The redesign of blue- and white-collar work triggered by digitalization:collar matters

The implementation of digital technologies in the context of Industry 4.0 radically changes methods of production and thereby the jobs of blue-collar workers. Although the work design effects of digitalization on the operator 4.0 have been explored in the existing literature, less is known about the simultaneous effects on white-collar work and the underlying (re)design process of human work including the factors that shape this process. To address this gap, we performed an in-depth industrial case study of an organization in the process of digitalization. Our findings confirm the concurrent impact of digitalization on blue- and white-collar work and suggest that its human implications highly depend on the extent to which, and at what moment, human factors are considered during the design and implementation process. Where work design knowledge lacked, the motivation of system designers turned out to be an important individual factor to realize favorable work design outcomes. At the organizational level, results show the importance of early involvement of system users and incorporating social performance indicators in addition to operational performance indicators in the statement of project goals. Our findings provide important empirical input for the further development of human-centric models and theories that integrate the challenges and opportunities for blue- and white-collar workers that are emerging when adopting digital technologies

Manufacturing Execution Systems: The Next Level of Automated Control or of Shop-Floor Support?

Part 6: Industry 4.0 - Smart FactoryInternational audienceManufacturing Execution Systems (MES) are at the heart of industrial organizations’ endeavors. While MES were traditionally positioned as an integration technology to bridge the shop-floor with higher level business systems, their current focus seems to be on the digitization of shop-floor activities for the collection, analysis and exchange of real-time information. Still, there remains dispute on the role of MES, specifically with respect to the functions they support in relation to other information systems in the automation pyramid, and their resulting interactions with humans. While MES are often positioned as the top layer of automated control of manufacturing processes, it is perceived by others as an integrated decision support system for the shop-floor. This study aims to shed light on the role of MES to either automate or to augment human tasks. Based on insights of a case study, we found that MES are neither automatic control nor solely decision support. MES’ main role is the creation and maintenance of digital twins of products. This involves human interaction, which closely resembles work related to computer-aided engineering (CAE) systems. We expect that work in the sphere of MES will therefore increasingly resemble engineering work

Work design in future industrial production: Transforming towards cyber-physical systems

Rapid advancements in an array of digital technologies and applications promote the transformation of industrial production into cyber-physical systems (CPS). This process is projected to lead to a completely new level of process automation, thereby redefining the role of humans and altering current work designs in yet unknown ways. However, existing literature is rather ambiguous and not explicit on how the transformation towards CPS affects work design. In this study, we therefore consider this transformation at a much more detailed level. Our main contribution is the development of a framework to assess work design changes in the transformation towards CPS, and the consideration of the role of management choice therein. The framework relates (future) capabilities of CPS on the machine, production line, factory and supply chain scope to functions of human information processing. We then evaluate how the potential automation or augmentation of those functions by CPS affects job characteristics. Automation in this context is defined as the transfer of control and decision-making from humans to CPS, while augmentation means that technology is used to enhance human productivity or capability. We expect that the transformation towards CPS and the resulting automation and augmentation of tasks will shift the majority of human work to jobs characterized by high levels of job complexity, job autonomy and skill variety. This effect will become more severe when tasks are increasingly automated in the transformation towards CPS. During this development, human skills and knowledge will presumably remain critical in near future industrial production. Nevertheless, the ultimate implications for work design are strongly dependent on management choice. Strategic decisions are required on (1) which functions to automate across different scopes of operations and (2) how to group the resulting pool of tasks into jobs. This may result in various work designs. However, this choice is to a certain degree limited, and the role of technology is to restrict, rather than determine management choice

Manufacturing Execution Systems: The Next Level of Automated Control or of Shop-Floor Support?

Manufacturing Execution Systems (MES) are at the heart of industrial organizations’ endeavors. While MES were traditionally positioned as an integration technology to bridge the shop-floor with higher level business systems, their current focus seems to be on the digitization of shop-floor activities for the collection, analysis and exchange of real-time information. Still, there remains dispute on the role of MES, specifically with respect to the functions they support in relation to other information systems in the automation pyramid, and their resulting interactions with humans. While MES are often positioned as the top layer of automated control of manufacturing processes, it is perceived by others as an integrated decision support system for the shop-floor. This study aims to shed light on the role of MES to either automate or to augment human tasks. Based on insights of a case study, we found that MES are neither automatic control nor solely decision support. MES’ main role is the creation and maintenance of digital twins of products. This involves human interaction, which closely resembles work related to computer-aided engineering (CAE) systems. We expect that work in the sphere of MES will therefore increasingly resemble engineering work

Identifying the Role of Manufacturing Execution Systems in the IS Landscape: A Convergence of Multiple Types of Application Functionalities

Manufacturing execution systems (MES) enable the detailed control of manufacturing operations, i.e. they facilitate digital and integrated shop-floor systems as envisioned by Industry 4.0. Yet, many manufacturing organizations struggle to integrate MES and demarcate it from other information systems (IS) in manufacturing. Therefore, this paper explores how MES can be functionally and technologically distinguished from other IS to determine its (future) role in the IS landscape. To provide an answer, this research applies the conceptualization of IS into five application functionalities and underlying enabling technologies. They are referred to as transaction processing, interactive planning, analytics, document management and process monitoring and control systems. We found that MES merges different types of application functionality into one system through its diverse functional requirements, and therefore can be characterized as technologically heterogeneous, in contrast to other ‘classical’ systems. MES then also takes on a central integrating role in the IS landscape. The findings offer an explanation for the challenges associated with the adoption of MES functionality, and highlight the importance of addressing integration questions in light of Industry 4.0

The Transformation Towards Smart (er) Factories:Integration Requirements of the Digital Twin

The vision of the smart factory with its interconnected systems is based on the seamless (real-time) integration of data across the information system (IS) landscape. Yet, due to the existence of many legacy systems, this task is far from trivial. In industrial practice, the IS landscape comprises systems of different application functionality which can be characterized as technologically heterogeneous, e.g. transaction processing versus real-time systems. Integrating such systems has always been a major challenge and constraining force for many organizations. This problem is receiving renewed attention in the context of the implementation of the digital twin in manufacturing. Due to its central role in the IS landscape, the digital twin needs to communicate with a number of heterogeneous applications to achieve its full potential, i.e. achieving a complete virtual representation of an asset, process or product. This research analyses the integration requirements from the perspective of the digital twins’ application functionality. In particular, we provide an explicit mapping of the integrations needed between the digital twin and existing information systems (IS) in manufacturing, which serves as a basis to better understand integration issues. These findings provide an explanation for and a conceptualization of some of the challenges that emerge when transforming towards an interconnected smart factory