THE CHARACTERISTICS OF SMART
MANUFACTURING AND THEIR EFFECT ON
WORK DESIGN
By
MAIK MATI
University of Groningen Faculty of Economics and Business (Pre-) Master Supply Chain Management
Grovestins 22 7608 HM Almelo
+316 19246606
M.Mati@student.rug.nl
Abstract
Industry 4.0 opens up diverging discussions about the consequences for employees. This research paper investigated four Smart Manufacturing technologies, PLMS, MES, M2M, and the digital interface. A multiple case study explained how the key characteristics of these technologies affect the work design of planners and operators. The technologies showed patterns of generating more data. The availability of more data had a certain impact on all or some work characteristics of planners and operators. Overall, the systems created job
enrichment but proved more simplification for operators and more support for planners.
Introduction
The fourth industrial revolution is on its way, also referred to as Industry 4.0 (Frank,
Dalenogare & Ayala, 2019). Industry 4.0 includes several emerging technologies that provide digital solutions, like productivity and efficiency improvement, reduced costs, and a better focus on the customers, with Smart Manufacturing as a central element (Frank et al., 2019). Kusiak (2017) states that Smart Manufacturing uses technology to support production. However, this new industrial revolution also opened up diverging discussions about the consequences for the employment of humans, reflecting on both risks and opportunities for the nature of work (Rauch, Linder & Dallasega, 2020). For example, Frey and Osborne (2017) argue that routine tasks, including some complex activities, can increasingly be automated. They conclude that approximately 47% of the American labor market faces a potential threat over the next one or two decades. Hecklau, Galeitzke & Kohl (2016) claim that employees need to take on more strategic, creative, and coordinating tasks for their existing and future jobs to face the challenges that Industry 4.0 brings. That is why Rauch et al. (2020) believe that future employees will have a different work design that is characterized by operating in a human-automation collaboration to enhance workforce capabilities (Fantini, Pinzone & Taisch, 2020). This research paper aims to empirically explore these contradictions on how Smart Manufacturing impacts work design.
market are only 9%. This is a difference with the 47% of Frey and Osborne. On the contrary, other studies believe that there are positive effects of Industry 4.0 on employment as a result of new job opportunities (Hirch-Kreinsen, 2016).
To this day, Smart Manufacturing remains new and complex as a concept. This research intended to acquire more knowledge about the impact Smart Manufacturing has on work design by investigating the impact of specific Smart Manufacturing technologies, on work designs of planners and operators. This was done using work characteristics classified by Morgeson & Humphrey (2006).
In particular, this study focused on four Smart Manufacturing technologies. First, Product Lifecycle Management Systems (PLMS). PLMS collects data of products through their entire lifecycle (Schuh, Rozenfeld, Assmus & Zancul, 2008). Second, Manufacturing Execution Systems (MES). MES delivers, accurate real-time, information about a process, from raw material to finished product (Mansour, Millet & Botta-Genoulaz, 2018). Third, Machine to Machine communications (M2M). M2M is a wireless communication system, which requires no intervention and supervision of humans (Mingyu, Ying & Xudong, 2019). And at last, the digital interface. A digital interface offers support through a projection-based environment (Posada, Zorrilla, Dominguez, Simoes, Eisert, Stricker, Rambach, Dollner & Guevara, 2018). All these technologies have an impact on the work designs of people, which will be explained later on. But not all work characteristics is used in this research. Morgeson & Humphrey (2006) use work characteristics as measurable dimensions of work. They divided their classified characteristics into three categories, motivational, social, and contextual. But since not all technologies have a direct impact on contextual work characteristics, regarding physical and environmental contexts, only the motivational and social work characteristics were used.
This research aimed to explore the key characteristics of the investigated smart manufacturing technologies and how these characteristics affect the work design of planners and operators. The following research question (RQ) was formulated:
What are the key characteristics of the investigated Smart Manufacturing technologies and how do these affect the work design of planners and operators?
1. What are the key characteristics of the PLMS, MES, and M2M, and how does it affect the work design of planners?
2. What are the key characteristics of the digital interface, MES, and M2M, and how does it affect the work design of operators?
The RQ was answered by conducting a multiple case study, where interviews were held with several employees from different companies. These interviews were analyzed and used as information for the RQ.
Theoretical framework
Industry 4.0
As mentioned, Industry 4.0 is a paradigm. The aim of Industry 4.0 is to increase productivity and efficiency in industries by developing new advanced technologies (Kagermann, Wahlster & Helbig, 2013) that add value to the whole product lifecycle (Wang, Wan, Li & Zhang, 2016). The definition of technology, used in this research, is considered as an implement or tool used to transform or manipulate elements in any production process (Rooney, 1997). Smart Manufacturing
Smart manufacturing is seen as the central element of Industry 4.0, and therefore will be elaborated on in this research (Kagermann et al., 2013). Smart Manufacturing can have various definitions. Thoben, Wiesner & Wuest (2017) state in their paper that Smart Manufacturing is:
''a data-intensive application of information technology at the shop floor level and above to enable intelligent, efficient, and responsive operations.''
Kusiak (2018) states that Smart Manufacturing is a fully integrated, collaborative system that responds in real-time, to meet changing demands and conditions. As both give a different definition, they mention the use of information and communication technology in
manufacturing operations and collect advanced data to improve these operations at all levels of the supply chain enterprise. Smart Manufacturing technologies can be divided into three stages, according to their complexity (Frank et al., 2019), with stage three being to the most complex. Technologies in this research all belong in a certain stage, for example, MES is a stage one and M2M is a stage 2 technology (Frank et al., 2019).
PLMS
Manufacturers implement PLMS when they want to change their focus on products. The scope of products then extends from only design and production to maintenance, repair, disposal, and recycling (Lee, Choi, Kim & Noh, 2011). PLMS manage product-related
depends on the worker's tasks. It enhances cross-functional collaboration among employees (Cantamessa et al., 2012). Also, the enriched information management enables to improve the coordination and control of product engineering and new product design (Cantamessa et al., 2012).
PLMS bring changes to a company, this also implies for workers. PLMS substitute all
systems in a company into one and therefore strives for more effective collaboration between people (Cantamessa et al., 2012). Also, the systems require organizations to acquire skills on PLM and the system itself (Lee et al., 2011).
Tasks can become more efficient due to coordination and communication improvements (Lee et al., 2011). This can make jobs less complex, but PLMS can also make jobs more complex. Even though workers can have more opportunities to take advantage of past knowledge through better availability of information, this needs to be done voluntarily (Cantamessa et al., 2012). Workers need to put effort by doing and communicating more which can be a problem for organizations that had a strong functional orientation (Cantamessa et al., 2012).
MES
MES does not actually execute production, but collects, analyses, integrates, and presents data that is generated during production (Naedele, Chen, Kazman, Cai, Xiao & Silva, 2015). MES operates as a decision support system for operators, but also provide employees better insights into processes (Naedele et al., 2015). According to Naedele et al. (2015), the system stores and analyses historical data controls processes during production and prognoses and plan future process runs. The system also makes it possible to warn workers early regarding process or quality deviations (Mansour et al., 2018). The system requires integration with other information systems because MES bridges ERP systems and other systems that operate in the work field (Sellitto & Vargas, 2020).
MES brings change to people because the system guides people through the process which can lessen their autonomy, but it supports them by minimizing their tasks of searching for information due to the availability the system brings (Saenz de Ugarte, Artiba & Pellerin, 2009). The availability also provides quick feedback when mistakes are made during production (Naedele et al., 2015).
M2M
between these smart devices without human intervention (Mingyu et al., 2019). So the more machines are interconnected, the more autonomous and intelligent applications can be generated (Chen, Wan & Li, 2012).
Workers do not use the system but that does not mean that they are not affected by it. The system will change some processes by offering a greater amount of data to people (Chen et al., 2012). Also, because it autonomously interacts with machine devices the system automatically replaces tasks that give manufacturers the ability to improve efficiency and production (Verma, Verma, Prakash, Agrawal, Naik, Tripathi, Alsabaan, Khalifa, Abdelkader, Abogharaf, 2016).
Digital interface
An interface is an interaction between two independent systems (Bessa, 2012). This research concerns a digital interface that involves human interaction together with the use of virtual and augmented reality.
- Virtual reality (VR) is a technology that puts a human in an artificial environment. The user of a VR accepts the environment as real and can navigate and interact with the artificial environment (Farrel, 2018).
- Augmented reality (AR) layers digital content over the real environment through a virtual object like texts, images, or videos (Farrel, 2018).
A digital interface offers support and is often designed and used by operators (Posada et al., 2018). The system improves the experience of operators by providing projection-based instructions and interactions (Posada et al., 2018). A digital interface is used to support and train operators with tasks, measure data that supports the understanding and decision-making of operators, and predict situations by learning from operators (Posada et al., 2018).
Work design
The definition of work design by Grant & Parker (2009) goes as follows:
‘’Work design describes how jobs, tasks, and roles are structured, enacted, and modified, as well as the impact of these structures, enactments, and modifications on individual, group, and organizational outcomes’’
This research paper will focus on the work characteristics that were classified by Morgeson & Humphrey (2006). Work characteristics are measurable dimensions of work and they
conceptually reflect different design features (Morgeson & Humphrey, 2006). As mentioned, only the motivational and social work characteristics are used. The work characteristics focused on in this research are autonomy, skill variety, task variety, interaction with others, dependency, feedback from the jobs, feedback from others, job demands, problem-solving, and task significance. These were used to figure out which work characteristics were infected by the technologies and which did not. The previous sections about the technologies stated the changes they brought. Each change could be linked to work characteristics but is not done by the previous authors.
The importance of work design is sometimes underestimated by management, causing many employees to experience deskilled and demotivating work (Parker, Van den Broeck & Holman, 2017). This also applies to the implementation of Industry 4.0 technologies, especially when Industry 4.0 causes a growing uncertainty about the role of humans in the future (Zolotová, Papcun, Kajáti, Miškuf & Mocnej, 2020). Muller, Kiel, and Voigt (2018) prove this by explaining that employees need to be trained and willing to work with Industry 4.0 technologies and to learn new competencies to be qualified to approach these
technologies.
Theoretical framework
Figure 1
Theoretical framework
Methodology
Research design
A case study was conducted to collect data for this research paper. According to Yin (1981), a case study is an empirical research that investigates a certain subject in-depth, often when there is little research done about the subject. A benefit is that a case study can either perform qualitative or quantitative data (Yin, 1981). They provide information and theories, involving one or more cases (Yin, 1981).
A multiple case study is performed. A multiple case study prefers to adhere more cases to establish a stronger theory building and explanation (Rowley, 2002), and as of now there is little information about the underlying relations between Smart Manufacturing and work design. The research paper used multiple cases to build a stronger base on the theory. Research setting
For this research paper, three cases were selected that operate in different sectors (Table 1). There were some requirements that organizations had to meet to be able to use the interviews for the research questions. First, the selected organizations use, two or more, Smart
Manufacturing technologies. Second, the technologies are already implemented or are
Table 1
Case description
Organization A B C
Sector Defense Food Frames
Products Integrated systems caps, closures, and lids Frames
Employees 2000 75 135
Technologies PLMS & Digital interface MES & M2M MES & M2M Function
case
technologies
PLMS: Collect as much data as possible so that a product can be traced back during its lifecycle. Digital interface:
Takeover administrative tasks. Also, explain and show production steps.
MES: Gain more insight into the production process. Also, the system guides operators in the process. M2M: A buffer stacks crates. When these crates are full an automated guided vehicle automatically gets a signal to pick the crates up.
MES: Monitor the production process and manage it from the office. M2M: Buffers in production automatically call products up from machines.
Interviewee Digital industry engineer (DIE)
Production planner Operator Reason
suitable for research
The organization
implemented PLMS and is currently designing the digital interface at which they already started to work with VR. Therefore they can give information on how the
implementation affected the work design of their employees.
The organization has implemented MES and M2M. Therefore they can give information on how the implementation affected the work design of their
employees.
The organization has implemented MES and M2M. Therefore they can give
information on how the implementation affected the work design of their employees.
Data collection
Data is collected by conducting semi-structured interviews. There was one common script used as interview script. Semi-structured interviews are conducted to at least get answers on all the interview questions and to have an opportunity to acquire extra information by asking follow-up questions. The interviews were all transcribed word for word. In table 2 an
overview of the interviews and interviewees is provided.
Data analysis
This research paper has analyzed data by coding the conducted interviews. To begin, a coding scheme was made that followed the variables and concepts of the RQ (table 2). Thereafter was an iterative process of reading the interviews. Per interview, text fragments, that were interesting for the RQ, were put in Excel and labeled to one or multiple codes. Data is then analyzed by comparing and looking at the similarities and differences of codes and comparing the cases and looking for patterns, all in the light of the RQ.
Table 2
Overview of coding tree
Concepts and variables
First-order codes Descriptive codes
Technology A Smart Manufacturin g A1 PLMS A2 Digital interface A3 MES A4 M2M
Work B Work design B1 Skill variety B2 Autonomy B3 Task variety
B4 Interaction with others B5 Dependency
B6 Feedback from the job B7 Feedback from others B8 Job demands
B9 Problem-solving B10 Task significance C Employees C1 Planner
Findings
Characteristics PLMS and its effect on the work design of planners (case A)
Technology characteristics
Organization A uses the PLMS with the main focus to gather data about their products. The data covers the whole lifecycle of a product so that the system can trace back what exactly has been put into a product. PLMS does not only support the production but also the service of organization A because of its traceability.
PLMS replaced all different systems and placed them into one system. The availability of data became greater because all data was not divided anymore into different systems.
‘’We kept track of what goes on in our systems in all kinds of places, but that did not actually come together into one system, so you could do very poor analyses.’’ – DIE (case A)
Mistakes in production are fixed faster because of the traceability, it is easier to spot where mistakes in production were made.
‘’What we often encountered was that sometimes something was wrong during production. Products had to be sent back, where it had to be sorted out again. This would cause a delay for one or two weeks, and now that we have the right data it is going better.’’ - DIE
The fast emergence of information makes it possible to retrieve new information about events that were unknown at first. A manufacturer can take measures about these events or even improve their processes. But because of this, organization A wants to obtain more data as a result. This means that certain functions in the company need to perform their work in more detail.
Effect on work design
The PLMS enforced a certain process in the organization and required planners to work in a certain way causing planners to lose some of their autonomy. This does not mean that
planners do not have autonomy. Planners still need to make decisions and control the data that is entered into the system.
''The planner still decides which regulations will be chosen, what needs to be included in the bill of material, and which production steps are involved.'' - DIE
more analysis, and to link certain information with each other. Especially because planners receive more feedback at short notice since the PLMS stores a lot of data. The system immediately indicates when something goes wrong.
As was mentioned, planners need to perform their work with more details, this increased their task variety. But this automatically reduced communicating to others because colleagues can gather information from within the system. So, the significance of the planners has increased because it became more detailed, they contribute more because of the system.
The whole company works towards one goal in one system. This increased coordination because planners need to interact more with others to achieve the goal. Planners cannot perform certain actions, due to the enforced process, until someone else has finished his actions. This made planners also more dependent on the people upstream in the process. ‘’What we sometimes run into is that someone still has an action open in the system and gets sick, which means that the action cannot be officially released.’’ - DIE
Altogether the job demands of planners did not change, it was only expected of them to have some digital knowledge. They still need to possess their current skills to perform.
But, the whole company, including planners, needed to gain some problem-solving skills, mainly during the early stage of the implementation of PLMS. This was because the system needed to be adapted to the business process of organization A.
Case analysis
Figure 2 shows an overview of the changes in organization A. Overall, there is job
enlargement and enrichment for planners in this case. Planners received more tasks, but these tasks did not increase the responsibility of the planners or required them to have a higher skill level. But the system requires the company to work together towards one goal which
Figure 3
Overview change work design planners
Characteristics MES and M2M and its effect on the work design of planners (case B)
Technology characteristics
MES changed the planning system for organization B. The system makes more data available and simplifies the process by linking an order or planning to machines. MES organizes these orders to run the production optimally. MES also serves as an auxiliary system for planners, the system has data about orders and can inform them about the progress of the planning. Like when an order cannot deliver on the requested delivery time.
''You have a good auxiliary system. In the past, you used to calculate it yourself and now the system does it for you.'' – Planner (Case B)
MES offers real-time data, planners receive more information about what is happening in production and much more data is secured, however data needs, voluntarily, to be searched. But the important thing is that data can be traced back which created more control and prevents mistakes.
‘’MES does not immediately give advice, we have to extract that from the data ourselves.’’- Planner
Effect on work design
MES did not have a direct impact on the autonomy of planners, it only offered more data. Planners still determine in which order they perform their work and make decisions based on what they think is efficient.
‘’When an order is entered, the system only considers whether it is achievable. Eventually, I make the decisions.’’ - Planner
This does not mean that MES does not influence the decisions of planners. Even though the system does not advise on the best option, it offers possibilities for them. This can cause planners to make a different decision.
A planner receives and loses tasks due to the system. MES takes over tasks that take care of the retrieval of data. It also makes calculations, this means that planners do not have to make them anymore and or are required to possess that skill. But this means that planners need to control more to secure the process.
Interaction with others became less due to the fact MES delivers real-time data. Colleagues have more insight, reducing the need to communicate. But because of the increase in data availability, feedback from the system and others will become more.
‘’MES suggest follow-up actions in case of malfunctions. There is no need to discuss who is going to do what anymore.’’ - Planner
Planners became more dependent on the sales department. Planners cannot perform activities if the sales department fills the wrong data in MES. Planners cannot change the data in MES and are therefore also dependent on departments that can, like ICT.
Some things remain unchanged. Planners still need to prepare orders for production, the way of preparing work has only changed. They also still need to be creative when solving
problems. But the aspect increases after the implementation of MES because the system is not adapted to the processes.
Case analysis
Figure 3
Overview change work design planners
Similarities and differences work design changes of planners (Cases A & B)
Interpreting the similarities and differences of the key characteristics of PLMS, MES, and M2M showed that the main similarity between characteristics of the two systems is that they make more data available.
The main similarities between the effect on the work design of planners were that there is job enrichment. The job demands of planners did not change. Planners still need to perform their main activities, only the way of working changed, but they became more dependent on the people upstream in their process.
When it comes to skill variety, both planners developed some technical skills to work with the systems. But planners using PLMS also needed to develop analytical skills while planners using MES require fewer skills with the system.
More feedback is received because of increasing data availability. Also, problem-solving increases in the early stage of the implementation of the systems, since the systems need to be adapted to the processes.
PLMS intends to work more together, which increases the interaction planners have with others. But the interaction planners have with others, using MES, became less because of the data availability.
Figure 4
Similarities and differences
Characteristics of the digital interface and its effect on the work design of operators (case A)
Technology characteristics
The digital interface is considered as a personal assistant for operators in organization A. Because of its ability to collect data during production, support the operator by explaining production steps and taking over non-value-added tasks by using interactive computer programs. This improved lead times, delivery times, and product quality.
It was also used as a replacement of paper in the workplace, such as work instructions and administrative information with the use of AR.
A digital interface is a tool that explains the production process clearly to the operator to avoid error sensitivity and produce more efficient by making fewer mistakes. It makes it also possible for operators to rotate work if the explanation is clear enough.
Effect on work design
The autonomy of operators became less because the digital interface forces a certain process by having a sequence of production steps that operators must follow. The system also keeps track of what operators are doing. Due to this, the system increases the feedback operators receive from the job by indicating operators when something goes wrong
‘’The system is going to take over more tasks of the operator and enforce him to complete the previous product because he cannot go to the next one if the previous one is not registered in the system.’’ – DIE (Case A)
The skill variety of operators increased due to the fact that operators need to work with an interface using VR and AR. This was new for many operators, so it was important for them to develop the digital skills to use VR and AR.
As was mentioned operators are released of their non-value-added tasks which reduced some of the tasks of operators. This allowed operators to perform more varied and smarter tasks, like rotating work with other operators or just to focus more on production. The task
significance of operators increased because the system improves the efficiency of operators by replacing the non-value-added tasks.
‘’Administration is only important for us, and it is also necessary, but it is not something our customer requires from us, so the interface gives operators more time to focus on our
customers.’’ – DIE
The interaction with others became less because operators do not have to interact with the production manager or planners because they receive information through the system. They also become less dependent on others due to the system's ability to plan production smartly. The digital interface plans production in a certain way where operators do not have to wait on each other.
The job demands of operators do not change using the system. Operators still need to be capable to produce products. The system only operates as a support system for the operators. Also, the number of feedback operators receive from others and the problem-solving
Case analysis
Figure 5 shows an overview of the changes in organization A. Overall, there is job enrichment for operators in this case. Non-value-added tasks are substituted and allowed operators to perform more varied and smarter tasks. These tasks became simplified due to the support of the system.
Figure 5
Overview change work design operators
Characteristics of MES and M2M and its effect on the work design of operators (case C)
Characteristics
MES determines which orders will be produced for organization C. Operators receive more information about the production schedule process, whereby the system also indicates whether some orders are feasible to produce. Operators work with more structure by following the system.
Operators used to work differently before the system was implemented. Nowadays production is often automated because of it. Machines automatically check and call up products or
components from other machines or buffers with M2M to increase flow. With MES, machines automatically manage to produce according to the planning.
Effect on work design
The autonomy of operators decreases. As mentioned, the system forces operators to work in a certain structure, this decreases their autonomy. Operators lose the freedom of making their planning. Now they have to produce based on what is on the production line. They also have to interact less with others because the system generates data automatically. The system also generates feedback that management or colleagues can use to provide feedback to operators. ‘’Deviating from the production order is simply not possible.’’ – Operator
Operators lose skills because machines took tasks over that required specialism. However, operators need to gain skills when it comes to working with and maintaining the machines. ‘’I think everyone could do the work now.’’ – Operator
Due to this, operators can rotate activities. Activities became simpler and doing the same job over and over becomes demotivating. Operators need to perform more control since the system does not directly detect mistakes.
''I would not be happy if I only do work that does not motivate me.'' – Operator
Operators are more dependent on the system because they cannot perform work during disruptions. Operators also became more dependent on each other. If one operator makes a mistake and does not check it, the operator at the next production step cannot go further. The job of operators became less demanding because they have to do less than they had to do before due to the abilities of the systems. This decreased the significance of their task since they do not deliver such a contribution as they used to do, due to automation.
Problem-solving capabilities of operators are expected to rise because operators need to adapt to the system. This means that operators need to follow a certain structure. Operators can make the structure more pleasant by making creative solutions.
''We noticed that we often grabbed the wrong bin when changing series. One of the boys suggested giving articles and bins a color code. We then see a color on the screen, for
example, blue. Then we know that we have to take parts of the blue boxes. This prevents you from making mistakes.'' – Operator
Case analysis
Figure 6 shows an overview of the changes in organization C. Overall, there is job
the need of operators to control more. This caused that operators can rotate tasks, otherwise they had to do the same task over and over again which can be demotivating.
Figure 6
Overview change work design operators
Similarities and differences work design changes of operators (Cases A & C) Technologies used for the work design of operators were the digital interface, MES, and M2M. Interpreting the similarities and differences of these technologies and their effect on the work design showed that the main similarity between the two systems is that they create data and provide simplification.
The main similarities between the effect on work design were that the autonomy of operators became less since both systems enforce some form of structure from operators. And because both systems also generate data, operators need to interact less with others. But with the generated data operators receive more feedback.
Although both operators increased their skills to work with the systems, the operators using MES lost skills because the system took over activities.
Also, both systems made it possible for operators to rotate. The digital interface made it possible by having clear work instruction and MES by making work simpler.
The job of operators using MES is less demanding because the system took over value-added activities, while operators using the digital interface still need to perform the same job only with more support and less non-value added tasks.
Because operators, using MES, needed to adapt to the structure of the system, the problem-solving capabilities of operators were expected to rise to make the structure more pleasant. Also, the task significance of operators using MES decreased because of the lesser
contribution they bring. On the other hand, the digital interface increased the task significance of operators by improving their efficiency.
Figure 7
Discussion/conclusion
The theoretical framework explained that the characteristics of the technologies will affect the work design of employees. To support the framework a RQ was formulated, that was divided into two sub-questions that showed what the key characteristics are of the investigated technologies and how these affected the work design of planners and operators.
Conclusion
So, what are the key characteristics of the investigated Smart Manufacturing technologies and how do these affect the work design of the employees?
The key characteristics of the technologies are that they all generate more data for
manufacturers. The availability of more data will have a certain impact on all or some work characteristics of planners and operators, or in general, employees.
The findings showed that each system affected work design differently and that each function was affected differently. Although every system provided job enrichment, each system provided it in various ways. But, the systems simplified work more for the operators than the planners, but on the contrary, the systems provide planners more support than the operators. These findings complement the theory of Hecklau et al. (2016) that claimed that employees need to be able to take on more strategic, creative and coordinating tasks together with the theory of Muller et al. (2018) that proved that employees need to be trained and willing to work with Industry 4.0 technologies and to learn new competencies to be qualified to
approach these technologies. The findings showed that every work design needed to develop skills regarding using the systems, but also on taking more tasks. For example, operators using MES need to control more due to the system's incapability to do itself. Or planners using PLMS need to perform more detailed work to be able to keep an efficient track on a product for its whole lifecycle.
Also, the changes in the work design of planners and operators showed that they complement the theory of Hirschi (2018). Because the systems all substituted some tasks but did not eliminate entire functions. This contradicts the theory of Frey and Osborne who claim entire jobs can be automated.
Implications for theory
negative or positive. Companies can take countermeasures to lessen the negative impact. Lessen the negative impacts can be a topic for future research.
Implications for practice
Organizations can use this research paper to further understand the impact Smart
Manufacturing technologies have on employees. This can encourage them to implement, change, or improve technologies in a way to make optimum use of the collaboration between employees and technologies.
Critical reflection
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