industry 4.0 technologies are allowing businesses to collect and analyze data more efficiently. This data can be used to identify bottlenecks and optimize the supply chain. Second, Industry 4.0 technologies are making communication and collaboration between different parts of the supply chain more efficient. This results in a more coordinated and efficient supply chain. Finally, Industry 4.0 technologies are making it possible to automate many tasks in the supply chain. This frees up employees to focus on more important tasks and reduces the need for manual labor. The adoption of Industry 4.0 technologies is benefiting both businesses and consumers. Businesses are able to operate more efficiently and at a lower cost, while consumers are getting products and services that are high quality and meet their needs. In a free market economy, businesses are able to operate more efficiently and at a lower cost because they are able to produce goods and services that are high quality and meet the needs of consumers. This is possible because businesses are able to specialize in the production of goods and services that they are good at and because they are able to compete with other businesses to provide the best products and services to consumers. As a result, businesses are able to keep their costs down while still providing high-quality products and services to consumers.

In addition, in a free market economy, businesses are able to specialize in the production of goods and services that they are good at. This allows businesses to focus on producing the goods and services that they are good at, and as a result, they are able to produce these goods and services more efficiently (Hofmann et al., 2019). This specialization also leads to businesses being able to keep their costs down, as they are not wasting resources on producing goods and services that they are not good at. In the future, individuals expect to see even more adoption of Industry 4.0 technologies in the supply chain as businesses continue to look for ways to improve their efficiency and competitiveness. Flexibility and scalability are important characteristics of a well-functioning supply chain. Flexibility and scalability are important characteristics of a well-functioning supply chain. First, a flexible supply chain can quickly adapt to changes in demand or supply, while a scalable supply chain can easily expand or contract to meet changing needs. Second, it is able to respond quickly to changes in demand or supply. For example, if a company suddenly needs to increase the production of a certain product, a flexible supply chain can quickly ramp up production to meet the new demand. Similarly, if a company needs to reduce the production of a certain product, a flexible supply chain can quickly adjust production levels to meet the new demand. Finally, it can easily expand or contract to meet changing needs. For example, if a company needs to increase the production of a certain product, a scalable supply chain can quickly add new production lines or additional capacity to meet the new demand. Similarly, if a company needs to reduce the production of a certain product, a scalable supply chain can quickly remove production lines or capacity to meet the new demand (Koh, Orzes & Jia, 2019). The agility that Industry 4.0 technologies bring to the supply chain results in a more responsive and adaptive supply chain. This allows businesses to better meet the needs of their customers and the market. In the future, we can expect to see even more adoption of Industry 4.0 technologies in the supply chain as businesses continue to seek ways to improve their efficiency and competitiveness.

1.2 Research Objectives

The goal of this research is to investigate the effects of the COVID-19 pandemic on Industry 4.0 technologies.

1.3 Research Questions

The research will focus on the following research question:

  1. What impacts did the COVID-19 pandemic have on industry 4.0 technologies?

CHAPTER TWO

2.1 LITERATURE REVIEW

 

The present world is highly technology driven and everything we see around us are targeted at being tightly knit ecosystems to reduce effort and improve efficiency in operation. This applies not only to consumer products, but also to commercial and industrial products and solutions. After the industrial revolution, rapid development happened in this arena to integrate smart technology in the form of automation with the use of information technology & internet in amalgam with electronics.[1]

 

Industry 4.0 has been progressively transforming businesses of the world by employing technologies, to empower the various facets of business such as manufacturing, sustenance & maintenance, supply, logistics and retail divisions involved in many and most industries. It has been a major contributing factor towards the development of smart technologies in the manufacturing sector.[2] This has paved the way to newly emerging, innovative and highly effective operational and business concepts. [1,3]

 

Acatech in their report organise Industry 4.0 into the following scenarios: (1) across the complete industry, (2) across the life of the product and (3) across the manufacturing division. While being implementing across the complete industry, integration of Industry 4.0 is proposed across in both inter-company and intra-company. While implementing across the life cycle of the product, the integration has to be done starting from the point of acquiring the raw material till the delivery of the product to the end user. While implementing across the manufacturing division it involves integration across the factories, lines and adjoint divisions such as product development, logistics, supply chain and marketing. [7]

 

 

2.1.1 Industry 4.0 in Manufacturing and Logistics

 

Industry 4.0 was originally intended to accelerate the automation and computerisation of manufacturing processes. Tang and Veelenturf (2019) discuss about the various technologies that are associated with Industry 4.0, which gives us an insight into how the manufacturing sector can be impacted with the employment of smart technologies.

 

Tang further investigates the various ways in which Industry 4.0 helps in boosting manufacturing processes, like improvement of delivery speed, increasing reliability, improvement of efficiency and reduction in cost of operation. A comparison is established by Tang on planes of competition, social value creation and sustainability. Major technologies that are discussed are Internet of Things, Drones, 3-D printing, Robotics, Autonomous Vehicles, Data Analysis, Artificial Intelligence and Blockchain.

 

3-D printing or additive manufacturing as the name suggests is used to develop 3-D objects using a CAD design. Westerweel et al. (2018) states that 3-D printing prototypes in house can offset the higher cost by offering reduction in reduced cost of logistics and reduction in lead-time. It also offers flexibility in the components that are produced, helping increase availability.

Robotics are one of the fastest growing sectors that are helping solve issues in logistics and the supply chain. Tang (2018) talks about BMW employing advanced robotic systems alongside their human workforce in their production line in South Carolina. Similarly in 2012, Amazon procured Kiva, a robotic system which improves productivity at Amazon fulfilment centres by helping movement and packaging of packages to be shipped.

 

In Shanghai’s Jinshan Industrial Park, Ele.me, who is a part of Alibaba, started delivering meals quickly using their fleet of drones from more than one hundred restaurants. Drones could become an effective mode of high-speed shipment delivery or even an alternative to delivery by road for areas with poor connectivity on land.

 

The world presently is majorly dependent upon the usage of internet for communication, which is forming the basis of business, trade, news and entertainment. Internet of things (IOT) has been rapidly developing over the last decade promoting remote access and control over devices, machine and equipment. This has become a major aid to the manufacturing sector as IOT is being put to use in multiple scenarios, due to the easy integration of modules and sensors even into existing systems. Sensors are used to read and deliver data on the condition of machinery used in the production lines, track the position and location of packages that are being shipped and a variety of other applications. Inventories can be monitored and data can be collected to help maintain a balanced stock position in real time.

 

The manufacturing sector is also extensively employing artificial intelligence. Artificial intelligence is putting computer intelligence to work, by analysis of existing patterns and coming up with human-like suggestions to proceed forward. Artificial intelligence is being put to use along with IOT to aid in maintenance, manufacturing, logistics and shipping. Many companies, use IOT to monitor the condition of their manufacturing equipment, and use AI to predict a possible breakdown and possible solutions that could help reduce downtime or even conduct preventive maintenance. This in turn would reduce operating costs for the organisation.

 

With all this the industry also accumulates data which is very vital. This collected data is vital as it helps understand and better build predictive models to be able to close the gaps in supply and improve the reach of products and services into the market. It also helps improve efficiency, reduce costs and maintain assets in much better conditions.

 

2.1.2 COVID-19 – The pandemic & it’s effects

 

COVID-19 had and has affected the world in a very strong way and this brought about so many changes in the way of life of people. Local governments had implemented stringent precautions to stop additional harmful spread of the virus as a result of the shocks caused by the COVID-19 outbreak. Measures, such a mandatory national lockdown, had been put in place with the goal of isolating patients and lowering the transmission rate in many nations (Chamola et al. 2020). Jones et al.2021 states that such implementations by governments led the industry to have to respond quicky with various strategies. Due to the global disruption of the delivery of commodities, these restrictions have not only impacted local manufacturing and marketing, but have also caused companies to close and a lack of resources (Tang et al. 2021). Governments had separated the non-essential sectors, which have been forced to suspend operations, from the vital sectors, which could continue to operate (Carletti et al. 2020). According to Xu et al. (2020) various governments across the world had varied response time in implementing the restriction mandated due to covid. Nearly the whole world went into complete lockdown by the end of March 2020, prohibiting all travel and forcing the closure of all companies that are not absolutely necessary. Schools and institutions were also closed. Production and employment decreased significantly as a result, at record rates or in excess of the reduction seen during the Great Recession of 2008 (Sheth 2020). Shutdowns or capability suspensions occurred in nearly all industrial sectors as a result of the lockdown in numerous cities and supply of labour, raw materials, and consumables was limited (Paul and Chowdhury 2020; Singh et al. 2020a; Xu et al. 2020; Zhu et al. 2020). Small and medium-sized businesses (SMEs) in particular have seen immediate negative repercussions as a result of logistical problems, lower capacity utilization, and demand-side effects (Juergensen et al. 2020). The limitations placed on eateries, cafés, shopping malls, and general leisure and sporting activities have indirectly affected manufacturing enterprises (Juergensen et al. 2020; Seetharaman 2020). The production in allied sectors decreased as a result of the drop in demand for these activities.

 

Governments began to consider the value of remote work for industrial enterprises as a result of the need to implement social distancing (Kanda and Kivimaa 2020; Omary et al. 2020). These procedures, which were adopted to prevent disease transmission, have had a significant impact on consumer behaviour and consumption patterns (Diaz-Elsayed et al. 2020). These restrictions have occasionally forced a radical restructuring of workplace and retail areas. Many nations have established standards that must be followed in both indoor and outdoor settings, including physical distance and the wearing of masks (Shen et al. 2021; Telukdarie et al. 2020). The best way to stop an outbreak of illness is likely to socially isolate yourself and wear a face mask. Compulsory home quarantine is another step to stop the illness from spreading, and it is applicable to both confirmed cases and to anybody who has come into contact with a confirmed case (Gupta et al. 2020). The COVID-19 virus’s propagation further illuminated the potential for a significant rearrangement of operations, but it also highlighted that difficulties that have to be overcome (Bolisani et al. 2020). Face masks and physical distance might reduce productivity in some businesses that often require reconfiguration, creating operational difficulties and necessitating alteration of workday schedules (Garlick et al. 2020; Kurita et al. 2020; Telukdarie et al. 2020; Weersink et al. 2020). In order to implement these measures, facilities for production and offices had to be redesigned, and workers needed access to the right technology for remote work and video conferencing equipment (Okorie et al. 2020). Working remotely can lead to less human interaction, therefore leading to less effective coordination (Ali Abdallah 2021). In general, much effort has also been put towards retraining skills to enable a quick switch to working remotely, which occasionally presented challenges as well (Rapaccini et al., 2020; Sharma et al. 2020). Despite these challenges, the majority of manufacturers concur that future processes will be reengineered, with social isolation and remote work persisting long after the pandemic ends (Moutray 2020).

 

2.1.3 Adaptations due to Covid-19

 

Manufacturing organizations have been obliged to undertake significant organizational adjustments as a result of the adoption of social distance rules in order to maintain chances for the continuation of business operations. Most activities were already halted at the outset of the crisis, and precautions were taken to lower the danger of infection (Rapaccini et al. 2020). In several businesses, employees were able to operate remotely by utilizing Internet Communication Technologies like email, video conferencing, and cloud file management (Garlick et al. 2020).

 

Surprisingly, despite the challenging nature of field operations, the transition from office to remote work has typically gone well (Rapaccini et al. 2020). Due to the experiences gathered during the worldwide shutdown, the viability of remote work has therefore been confirmed in a variety of industry sectors, and it is generally considered to be a potentially feasible option in the future as well (Wang et al. 2020). Given that many manufacturing businesses anticipate that future production processes will be designed “with social distancing in mind,” working remotely may also be seen as a structural mechanism that was born out of the necessity to preserve social distance (Moutray 2020, 248). Safety and health procedures as well as remote work circumstances have evolved into essential factors for manufacturing businesses to rate their suppliers (Petrudi et al. 2021).

But because remote work has been adopted too rapidly, “a cultural revolution in how individuals approach their job is still needed,” according to Rapaccini et al. (2020). Organizations must become more adaptable, and this includes taking steps like renewing employees’ skills by training them again to make them fit for remote work (Okorie et al. 2020). Cloud computing, Internet of Things (IoT), and big data analytics are examples of digital technologies that may make remote and autonomous operations more possible (Niewiadomski 2020; Telukdarie et al. 2020). Where direct touch is impeded by limitations, the use of visualization technologies can assist in carrying out field activities (Akpan et al. 2020).

 

Manufacturers have required to ensure that all workplaces are clean and safe to safeguard employees in offices and in production divisions in order to reduce the likelihood of infection. Manufacturers have made an effort to strike a compromise between maintaining factory safety standards and limiting operational disruptions (Moutray 2020). In fact, since the COVID-19 epidemic broke out, every business has had to sterilize the workplace (Ali Abdallah 2021). Thus, for company continuity, PPE and new cleaning techniques are required (Garlick et al. 2020). In locations where the situations were too dangerous for human exposure, the employment of robotic technologies helped, given the ability to do a task without exposing people to the condition (Wang and Wang 2021).

 

2.1.4 Adaptation of Technology to mitigate the effects of COVID in Manufacturing

 

Companies, government organizations, and people have all been impacted by the acceleration of the digital transformation brought on by the introduction of COVID-19 (Almeida et al. 2020). People have become accustomed to using digital tools that allowed for remote work and virtual learning during the pandemic. While e-commerce and home delivery, supported by Information and Communication Technologies (ICT), have grown in popularity as a result of stay-at-home policies, Voice-over-Internet-Protocol (VoIP) software, such as Zoom, Microsoft Teams, and Google Meet, have quickly become a common tool for hosting work meetings and online classrooms (Jiang 2020). Although it is difficult to execute production activities remotely, digital technology may be used to facilitate some remote operations, automate procedures, enabling equipment to operate on their own, and eliminate the need for on-site staff (Kamal 2020). The function of technology in combating the pandemic has only been briefly discussed in a historical era strongly defined by the digital transformation of industrial businesses and the various scientific achievements connected to the “Industry 4.0” paradigm (Zheng et al. 2021; Frazzon et al. 2021; Ivanov et al. 2021a). There isn’t much research connected to the technology for supporting factory operating procedures; instead, most published studies have focused on the possible uses of technologies for supply chain resilience (Spieske and Birkel 2021).

 

Manufacturing has been impacted by social distancing and the imposition of working remotely. As a response to the pandemic conditions, workplace redesign and workforce restructuring might be referred to as response activities. Significant influence on industry should be taken into account when considering governmental measures for pandemic management, such as lockdowns and required industrial closures. Therefore, response efforts in this area should include preparation for and adaptability to a remote work environment. Networks and digital ecosystems powered by data and technology are becoming more prevalent in manufacturing. End-to-end visibility may be created using data analytics, additive manufacturing, and Industry 4.0 using a configurable flow of materials and digital flow of information (Dolgui and Ivanov 2021). Big data analytics, cloud computing, artificial intelligence, robotics, and artificial intelligence have a significant impact on industrial resilience. Technologies including robotics, digital twins, blockchain, and additive manufacturing, have attracted attention in the manufacturing sector (Chen and Cao 2020; Ivanov 2021d; Ivanov and Dolgui 2021b; Shen et al. 2021; Singh et al. 2020b). Specific digital technologies, such machine learning algorithms and augmented reality systems, may be introduced to production lines to help them become flexible to changes, resilient to faults, and aware of the need to upgrade operators’ abilities (Baroroh et al. 2020; de Giorgio et al. 2021). The significance of artificial intelligence and digital technology in industrial resilience will undoubtedly grow in the future. Automation, end-to-end visibility, and remote production control can help with both proactive recovery and preparedness for pandemics and pandemic-like events. Therefore, digital manufacturing trends have a favourable effect on resilience.

 

 

CHAPTER THREE

METHODOLOGY

3.1 Introduction

This chapter elaborates on the methods used to complete this investigation. An overview of the research process, data collection and analysis techniques are discussed and explained. The validity of this study and the reasons for choosing the methods are also presented to ensure clarity.

This chapter is separated into four sections: Initially, section 3.2 provides an overview of the process and is followed by section 3.3, which explains the research design for the dissertation. The design elaborates on the ideology and philosophy behind the investigation and shows the cause for the research methods, the approach and the techniques used. Section 3.4 elucidates the undertaken research in sequential order. The last section mentions the challenges faced through the dissertation.

3.2 Research Process

The complete research process was split into four stages to simplify the process and form a framework and timetable for the dissertation. The stages were the literature review, initial data collection, the interview process, and analysis of the obtained data. The literature review is essential to form an initial idea of the topics to investigate further and provide background knowledge. It also helped to create a draft of the interview questions and the topics to be discussed with the participants. A literature review is a systematic “A literature review is a systematic and reproducible method for identifying Chapter 3: Research Methodology 89 and synthesising the existing body of recorded work generated by researchers or scholars.” (Fink, 2013)

The initial data collection followed this process. This is essentially the study of the requirements to conduct interviews and the study of companies related to the chosen topic. The purpose of this initial study can be generalised into four areas: “(1) to find problems and barriers related to participants recruitments, (2) being engaged in research as a qualitative researcher, (3) assessing the acceptability of observation or interview protocol and (4) to determine epistemology and methodology of research” (Janghorban, Roudsari and Taghipour, 2014). This allowed the interview process to be refined and identify the research techniques applied in the analysis. The initial study and data collection consisted of reviewing various kinds of literature and exchanging dialogues with some professionals in the field of research. This allowed a formation of a rough idea of the direction of the analysis.

The third stage was the interview process of the chosen six professionals in the field of Industry 4.0 application from Canada and India. All the interviews were semi-structured, and the reason for choosing this method will be provided later in this chapter. The number of interviewees was chosen to be six due to constraints such as time and availability. The data collected from these interviews were then analysed using thematic analysis as a primary tool. The results of the analysis were then put under scrutiny by corroborating the completed literature review.

3.3 Research Design

This section of the methodology outlines the various elements which devise the design of the research conducted in this dissertation. The elements are philosophy, approach, strategy, and methods.

 

Figure 3.1: Research design structure

3.3.1 Philosophy of Research

“The research philosophy sets the tone for the researcher’s thoughts, processes, and appreciation of the obtained data” (Strang, 2015). According to Strang (2015), the primary purpose of the establishment of philosophy is the definition of perspective and to serve as a standard line for other researchers to understand the presented viewpoint and analysis of the research. The four philosophical positions used to approach any research are Positivism, Pragmatism, Realism, and Interpretivism.

Positivism is an approach where theories and evidence mainly drive the research. Strang (2015) mentions that this approach is rarely used to its most authentic form and is always mixed with some pragmatism as a certain amount of flexibility is required. A positivist approach is mainly used in analysing quantitative or mixed data and using deductive research methods instead of inductive ones.

Pragmatism is a flexible research philosophy as it allows the researcher to collect a round of qualitative or quantitative data, refine the theory, and proceed with further data collection based on the collected data (Strang, 2015). The theory guides the investigation and allows the researcher to peruse the data according to their ideas. Researchers using this approach can use quantitative, qualitative, or mixed methods.

The third philosophy, Realism, is built on the philosophy of positivism. “The concept aims to carry the study forward with not just the situation or issue being researched, but also the cause and effect” (Brinkmann, 2017). This is a highly time-consuming process and goes into detail about the chosen research topic, and requires a definition of the cause of the research. The analysis needs to be based on the causes and must try to find a solution to the causes found. “It is not enough to describe and understand what happens in contextually framed situations. For the realist, the goal is to go beyond the situation and pinpoint the mechanism that causes something to happen, given specific contextual features” (Brinkmann, 2017).

The final philosophy, Interpretivism, aims to better understand the real world and the implications of the researched topic. “The core idea of interpretivism is to work with these subjective meanings already there in the social world; that is to acknowledge their existence, reconstruct them, understand them, avoid distorting them, and use them as building blocks in theorising” (Goldkuhl, 2012). The standard method used to obtain data for an interpretivist approach is a qualitative interview with a small sample with a small amount of variation such that the data that is collected depicts various viewpoints on the research to be undertaken and has a personal account of the events that are related to the research questions to be answered. Hence this method was most applicable to this dissertation and was chosen as the selected philosophy to be followed.

There are very little background researches for this particular investigation where I hope to investigate the application of Industry 4.0 into Logistics and Supply Chain processes. This is a growing field of research even though the concept of smart technology application in various industries has existed for a long time. I hoped to consider the recent pandemic of COVID-19 and its impact on the companies that employed smart technology in their systems. This made the information available from a qualitative point of view highly necessary as the quantitative data may not provide the required information. Thus, this dissertation follows a pragmatic approach. The data used is qualitative, and this approach allows the collection of various viewpoints.

3.3.2 Approach of Research

The choice of an Interpretivist approach for the study implies that the research approach is flexible. A qualitative approach is suited for exploratory research where minimal information is available. Hence, the approach’s inductive nature helps generate a theory to use as a research base. Choosing between quantitative, qualitative, and mixed methods methodology needs a thorough understanding of the available information, the field in which the study is to be conducted, and the nature of the study. This dissertation aims to analyse the acceptance of new technology into logistics and supply chain processes and the change the employed technology brought to the companies after the pandemic. The available data on most smart technologies being applied in manufacturing, transportation and supply chain are driven mainly by numbers and are highly quantitative. The required level of research cannot be completed by only using this data and requires the opinion and comments of people involved in the field. Keeping these requirements in mind, this investigation adopts a qualitative research approach, which was obtained using semi-structured interviews.

3.3.3 Strategy of Research

Implementing a grounded theory seems like the most viable option by choosing an interpretivist research philosophy with a qualitative approach. This theory was developed in the early 1960s by sociologists Barney G. Glaser and Anselm L Strass, who proposed that qualitative analysis is highly variable, and each data could be used to generate its own theory (Charmaz, 2014).

Charmaz (2014) highlights the defining elements as the following: (1) The parallel connection between analysis and collection of data. (2) Not possessing a preconceived opinion of how the data should be interpreted and constructing the themes and codes. (3) Making constant comparisons during each stage of the analysis. (4) development and updating of the theory in each analysis stage. (5) Sample the obtained data while aiming toward constructing the theory and not for population representativeness. Finally, (6) Conducting the literature review after an independent analysis and a review of the obtained information. Using these principles, grounded theory is a methodology which needs continuous comparison and revision to form a theory that needs to be constantly updated at each stage after a new factor emerges. The qualitative data collection process is then undertaken after establishing a theory. At the same time, the authors who proposed the theory to be used flexibly, Charmaz (2014), views grounded theory as a set of postulations and practices that can be implemented after scrutiny of the type of investigation.

This research will use specific methods and principles of Grounded theory wherever applicable, such as semi-structured interviews and a thematic analysis of the obtained data, hence the term Partial Grounded Analysis.

3.3.4 Methodology of Research

The research methods that were implemented in this dissertation are (1) Literature review, (2) Semi-structured interviews (3) Thematic Analysis. The semi-structured interview was chosen for collecting qualitative information, and thematic analysis was used for data analysis. The reason for the choice of semi-structured interviews was the requirement of constant reiteration of the collection tools used for obtaining information. The conduction of semi-structured interviews within the guidelines of grounded theory requires the data analysis to be done constantly as the information is obtained from the interviewees, which aided in the thematic analysis as the initial collection of data only focused on prerequisite knowledge on topics to be discussed and the research methods to be used.

The choice of a pragmatic approach made the initial data collection a requirement as the researcher must interpret the data consistently to obtain a consistent response from the interview participants. “The use of qualitative descriptive approaches such as thematic analysis is suitable for studies where the researchers wish to employ a relatively low level of interpretation, in contrast to grounded theory or hermeneutic phenomenology, in which a higher level of complexity exists in the interpretation of data” (Vaismoradi, 2013). Hence the required minimal guidelines were chosen from grounded theory to keep the method flexible for data collection and analysis.

“A semi-structured interview is a variation of a structured interview which offers more flexibility in obtaining subjective responses from the participants” (McIntosh and Morse, 2015). This aids in acquiring personal anecdotes from the interviewees, which can help aid in the analysis and vary the interviewer’s opinion. “The data from semi-structured interviews cannot be obtained from structured questionnaires, participant observation or analysis of the literature” (McIntosh and Morse, 2015). The technique used to obtain interviewees was Snowball sampling. “This is the process where the contact information of other respondents is obtained using an initial respondent” (Noy, 2008). This was achieved through conducting a semi-structured interview with the initial respondent. They were asked to provide any contact information of professionals in the field of Logistics and supply chain field or any related company. This process was repeated until the requirement for the dataset was achieved by interviewing six respondents.

Thematic analysis examines the obtained narrative by breaking the data into smaller units and describing the “themes” in detail. “A thematic analysis of data provides an account of the data such that it is purely qualitative, comprehensive, and refined. It identifies and analyses patterns within the qualitative dataset” (Braun and Clarke, 2006). The steps to be undertaken to conduct a thematic analysis are quite simple. The collected qualitative data must be transcribed, and the initial ideas must be noted to make identifying patterns or themes easier. This is followed by generating initial codes by highlighting notable features across the dataset. The codes are then scoured for themes and collated with the required research output, naming them accordingly. The process is then completed by generating a report with the required analysed data.

3.4 Undertaken Research

This section of the methodology outlines the different processes that have been completed through the course of this dissertation. The first process that was completed was the literature review which was followed by the initial data collection. The data collection provided the information required for the semi-structured interview through online methods. The analysis of the collected data followed this to interpret the information, answer the research questions, and discuss the challenges and implications of the topic.

The literature review was carried out while following the methods and recommendations made by Fink (2013) with a structured and informative approach. The existing data published by scholars worldwide were selected and scoured for related information. This was carried out using online services like Google Scholar, and this redirected the reading focus to various journal repositories like Springerlink and Science Direct. To find related dissertation examples for a sample structure and workflow, online resources like EThOS were accessed using the Library at the University of Southampton. The advantage of using these repositories is the large selection of peer-reviewed journals, books, and academic publications around the chosen “industry 4.0 technology” topic. The keywords used to select the literature were “industry 4.0”, “qualitative analysis”, “supply chain”, “logistics”, “covid -19”, “smart technology”, “IoT”, “RFID”, “automation”, and “smart warehousing”. The relationship between these terms and the chosen topic is discussed in chapter two. The investigation of these topics and the completion of the literature review and initial data analysis allowed the formulation of the final data analysis discussed in the next chapter.

An initial data analysis followed this to gain information on the qualitative analysis process and the number of participants required to obtain the necessary data for answering the research questions. Since the process of conducting semi-structured interviews is an unfamiliar concept, I had to study the various methods available and choose the philosophy to be followed. Keeping in mind the various challenges and constraints of the dissertation, the Interpretivist philosophy of qualitative analysis using semi-structured interviews was selected as the data collection method. After discussion with the supervisor for the dissertation, the professionals in the field to be contacted were chosen to be six in number, and the company was contacted to obtain an initial confirmation of participation. Once the confirmation was received, the permissions for conducting the interviews were to be obtained from the University of Southampton and the Ethics committee at the university.

Any research that involves human participation needs ethical approval from the above organisations. This required a form to be submitted by the researcher through the supervisor to the Faculty of Social Sciences, Southampton Business School. During the application for ethical approval, the interview questions were formulated and reviewed by the supervisor, who made certain changes to the questions to obtain better answers from the participants to obtain data related to the research questions. The participants were informed that their identities and personal information would be confidential. Since the data being collected could be confidential data from the company’s perspective, efforts were made such that all sensitive information was removed from transcripts and kept as a reference if required. Ethical concerns regarding human participants were informed to the participants in detail, and any prerequisite information requested regarding the research and the University policies were provided for their reference.

The company chosen for the case study is 5G Energy Ltd., based in Canada, with branches in the USA, Mexico, and India. This company was selected to gain a different perspective on applying smart technology in logistics and supply chain operations. Every qualitative study obtains data from the consumers of “industry 4.0 technology”, which would require contacting various professionals and obtaining the required permissions from multiple companies. The company has been in business since 1999 and hence has a lot of experience in developing smart technology. The developed products have been applied to various industries ranging from large to small manufacturers. The company has three products that help in various aspects of the production process, which are elaborated on in the data analysis section.

This is a long process and was difficult to carry forward with the time constraint for the research. The chosen method for obtaining participants was “Snowballing”, and the initial contact was made through friends who had personal connections with the Innovation and Technical Leads of the company. The other participants were contacted through them, and a semi-structured interview was completed for each of them during August 2022. The participants were spread across different locations, which provided various accounts for the same questions as the experience is different for each country. Four of the participants were from Canada, where their headquarters is situated, and two of the participants were from the Indian branch. The duration of each interview was 30 minutes on average, and all the interviews were conducted through the online meeting platform called “Zoom”. This platform was chosen due to its ease of access and the ability to record the interactions. The recordings were then transcribed using the transcription software “Descript”, which provided an accurate transcription of the dialogue between the interviewer and the interviewee. This was an interview where the participants were only on call and not on video as they did not feel comfortable with the latter. The consent was obtained from each participant through the consent form provided by the University of Southampton.

A detailed account of their experiences and opinions regarding their products and the development processes was obtained, allowing a thorough analysis process. To assist with the data analysis, the 6-step process described by Braun and Clarke (2006) was used as the framework, and a thematic analysis was conducted. The steps described by Braun and Clarke (2006) were: (1) Familiarising the data, (2) Generating initial codes, (3) Searching for themes, (4) Reviewing the themes and rewriting them, if necessary, (5) Defining the themes and categorising them according to research questions and goals, and (6) Writing up the analysis and providing a detailed account of the researcher’s understanding. The initial transcription using the software is simple. Still, it is a powerful tool that transcribes each voice recording porting in detail, so the filler words needed to be removed, and a data “cleaning” had to be completed. This allowed a thorough inspection of the obtained data and made familiarising the data much quicker. The next step was generating initial codes, which provided a deeper understanding of the points made by the participants of the interview and resulted in a better generation of themes and sub-themes. The themes were then reviewed for accuracy and similarity to the objective of the dissertation. The results were promising as the obtained themes related to the challenges and problems faced while deploying an “industry 4.0” product known as “BorgConnect”. The interviewees were from high positions in the company and had a complete understanding of the requirements of the consumers. This allowed the collection of comprehensive data with various related themes and points. The analysis of the themes and codes was then carried out by the researcher to relate the obtained data and conduct a literature review such that the research questions were answered.

The number of challenges that must be addressed while conducting qualitative research is always high. “The three recurrent challenges when performing qualitative studies are reflexivity, transferability and interpretation and analysis” (Malterud, 2001). The first challenge, reflexivity, refers to the researcher’s requirement to have a flexible viewpoint such that all areas of that data are comprehensively researched in line with the research objectives. A constant reflection of the findings and literature must be achieved. This allows the researcher to form an idea of the conclusion and the recommendation while carrying out the research process rather than at the end. The second challenge was “transferability”, which refers to applying the research from a worldwide perspective rather than a single country. This research was conducted across two countries where the conditions of work and business are not the same, namely India and Canada. The participants also gave accounts of their technology being applied in the United States of America. This requires a high amount of generalisation of the research such that the findings and conclusions reached apply to all the related regions. The findings obtained, however, did not require much generalisation as the company functioned as one unit rather than three separate entities. The last and most important challenge was the interpretation and analysis, where the researcher must maintain a singular thought process and philosophy and must not be swayed by any personal background information. No misinterpretation of the data should occur, and the research goals must not change due to sudden changes in beliefs.

The time constraint of the research was a huge challenge as it required a lot of time management and scheduling. The semi-structured interviews had to be conducted in a rushed manner as the permission that was required took a lot of time to be approved. Since the interviewees were in high positions and in different time zones due to differences in location, the process took longer than planned.

CHAPTER FOUR

4.1 RESULTS AND DATA ANALYSIS

4.1.1 Introduction

Thematic data analysis is a method used to analyze data sets to identify patterns and themes. This method is often used in research to understand better a particular topic (Braun & Clarke, 2012). A few steps are typically followed to carry out thematic data analysis. First, the data set is divided into smaller units of analysis, such as individual cases or documents. Next, the researcher looks for patterns and themes within these units of analysis. Finally, the researcher interprets these patterns and articles to understand better the data set as a whole (Joffe, 2012). Thematic data analysis is a valuable tool for researchers looking to gain a deeper understanding of a particular topic. This method can identify patterns and themes that may not be immediately apparent.

4.1.2 P1 Transcript

The main themes that emerged from this interview were:

  • The challenges of communication and coordination during the pandemic.

The pandemic has presented new challenges in communication and coordination for companies with employees based in different locations. One of the biggest challenges is coordinating between different time zones. This can be difficult when teams are trying to communicate via email or other messaging platforms, as there can be a delay in receiving replies. Another challenge is related to the availability of team members. Some team members may be unable to work due to the pandemic, while others may work from home or in different parts of the world. This can make it difficult to coordinate work tasks and lead to project delays. To overcome these challenges, companies need to invest in communication and coordination tools that can help to streamline communication between different team members. They also need to implement processes to ensure work tasks can be assigned and tracked effectively. Furthermore, companies need to train team members to use these tools and techniques.

  • The challenges of managing data centers and shipping products during the

Pandemic.

The pandemic has also presented new challenges in managing data centers and shipping products. One of the biggest challenges is related to the accessibility of data centers. Some data centers are located in areas that are difficult to reach, which can make it hard to provide support in the event of an incident. Additionally, the pandemic has resulted in a decrease in the number of flights, which has made it challenging to ship products to customers. This has led to delays in the delivery of products and has resulted in customer frustration. To overcome these challenges, companies need to invest in data center management tools and processes that can help ensure that data centers are accessible and that products can be shipped promptly. Companies must also train team members to use these tools and techniques.

  • The challenges of providing customer support during the pandemic.

The pandemic has also resulted in new challenges in providing customer support. One of the biggest challenges is related to the increase in the number of customer support calls. This is because many customers start using their products again after the lockdown. Additionally, the pandemic has resulted in a decrease in the number of customer service representatives. This has led to longer wait times for customer support calls and has resulted in customer frustration. To overcome these challenges, companies need to invest in customer support tools and processes that can help to ensure that customer support calls are answered promptly. Companies must also train customer service representatives to use these tools and techniques.

  • The need to constantly adapt processes to handle new challenges during the pandemic.

The pandemic has resulted in a need for companies to adapt their processes to handle new challenges constantly. This is because the pandemic has resulted in new challenges in communication, coordination, data center management, shipping, customer support, and other areas. As a result, companies need to invest in tools and processes that can help them effectively manage these new challenges. Companies must also train team members to use these tools and techniques.

  • The importance of emotional support for team members during times of stress.

The participant noted that during the pandemic, it was essential to provide additional support to team members to help them cope with the stress of the situation. This was in contrast to the normal day-to-day operations, where there is typically more of a focus on the technical aspects of the job. The participant also noted that the pandemic presented new challenges beyond the company’s control and that they had to learn to accept these challenges and communicate them to customers.

 

  • The need to customize products to fit the needs of each manufacturing facility.

The participant noted that each manufacturing facility has its unique processes and that it is essential to customize products to fit the needs of each facility. The participant also pointed out that the pandemic had a negative impact on the efficiency of the company’s operations and that this affected the development of new products.

4.1.3 P2 Transcript

The main themes that emerged from the interview were:

  • The importance of customer feedback and validation in the product development process:

It is essential to obtain customer feedback and validation during the product development process to ensure that the product can meet the needs and wants of the target market. This was evident in the above interview, where the participant spoke about how the company had to obtain customer feedback to validate the idea for the new product. The pandemic made this process more difficult, as it was harder to access customers during this time. However, it is still essential to obtain customer feedback and validation to create a successful product despite the challenges.

  • The challenges of conducting customer research and validation during the pandemic:

Conducting customer research and validation during the pandemic can be difficult, as it can be hard to access customers during this time. This was evident in the above interview, where the participant spoke about how the company had to wait six months to access customers and get their feedback. This delay can be costly, as it can mean that the product cannot promptly meet the target market’s needs. In addition, it can also be challenging to obtain accurate feedback during the pandemic, as customers may not be willing or able to provide honest feedback during this time.

  • The need for innovation in product design to create a cost-effective and affordable product:

To create a cost-effective and affordable product, it is necessary to innovate in product design. This was evident in the above interview, where the participant spoke about how the company had to innovate to ensure that the product could be produced cost-effectively. In addition, it is also essential to ensure that the product can meet the target market’s needs at an affordable price. This can be a challenge, but it is necessary to create a successful outcome.

  • The difficulties of developing and deploying products during a pandemic.

The pandemic has had a significant impact on the way products are developed and deployed. One of the main challenges is the lack of face-to-face interaction between team members. This can make it difficult to communicate effectively and understand the work that needs to be done. Another challenge is the impact of the pandemic on supply chains. This can make it difficult to obtain the necessary components and materials to develop and deploy products. The pandemic has also made it difficult for companies to scale their operations, impacting the bottom line.

  • The challenges of working with remote teams.

Working with remote teams can be challenging for several reasons. One of the main challenges is the lack of face-to-face interaction. This can make it difficult to build relationships and communicate effectively. Another challenge is the need to manage different time zones and schedules. This can make it difficult to coordinate work and meet deadlines. Additionally, working with remote teams can also be isolating and lead to feelings of loneliness and isolation.

  • The challenges of working with small and medium enterprises (SMEs).

For several reasons, small and medium enterprises (SMEs) can be challenging to work with. One of the main challenges is the need to build trust. This can be difficult because SMEs are often skeptical of new products and solutions. Another challenge is the need to scale operations. This can be difficult because SMEs often have limited resources and budgets. SMEs can also be difficult to work with because of the need to manage different stakeholders.

  • The impact of the pandemic on supply chains.

The pandemic has had a significant impact on supply chains. One of the main challenges is the disruption of global supply chains. This has made it difficult for companies to obtain the necessary components and materials to develop and deploy products. Another challenge is the impact of the pandemic on logistics. This has made it difficult to transport products and meet customer demand. Additionally, the pandemic has also led to an increase in the cost of goods and services.

4.1.4 P3 Transcript

The themes identified in this interview include:

  • The Impact of COVID-19 on Business Operations.

The outbreak of COVID-19 has had a significant impact on businesses worldwide, with many having to change how they operate to adapt to the new circumstances. For businesses in the manufacturing industry, one of the biggest challenges has been the need to maintain social distancing in the workplace. This has often meant reduced staff numbers and the need to implement new safety measures such as regular cleaning and personal protective equipment. Another challenge businesses have faced the need to source materials from different suppliers to keep production going. This has often been difficult because many suppliers are based in different countries, and the global nature of the pandemic has made it difficult to transport goods around the world. In addition, businesses have also had to deal with the impact of the pandemic on their customers. Many businesses have seen a reduction in demand for their products as people have been forced to cut back on spending. This has often meant that businesses have had to adapt their product ranges and pricing to remain competitive.

  • The Development of New Products.

The pandemic has also had an impact on the development of new products. In many cases, businesses have had to put plans for new products on hold to focus on more immediate needs. However, in some cases, the pandemic has provided businesses an opportunity to develop new products specifically designed to meet customers’ needs in the current climate. One example of this is the development of new products that help to facilitate social distancing. This could include products that help people to stay connected with loved ones, as well as products that help people to stay safe when they are out and about. Another example of a new product developed in response to the pandemic is the development of contactless payment solutions. This has been driven by the need for people to limit their contact with others to reduce the risk of virus transmission.

  • The Shift to Virtual Communication and Meetings.

One of the most significant changes that have taken place as a result of the pandemic is the shift to virtual communication and meetings. This has been necessary to limit the amount of contact between people and reduce the risk of virus transmission. Virtual communication has often been challenging to adjust to, as it can be difficult to replicate the same level of interaction possible in person. However, businesses have often found that it is possible to adapt to new circumstances, and virtual meetings can be just as productive as in-person meetings. One of the benefits of virtual communication is that it can often be more convenient for people. This is because people are not required to travel to attend meetings, which can save time and money. In addition, virtual meetings often allow people to attend from anywhere in the world, which can be beneficial for businesses with international clients.

  • The Challenges of Selling to Small and Medium Businesses.

The pandemic has also impacted the sales process, with many businesses finding it more challenging to sell to small and medium businesses. This is often because small and medium businesses have been hit harder by the pandemic, and many have been forced to reduce their spending. In addition, the shift to virtual communication has made building relationships with potential customers more difficult. This is because it can be more difficult to establish trust and rapport when communicating online. However, businesses have often found that there are still opportunities to sell to small and medium businesses, particularly if they are able to offer products that are relevant to the current climate. For example, businesses that sell products that help to facilitate social distancing or that help people stay safe when they are out and about are likely to find that there is still demand their products from small and medium businesses.

4.1.5 P4 Transcript

The themes that emerged from the interview were as follows:

  1. The difficulties of developing a product during the COVID pandemic.

The COVID pandemic presented a number of challenges for the product development team. Firstly, the team was spread out across different locations, which made coordination difficult. Secondly, the pandemic meant that people were working from home, which made it difficult to maintain a work-life balance. Thirdly, the pandemic made it difficult to communicate effectively, as there were often power cuts or bad network connectivity.

  1. The importance of communication during the development process.

Communication is extremely important during the product development process, as it allows team members to understand each other’s ideas and coordinate their work. Without effective communication, it is easy for misunderstandings to occur, which can lead to delays in the development process.

  1. The difficulty of coordinating a team when members are in different locations.

Coordinating a team when members are in different locations can be difficult, as it can be hard to keep track of everyone’s progress and ensure that everyone is on the same page. Furthermore, different time zones can make it difficult to schedule meetings or communicate in a timely manner.

  1. The importance of maintaining a work-life balance.

Maintaining a work-life balance is important for the development team, as it helps to ensure that team members are productive and happy. When team members are overworked, it can lead to burnout, which can have a negative impact on the development process.

4.1.6 P5 Transcript

The main themes that emerged from the interview were:

  • The role of the administration in a product company:

The administration in a product company has a very important role to play. They are responsible for managing the finances, the human resources, and the company’s overall operations. They need to be very well organized and have a good understanding of the product development process to be successful.

  • The importance of nimbleness and flat structure in a product company:

Nimbleness and flat structure are very important in a product company. This is because a product company needs to be able to react quickly to the market and customer demands. They also need to be able to innovate new products quickly. A flat structure helps to promote this by allowing for quick decision-making and ensuring everyone is on the same page.

  • The challenges of developing a product during the COVID pandemic:

Developing a product during the COVID pandemic can be very challenging. This is because of the restrictions on travel and the need to maintain social distancing. This can make it difficult to coordinate the development team and get customer feedback. Additionally, the pandemic has caused economic uncertainty, making it difficult to secure funding for a new products.

4.1.7 P6 Transcript

The main themes that emerged from the interview were:

  • The difficulties of working during the pandemic.

The interviewee spoke about the difficulties they faced when working during the pandemic. They mentioned that it was difficult to communicate with vendors and that they had to get permission from local authorities to go to certain places. They also spoke about how the pandemic affected the manufacturing process and how they had to adapt their process to accommodate the changes.

  • The importance of having a process in place.

The interviewee spoke about how having a process in place is important to avoid disruptions in the supply chain. They mentioned that their process allowed for different teams to work on different parts of the product simultaneously and that it also allowed for information to be easily shared between different departments.

  • The challenges of developing products for different markets.

The interviewee spoke about the challenges of developing products for different markets. They mentioned that their products have to be able to work in different environments and that they have to be able to withstand different levels of power consumption. They also spoke about how they must be aware of the different market regulations and how this can impact the development process.

  • The importance of smart technology in manufacturing processes and how it can help increase efficiency and reduce waste.

Smart technology can revolutionize manufacturing processes, making them more efficient and less wasteful. By automating tasks and providing real-time information to workers, smart technology can help reduce errors and increase productivity. In the long term, this can help to reduce costs and increase competitiveness in the marketplace.

  • The challenges of implementing smart technology in manufacturing are logistics and supply chain management.

One of the main challenges of implementing smart technology in manufacturing is managing the logistics and supply chain. This is because smart technology often requires different components from suppliers, which must be coordinated to work together. This can be a challenge for manufacturers, who need to ensure that all the components are compatible and that there are no delays in the supply chain.

  • The potential benefits of smart technology for workers are in terms of empowering them and providing them with more information.

Smart technology can empower workers by providing them with more information. By giving workers access to real-time data, they can make better decisions and be more productive. Additionally, smart technology can help to improve safety in the workplace by providing warnings about potential hazards.

 

 

 

 

 

CHAPTER FIVE

5.1 FINDINGS AND DISCUSSION

5.1.1 Findings

The above analysis highlights the different experiences of six people in manufacturing companies during the COVID pandemic. All six interviewees work in different roles within their companies, from product development to finance and administration. Despite their different roles, all six interviewees discuss how the pandemic impacted their work lives and companies. One common theme from the interviews is communication difficulty during the pandemic. Several interviewees mention how the pandemic has made communication more difficult within their companies and with customers and suppliers. This is because many people work remotely and cannot meet in person. This has made it difficult to coordinate work and get feedback from team members and customers. Another theme from the interviews is the importance of product development during the pandemic. All six interviewees discuss how their companies have had to adapt their product development process to the pandemic. This has included making the process more virtual and focusing on products that are easy to use and maintain. The pandemic has forced companies to be more innovative in their product development process and has resulted in some companies launching new products. Overall, the interviews suggest that the pandemic has positively impacted product development, as it has forced companies to be more innovative and adaptable. One of the most important insights from the interviews is the importance of product development during the pandemic. All six interviewees discuss how their companies have had to adapt their product development process to the new reality of the pandemic.

The analysis highlights the importance of innovation and the challenges associated with developing new products during a pandemic. All interviewees agreed that the pandemic has had a significant impact on how their companies operate and that they have had to adapt their processes to deal with the new challenges. One of the major challenges that companies have faced is the difficulty of getting customer feedback and validation, as they have not been able to access them during the initial few months of the pandemic. However, they eventually got validation from clients around June-July 2020, and the feedback was positive. The interviewee highlights the importance of user feedback and validation, especially when developing new products. Without feedback, it is difficult to assess whether a product is viable or not. The pandemic made it even more challenging to get feedback, but the company was eventually able to overcome this challenge.

Another challenge that companies have faced is the transition to remote work. The interviewees discussed how difficult it was to allocate work and communicate effectively with team members when they were all working from home. Additionally, they mentioned that there were infrastructure issues and many people had to work from home with distractions. The interviewees also discussed the reception of their products by the small and medium enterprises (SME) segment. They mentioned that the SME segment is skeptical of new and sophisticated solutions but that the cost factor is affordable. Despite the challenges that companies have faced, they have been able to overcome them and adapt their processes to the new normal. The most common challenge that companies have faced is the difficulty in communicating and coordinating with team members and vendors. However, companies have overcome this by using different communication tools and being more specific in their requests. The second challenge companies have faced is the decreased ability to do site visits and surveys. However, companies have been able to overcome this by conducting virtual meetings and by getting feedback from clients. The third challenge companies have faced is the lack of work/life balance. However, companies have overcome this by launching new products that help manage and track different processes in the manufacturing industry. The new products have been well-received by customers, both old and new. Overall, the new products are helping companies to improve their efficiency and operations.

5.1.2 Discussion

The interviews’ findings align with the literature review in that they both discuss the challenges that manufacturing companies have faced during the COVID pandemic. The literature review discusses the challenges in terms of communication, product development, and infrastructure. The interviews also discuss these challenges and the challenge of work/life balance. One similarity is that they both discuss the importance of product development during the pandemic. The literature review discusses how the pandemic has forced companies to be more innovative in their product development process, and the interviews echo this sentiment. The interviews also discuss the challenges companies have faced in getting customer feedback and validation. This is in line with the literature review, which discusses the difficulty of getting feedback during the pandemic. However, the interviews also discuss the reception of their products by the small and medium enterprises (SME) segment, which is not mentioned in the literature review. Additionally, the interviews discuss the challenge of work/life balance, which is not mentioned in the literature review. Overall, the findings of the interviews are similar to the literature review, with some additional insights into the challenges faced by manufacturing companies during the COVID pandemic.

The findings from the interviews suggest that the companies have been able to adapt their product development processes to the new reality of the pandemic. The analysis of the literature review and the interviews highlights the importance of innovation and the challenges associated with developing new products during a pandemic. All interviewees agreed that the pandemic has had a significant impact on how their companies operate and that they have had to adapt their processes to deal with the new challenges. One of the major challenges that companies have faced is the difficulty of getting customer feedback and validation, as they have not been able to access them during the initial few months of the pandemic. However, they eventually got validation from clients around June-July 2020, and the feedback was positive. The interviewee highlights the importance of user feedback and validation, especially when developing new products. Without feedback, it is difficult to assess whether a product is viable or not. The pandemic made it even more challenging to get feedback, but the company was eventually able to overcome this challenge.

Another challenge that companies have faced is the transition to remote work. The interviewees discussed how difficult it was to allocate work and communicate effectively with team members when they were all working from home. Additionally, they mentioned that there were infrastructure issues and many people had to work from home with distractions. The interviewees also discussed the reception of their products by the small and medium enterprises (SME) segment. They mentioned that the SME segment is skeptical of new and sophisticated solutions but that the cost factor is affordable. Despite the challenges that companies have faced, they have been able to overcome them and adapt their processes to the new normal. The most common challenge that companies have faced is the difficulty in communicating and coordinating with team members and vendors. However, companies have overcome this by using different communication tools and being more specific in their requests. The second challenge companies have faced is the decreased ability to do site visits and surveys. However, companies have been able to overcome this by conducting virtual meetings and by getting feedback from clients. The third challenge companies have faced is the lack of work/life balance. However, companies have overcome this by launching new products that help manage and track different processes in the manufacturing industry. The new products have been well-received by customers, both old and new. Overall, the new products are helping companies to improve their efficiency and operations. The findings from the interviews are similar to the findings from the literature review in that they both highlight the importance of innovation and the challenges associated with developing new products during a pandemic. However, the interviews provide more insights into how companies have overcome the challenges and adapt their processes to the new reality of the pandemic.

The findings from the interviews suggest that the pandemic has positively impacted product development, as it has forced companies to be more innovative and adaptable. This is in line with the literature review, which discusses how the pandemic has forced companies to be more innovative in their product development process and has resulted in some companies launching new products. One of the most important insights from the interviews is the importance of product development during the pandemic. All six interviewees discuss how their companies have had to adapt their product development process to the new reality of the pandemic. One of the major differences between the findings and the literature is the difficulty of getting customer feedback and validation. The literature review discusses how the pandemic has made it more difficult to get feedback from customers, but the interviewees did not mention this as a major challenge.

Additionally, the interviewees discussed how the pandemic has made it more difficult to communicate and coordinate with team members and vendors. However, the literature review does not mention this as a major challenge. The third challenge the interviewees discussed is the lack of work/life balance. However, the literature review does not mention this as a major challenge. Overall, the findings from the interviews suggest that the pandemic has positively impacted product development, as it has forced companies to be more innovative and adaptable. However, the pandemic has also made it more difficult to communicate and coordinate with team members and vendors. Additionally, the pandemic has made it more difficult to get customer feedback and validation.

 

 

 

CHAPTER 6

6.1 CONCLUSION

The fourth industrial revolution, or Industry 4.0, profoundly impacts manufacturing and supply chains. The use of data analytics and the Internet of Things has allowed manufacturers to collect massive amounts of data from various sources. Advanced analytics can then be used to make predictions and recommendations. Industry 4.0 technologies play a significant role in transforming the supply chain, making it more efficient, agile, and responsive to customer needs as it has become increasingly complex and globalized, making it more critical than ever for businesses to have efficient and effective supply chain management systems in place. One of the major benefits of Industry 4.0 technologies is that they can help to optimize supply chains by reducing waste and improving visibility into the entire system (Fatorachian & Kazemi, 2021). Industry 4.0 technologies can also help companies better forecast demand and reduce inventory levels, which can lead to significant cost savings. Another benefit of Industry 4.0 technologies is that they can help to improve the quality of products and services. Finally, Industry 4.0 technologies can also help improve employees’ working conditions.

6.2 Limitation of the Study

There are several limitations that the study on Industry 4.0 faced. First, there is no clear definition of Industry 4.0, making it difficult to identify and compare different Industry 4.0 initiatives. This lack of clarity can result in confusion and misunderstanding about what Industry 4.0 is and what it entails making it difficult to assess the effectiveness of different Industry 4.0 initiatives and to compare their relative merits. Second, Industry 4.0 data can be difficult to obtain and may be proprietary. This can make it difficult to replicate or verify results. There are a few reasons for this. First, Industry 4.0 is a relatively new concept, so there may not be a lot of data available yet. Second, the existing data may be owned by individual companies or trade associations, making it difficult to access. Finally, even if data is available, it may be in a proprietary format that is difficult to use. Finally, the field of Industry 4.0 is constantly evolving, making it difficult to keep up with the latest developments. This is because technology is constantly changing and improving, which makes it difficult for people to keep up with the latest trends. In addition, the field is constantly changing regarding the applications and industries in which it is being used.

6.3 Limitations of the Scope, Quality, and Validity of the Analysis Undertaken.

The scope, quality, and validity of the analysis undertaken in the dissertation on Industry 4.0 may hinder its usefulness to policy-makers and practitioners. The study is limited to a review of the existing literature on Industry 4.0, which may not represent the full range of opinions and perspectives on the subject. In addition, the quality of the data and analyses presented in the dissertation may be limited by the sources used and the methods employed. Finally, the validity of the conclusions drawn from the analysis is limited by the scope and quality of the data and analyses. These limitations should be considered when evaluating the findings of the dissertation. The dissertation on Industry 4.0 is based on a review of the existing literature on the subject. The literature review is limited to a review of the existing literature on Industry 4.0, which may not represent the full range of opinions and perspectives on the subject. In addition, the quality of the data and analyses presented in the dissertation may be limited by the sources used and the methods employed. Finally, the validity of the conclusions drawn from the analysis is limited by the scope and quality of the data and analyses. The data and analyses presented in the dissertation may be limited by the sources and methods employed. The quality of the data and analyses presented in the dissertation may be limited by the sources used and the methods employed. In addition, the validity of the conclusions drawn from the analysis is limited by the scope and quality of the data and analyses. The conclusions drawn from the analysis are limited by the scope and quality of the data and analyses. The validity of the conclusions drawn from the analysis is limited by the scope and quality of the data and analyses.

6.4 Recommendations.

First, there is a need for further research to determine the feasibility and benefits of Industry 4.0 for small and medium enterprises (SMEs). The potential for Industry 4.0 to offer significant benefits to SMEs is widely recognized. However, there is still a lack of detailed knowledge about how Industry 4.0 can be effectively implemented by SMEs. Further research is needed to assess the potential benefits of Industry 4.0 for SMEs. Second, more research is needed on the potential legal and ethical issues associated with Industry 4.0. The potential legal and ethical implications of Industry 4.0 are not yet fully understood. As Industry 4.0 technologies become more widely adopted, there is a need for further research to identify and assess the potential legal and ethical issues associated with their use. Third, research is needed to identify the most effective implementation strategies for Industry 4.0. There is currently a lack of detailed knowledge about effectively implementing Industry 4.0 technologies. This lack of knowledge poses a significant challenge for businesses adopting Industry 4.0. Further research is needed to identify the most effective implementation strategies for Industry 4.0. Fourth, further research is needed to assess the impact of Industry 4.0 on employment and skills. Industry 4.0 on employment and skills is not yet fully understood. As Industry 4.0 technologies become more widely adopted, there is a need for further research to assess their impact on employment and skills. Fifth, research is needed to evaluate the potential environmental impact of Industry 4.0. The potential environmental impact of Industry 4.0 is not yet fully understood. As Industry 4.0 technologies become more widely adopted, there is a need for further research to assess their potential environmental impact. Sixth, research is needed to better understand the evolving role of data and analytics in Industry 4.0. Data and analytics are playing an increasingly important role in Industry 4.0. However, there is still a lack of detailed knowledge about the evolving role of data and analytics in Industry 4.0. Additionally, further research is needed to better understand the evolving role of data and analytics in Industry 4.0. Finally, research is needed to monitor and evaluate the ongoing development of Industry 4.0. The ongoing development of Industry 4.0 is complex and rapidly evolving. As such, there is a need for ongoing research to monitor and evaluate the ongoing development of Industry 4.0.

 

 

 

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