Flow of information for autonomous operators in Industry 4.0 factories Marta Lall ([email protected]) Eva Amdahl Seim Hans Torvatn Gaute Knutstad SINTEF Technology and Society, Industrial Management P.O Box Sluppen, N-7465 Trondheim, Norway

Abstract ICT technology and "internet of everything" are the driving forces behind Industry 4.0. However, technology is easy to imitate. Thus, it is the manufacturers' ability to utilize emerging technologies, by applying a joint technical and social perspective that will create sustained competitiveness. In this study, we view Industry 4.0 from a socio-technical perspective and argue that an update of factory information systems should be done, with the operator in mind as the primary receiver and user of information. Our arguments are supported by findings form case studies at three Norwegian manufacturing companies. Keywords: Manufacturing, autonomy, decision support Introduction Currently, manufacturers are embracing advanced technology at such a pace that the change is said to be an industrial revolution, and described by terms such as "Industrial internet" (Evans and Annunziata, 2012), "Smart industry" (Programmabureau Smart Industry, 2014) and "Industry 4.0" (MacDougall, 2014, Blanchet et al., 2014). In this paper, we will use Industry 4.0, a term that is mainly used about manufacturing (Hermann et al., 2016). A characteristic of the future factory is that a multitude of sensors will register vast amounts of information that for instance can be used to improve processes, or to automate documentation. Information flow is hence a central element of change towards Industry 4.0. Norway is a high-cost country (Bureau of Labor Statistics, 2012) and the IMF Report (International Monetary Fund, 2013) draws a picture of Norway becoming more dependent on oil and gas with high salaries, few working hours and low overall productivity. In spite of this trend, Norwegian manufacturing companies have been able to compete globally within demanding markets such as the maritime, automotive and aerospace industries. In addition to having a high cost of labour, Norway has a high competence level and high levels of technology usage (Knutstad and Ravn, 2014). This enables competitiveness, stemming from the ability to develop high-value-adding products and efficient automated processes by a highly competent work force.

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From our case studies at Norwegian manufacturing companies, we observe a high focus on modernizing production processes, while improving information flows is given little attention. As the efficiency of these supportive flows of information lag behind ever faster and more complex production processes, their insufficiency negatively affects the case companies' production efficiency as costs incur from lack of information or documentation errors. Time is wasted looking for and correcting errors on papers, and relatively important information is spread at random by conversation. Furthermore, as pointed out by socio-technical systems thinking, changes in technology necessitate changes in work organisation, and vice versa (Knutstad et al., 2009). ICT technology and "internet of everything" are the driving forces behind Industry 4.0 (Kagermann et al., 2013). In order to achieve sustained competitiveness, it is essential to consider how the technical system, including the information system, relates to and affects the social system. The manufacturers' ability to utilize the emerging technologies by applying a joint technical and social perspective will create the competitive edge (Netland et al., 2011, Knutstad and Ravn, 2014). As manufacturing becomes ever more high-tech, the work content and required skills for operators will change dramatically (European Commission, 2013). The change towards industry 4.0 implies an increase in responsibility and authority of production for the operator, with a high degree of decision autonomy (Kagermann et al., 2013). Operators are the manufacturing managers of the future, and will only delegate tasks to a higher level in case of exceptions (Hermann et al., 2016). Thus, contemporary efforts to modernize information flow should be made with the operator being considered the primary user of the information (International Society of Automation, 2015). The autonomous operator will require assistance systems to aggregate and visualize information comprehensibly, in order to make informed decisions and solve urgent problems effectively (Hermann et al., 2016). In this study, we argue that an update of factory information systems should be done, with the operator in mind as the primary receiver and user of information. This view is also supported by the principles of socio-technical systems thinking, which clearly is an appropriate perspective to take in solving the challenge at hand. Our arguments are based on recent developments within Industry 4.0 literature and socio-technical systems thinking, and observations from case studies at three Norwegian manufacturing companies. Industry 4.0 and the socio-technical systems perspective There has been a shift in the development of new technology, with the "Internet of Things" being a key driver (European Commission, 2013). Within industry, these changes have been said to be the fourth industrial revolution, hence the term "Industry 4.0" (MacDougall, 2014, Blanchet et al., 2014, Kagermann et al., 2013). Advanced manufacturing industries all face a paradigm shift on how to operate and become more sustainable and competitive (MacDougall, 2014). Manufacturing will in the near future be embedded within Cyber-Physical Systems: Global networks that include smart products, smart and autonomous machinery, warehousing systems and production facilities, capable of communicating with and controlling each other (Kagermann et al., 2013). This facilitates fundamental improvements to the industrial processes involved in manufacturing, engineering, material usage, supply chain and life cycle management. The changes in manufacturing will of course have a large impact on the work of humans. The human role is changing from simpler manual task to more complex decision-making, as automation eliminates repetitive, low skill work (Oborski, 2003, Programmabureau Smart Industry, 2014). The new tasks of the operator will be to reorganize, reconfigure, and maintain 2

the system (Programmabureau Smart Industry, 2014) and they will retain a key role in quality assurance (Kagermann et al., 2013). The importance of the operators is also increasing, as they become responsible for the production as a whole, and not just a single machine (Oborski, 2003, Hermann et al., 2016). Increased autonomy emphasizes the importance of operators ability to act on own initiative and organize own work (Kagermann et al., 2013). Clearly, the change towards industry 4.0 is not just a technical one, but will also require new organisation. In order to achieve sustained competitiveness, it is essential to consider how the technical system, including the information system, relates to and affects the social system. This is the key element in socio-technical systems theory. If we look to modern production and management philosophies, it contains socio-technical elements in varying degrees. Sociotechnical” indicates that the system consists of workers, tools, technology and their relationships [90]. To achieve desirable goals such as productivity, on-time-delivery, quality and continuous improvement, the different aspects and subsystems of the work systems should be properly aligned and mutually supportive [91, 92]. The essence of STS philosophy has been summarized in a set of principles, such as "minimum critical specification" which entails that workers should be told what to do but not how to do it (Knutstad et al., 2009, Cherns, 1987).,and "information flow", meaning that information should be given to those who need it, when they need it. (Cherns, 1976). In organisational theory, the current interest in work systems is usually framed under “teambased” (Muller et al., 2000), “lean production” (Shah and Ward, 2007, Delbridge et al., 2000), or “high-performance” (Boxall and Macky, 2009). Team based work implies a reversal of the detailed technical division of labour and the Tayloristic separation between “thinkers” and “doers”. Lean production recommends empowering of employees, and work organisation by self-directed, multi-functional teams, which is in line with STS. Still, the constant strive to remove waste in lean production often leads to a reduction of resources spent on human development, such as competence development (Netland et al., 2008, Knutstad et al., 2009). Contemporary work systems typically integrate those who perform direct work, improvement work, technical experts and managers (Cutcher-Gershenfeld et al., 1994, Kim et al., 2010, Rolfsen et al., 2013). High-performance work systems aim to achieve superior performance through increased employee involvement and commitment (Boxall and Macky, 2009). Focusing on the human aspects of the work system, the high-performance perspective extends previous research on socio-technical systems, worker autonomy and work humanization, as well as employee driven innovation. Method As part of an on-going research project about zero-defect manufacturing, the authors of this paper has observed and participated in operators work in three case companies, to map the current situation at each site. To structure the case studies a topical framework for mapping (available upon request) was made, containing both methodological descriptions of how the researcher were to conduct the studies, and which topics to investigate. The topics covered a broad spectrum of issues, with the following headings: Production system, the team, quality, information and communication, management. Data collection methods have been qualitative, with a mix of observation, unstructured and semi-structured interviews (Yin, 2013). Mapping was done during two separate visits to each factory. Each visit lasted for two full days, of which one whole day was spent with operators to observe and participate in their everyday work. The first and second visits were conducted 1-2 months apart, so that the agenda for the second visit could be planned based on results from the 3

first visit. Researchers conducted the visits in pairs. Introductory meetings were held with key managers, such as production managers, process engineers and human resource managers, to discuss common problems, company culture and issues of future development. Combined with an overall tour of the premises, these meetings provided the understanding about each factory necessary to provide context to observation made on the shop floor. As preparation for the case studies, factory management had informed the operators about the purpose of the visit. Further, the researchers briefly explained about the project to the operators during conversations. The conversations with operators in production were mainly done on a one-to-one basis. The researchers asked operators questions as the operators went about their daily work. Brief notes were taken during conversations. To ensure maximum recollection the researchers wrote extensive notes together after each day of visit. In addition, feedback was given to both operators and management shortly after each visit, to ensure that the researchers had understood the situation. Case description All three case companies are Norwegian manufacturers. They are large enterprises in a Norwegian context, with several hundred employees and international markets. The three companies have different levels of automation, from low to high. For the sake of this paper we have named them:  Pretty Manual Line (PML)  Automated Machine Cells (AMC)  Robots In Line (RIL) We will here describe their situations regarding information flow to operators. Pretty Manual line (PML) The production at PML is very traditional. There is a low level of automation, with the machines performing simple, single tasks. The operators main work is to perform several manual tasks, such as to load products into the machines, run the machines, manually add materials/parts to the main products, and move products between different machines. Operators use computers to punch production information into the ICT system. Counts are read manually off machine displays, the number of items lost to testing/wreck is manually subtracted, and the resulting numbers are punched into the computer. In addition to the computers, the paper-based production notes constitute an important stream of information. Operators sign off on the note when the appurtenant items have been through a process. The production note covers the whole production line, and of such provides an overview of the internal value chain. Lastly, whiteboards are used to provide operators with information about production in a limited area of the production line. Although the ICT-system and production note contain a lot of information, operators do not say that they use these as sources for information. The operators feeds information into the ICTsystem and production notes, but do generally not extract information from them. Seemingly, operators at PML only relate to the daily production target for their part of the line, and lack any information about the rest of production. PML's production area is divided into several buildings, and it is difficult for anyone to have a complete overview of production progress. It was only by chance we observed a key information channel for value chain information to the operator; namely the forklift driver. Because the forklift driver moves the products along the production line between buildings and storages, the forklift-driver attains an overview of production and inventory status across the whole production line. Thus, operators can ask the forklift-driver about other parts of 4

production, and have done so to the extent that it has become part of the driver's job to convey information between buildings. This was discovered during our observation of production, as the forklift-driver called out "8000" when entering the building – which was the number of items in an intermediate storage. The information conveyed by the forklift-driver helps operators to make decisions about production. Although the needed information might be available in the computer system, the operators prefer to ask the forklift driver. This is partly due to a cumbersome computer system and partly due to lack of knowledge about what information exists in the computer system, meaning that asking the forklift-driver is the fastest option. Further, we observed that the computer system is not adapted to operator needs, as they had to calculate the numbers they needed when they should have been able to read them right off the screen. To summarize, this company is still in the "paper-age" – a description the company itself agreed on. Automated Machine Cells (AMC) AMC's production is organized as functional cells, and each item may pass through the same cell several times. This results in a rather complex production flow. The machinery is quite automated. Once started, machines perform complex operations without interference from the operator. The operators' main tasks are to load/unload items to the machine, start machines, change tools as needed, and monitor machines in case of malfunctions. Due to long processing times in most of the machines, monitoring accounts for a large part of the operators' time. The production flow at AMC is characterized by many sources of variance. Machine errors are an everyday issue at AMC. Further, some operations are not possible to automate and must be done manually. The very small tolerances on product specifications are hard to achieve with manual work and so considerable corrections are often necessary. Finally, because the main products are very expensive, and thus incurs large amounts in tied-up capital if held as inprocess inventory, AMC seeks to minimize inventory buffers in production. With large variances and small buffers, each cell at AMC experiences large variations in production flow. Even the bottlenecks occasionally experience lack of work. Ostensibly, due to the complex production flow and multiple sources of variance in production, AMC has dedicated production coordinators working in the factory. These coordinators keep track of in-house inventory and progress in production. Although the coordinators do not have formal responsibility for production, they are key decision-makers – making decisions such as what to produce and when. The coordinators are physically present in production, and operators say that they receive most of the information they need about production flow from coordinators and managers. Thus, information about production flow is mainly collected visually by one person, and then spread to operators by conversation. During our visit to AMC we got to interview one of the coordinators, who was also the first person to work as a coordinator at AMC. This coordinator had previously worked as a manager in production, but had to find another role after a longer absence. Having many years of experience from production, it was easy to know what could be done to improve the work for operators and production management. The role "coordinator" then emerged, fulfilling a much needed support function for operators and production managers. Since then, several departments of AMC has gotten their own coordinator. Coordinators cover larger parts of the internal value chain than production managers do, which is an advantage when managing production flow. As AMC's production has quite advanced technology, we expected the information flow to be more digitalized. To some degree it is – managers, coordinators and even some experienced 5

operators use information from a digital production planning system to make decisions in production. It is worth mentioning that those using the digital planning system is quite displeased with the system, as it is cumbersome to use and does not support re-planning and proactivity to adjust for the high variances in production flow. However, most operators at AMC do not use the digital production planning system. Operators receive information from other people in the factory, and from whiteboards and production notes. Therefore, from the operators' point of view the information flow is manual, with information being collected by visual inspection and spread by conversation. In this case, AMC is yet another example of how existing digital information systems are not designed for the operator. Robots In Line (RIL) RIL has a highly automated production line, with robots doing most of the work. There are few (2-3) operators in the factory, and so each operator has a lot to do. They load and unload parts to the line, do quality measurement on the products, and different maintenance tasks. The current production line at RIL is quite new, and still in a commissioning phase. Thus, the operators also spend a lot of time solving problems with the machines, or waiting while others solve the problems. Even with such advanced technology in production, there is little difference in how operators at RIL receive information, compared to the other two case companies. Operators at RIL mainly receive information by conversations with factory managers. Whiteboards are used extensively, depicting a multitude of information including production and quality performance. There is even some paper-based information flows: They have a book where the shift leader notes down any problems that have occurred in production. These notes are then read by the leader of the next shift, and also used by factory management as input to improvement work. The only digital information the operator relates to in everyday work in this very modern production facility, is a screen showing in real-time the number of items produced during current shift, the target, and the number of items the last shift had produced at that time. Having this small piece of realtime information to the operator is however a step up from the other case companies. Operators say that flow of information between shifts is a challenge. Those who work at the day-shift gets much more information than the night shift – because management is only there at daytime. The richness and responsiveness that face-to-face conversation provides is of course not to be disregarded, however the challenge that RIL experiences with different shifts getting different information shows the pitfalls of not having a more structured information system. A case at RIL shows us the importance of providing operators with information about the status of improvement projects going on at their workplace. The use of oil in the process means operators must wipe oil of the finished products – an un-ergonomic and boring task. While management is working hard on finding a solution, they have not communicated this back to the operators. Seemingly, nothing is going on to solve the problem, and operators feel management does not prioritize their welfare and wishes. While this kind of information might not be essential for efficiency in an industry 4.0 setting, it is important for operators' well-being. Discussion We will in the following focus on one principle of Industry 4.0, namely decentralized decision-making (Hermann et al., 2016). Decentralized decision-making implies: "The ability of cyber physical systems to make decisions on their own and to perform their tasks as autonomous as possible. Only in case of exceptions, interferences, or conflicting goals, tasks are delegated to a higher level" (op cit.). In order to enable such decisions at operator level, the information flow must reach operators, and be of sufficient quality, richness and timeliness to 6

support decision-making. The operator in an industry 4.0 enterprise cannot any longer limit himself or herself to only the production system. The operator will need information about the whole of the enterprise, ranging from market situation, production status at all phases of the value chain (possibly including suppliers), quality information and requirements, maintenance and technical status of the system. When errors occur and decisions are needed the operator should be able to analyse and find root causes, as well as take optimal actions dependent on the overall situation. The three cases show that the information flow is not anywhere near industry 4.0 requirements. First, the information flows in modern manufacturing is disintegrated. The three case companies all have several, separate computer programs that could utilize production information to both optimize production and generate documentation automatically, but none of these programs work together. Second, these systems are designed for factory middle management, who already spend enough of their time wrestling advanced computer programs. The potential that lies in the existing ICT-system is largely under-utilized, due to disintegration and cumbersome user interfaces. Further, and more important, information is not provided to those who really need it to make decisions, namely the operators. Managers at the case companies are aware of how digital information systems could help them in their own work. They would like dynamic and integrated systems that can combine information about both machines (errors, processing times, etc.) and humans (competence, absence, etc.) to optimize production for the whole factory. However, in this envisioned interconnected factory, they have not considered how the role of the operator should change. In this vision operators are mainly doing the same task, but then on more than one machine at the time. In reality, in Industry 4.0 operators will take on tasks that are currently performed by managers. Providing operators with a real-time overview of production flow and buffers/inventories would save the resources currently spent on attaining such information otherwise, and enable operators to take more responsibility for overall production flow. Even though the operators themselves are not aware of their own need for information, it is clear from the role that has emerged as information channels for the forklift driver at PML, and the coordinator at AMC, that the operators need information about the value chain. If this information is not provided digitally, other methods will be employed, be they oral or paper based. For the operators these solutions work well, as long as the driver/coordinator is not absent. However, when they are absent, operators waste time running between processes to attain the required information. Further, keeping track of inventory levels becomes a challenge, as the driver/coordinator are the only ones who has a comprehensive overview. There is a need for efficient managing of information, where information is displayed to the user according to the user's current needs (Lee et al., 2013, International Society of Automation, 2015), to help operators deal with the increased amount and richness of communication. With the current change of manufacturing towards Industry 4.0, this issue becomes even more urgent. The highly motivated operators currently lack the information to participate further in such things as flow optimization and quality improvement. There are obvious potential benefits from modernizing the information flow in production in a way that enables operators to live up to their full potential. Complex, high-pace production systems demand real time coordination and problem solving by people close to production. Conclusion We argue that the poorly performing information systems we find in manufacturing today is a result of a manufacturers favouring technology over humans – as long as the machines are 7

running everything else will sort itself out. Decisions on technology are given priority, and decisions on organisation and workers are fought with after technology and frame conditions are given. High-tech companies still focus too little on the competitive momentum stemming from the human and organizational side. This technocratic view has resulted in information systems that are sub-par and do not optimally support humans in their work. In addition, the operators need for information has been ignored, as information systems are made for management. We have done thorough case studies at three Norwegian manufacturers to map the operators current work, and viewed Industry 4.0 scenarios from a socio-technical perspective to predict the operators future work and needs. Digitalization has not yet reached the operator. This is true for all three of our case companies, despite the differences in technology level in production, and is also true for Norwegian manufacturing in general (Norsk Industri, 2016). Clearly, although the fourth industrial revolution is driven by technological development, an equally important and corresponding organisational development is required to remain competitive in the future industry. Focusing on the operator role, we have some recommendations for practitioners who aim to be Industry 4.0 manufacturers. First, information systems need to support the operator, and should be configured considering the operator (and not management) as the primary user. Second, operators should be organized in autonomous teams, with redundancy of competence, and decision authority, according to STS principles. Clearly, the system as a whole would be more efficient if operators had the necessary information to optimize their work, but this realization demands the operators work to be seen from a comprehensive, socio-technical perspective. Relative to earlier production systems the information flow in the case companies has not yet transformed into a system enabling decentralized decision-making. This must happen before the enterprises can reap the benefits of industry 4.0. We have no reason to believe that our three case companies are behind Norwegian or international manufacturing industry in this respect, thus the issue of information flow is a crucial for all industries wanting to move towards industry 4.0. References BLANCHET, M., RINN, T., THADEN, G. & THIEULLOY, G. 2014. Industry 4.0: The new industrial revolutionHow Europe will succeed. München. BOXALL, P. & MACKY, K. 2009. Research and theory on high‐performance work systems: progressing the high‐ involvement stream. Human Resource Management Journal, 19, 3-23. BUREAU OF LABOR STATISTICS 2012. Charting International Labor Comparisons. International Labor Comparisons. U. S. Department of Labor. CHERNS, A. 1987. Principles of Sociotechnical Design Revisted. Human Relations, 40, 153-161. CUTCHER-GERSHENFELD, J., NITTA, M., BARRETT, B., BELHEDI, N., BULLARD, J., COUTCHIE, C., INABA, T., ISHINO, I., LEE, S. & LIN, W.-J. 1994. Japanese team-based work systems in North America: explaining the diversity. California Management Review, 37, 42-64. DELBRIDGE, R., LOWE, J. & OLIVER, N. 2000. Shopfloor responsibilities under lean teamworking. Human Relations, 53, 1459. EUROPEAN COMMISSION 2013. Factories of the future - Multi-annual roadmap for the contractual PPP under Horizon 2020. Luxembourg: Publications Office of the European Union. EVANS, P. C. & ANNUNZIATA, M. 2012. Industrial internet: Pushing the boundaries of minds and machines. General Electric. November, 26. HERMANN, M., PENTEK, T. & OTTO, B. Design Principles for Industrie 4.0 Scenarios. 2016 49th Hawaii International Conference on System Sciences (HICSS), 5-8 Jan. 2016 2016. 3928-3937. INTERNATIONAL MONETARY FUND 2013. Norway: 2013 Article IV Consultation. INTERNATIONAL SOCIETY OF AUTOMATION 2015. ISA 101, Human-Machine Interfaces. KAGERMANN, H., HELBIG, J., HELLINGER, A. & WAHLSTER, W. 2013. Recommendations for Implementing the Strategic Initiative INDUSTRIE 4.0: Securing the Future of German Manufacturing Industry; Final Report of the Industrie 4.0 Working Group. Forschungsunion.

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