Cyber-Physical Production System

A Computer Science Perspective on Digital Transformation in Production

philipp — Thu, 17 Feb 2022 12:48:04 +0000

A Computer Science Perspective on Digital Transformation in Production philipp Thu, 02/17/2022 - 13:48

Abstract

The Industrial Internet-of-Things (IIoT) promises significant improvements for the manufacturing industry by facilitating the integration of manufacturing systems by Digital Twins. However, ecological and economic demands also require a cross-domain linkage of multiple scientific perspectives from material sciences, engineering, operations, business, and ergonomics, as optimization opportunities can be derived from any of these perspectives. To extend the IIoT to a true Internet of Production , two concepts are required: first, a complex, interrelated network of Digital Shadows which combine domain-specific models with data-driven AI methods; and second, the integration of a large number of research labs, engineering, and production sites as a World Wide Lab which offers controlled exchange of selected, innovation-relevant data even across company boundaries. In this article, we define the underlying Computer Science challenges implied by these novel concepts in four layers: Smart human interfaces provide access to information that has been generated by model-integrated AI . Given the large variety of manufacturing data, new data modeling techniques should enable efficient management of Digital Shadows, which is supported by an interconnected infrastructure . Based on a detailed analysis of these challenges, we derive a systematized research roadmap to make the vision of the Internet of Production a reality.

DOI

https://doi.org/10.1145/3502265

How Correct and Defect Decision Support Systems Influence Trust, Compliance, and Performance in Supply Chain and Quality Management – A Behavioral Study Using Business Simulation Games

philipp — Sat, 22 Aug 2020 16:14:42 +0000

How Correct and Defect Decision Support Systems Influence Trust, Compliance, and Performance in Supply Chain and Quality Management – A Behavioral Study Using Business Simulation Games philipp Sat, 08/22/2020 - 18:14

Abstract

Supply Chains and production networks are complex sociotechnical cyber-physical systems whose performance is determined by system, interface, and human factors. While the influence of system factors (e.g., variances in de- livery times and amount, queuing strategies) is well understood, the influence of interface and human factors on supply chain performance is currently insuffi- ciently explored. In this article, we analyze how performance is determined by the correctness of Decision Support Systems and specifically, how correct and defect systems influence subjective and objective performance, subjective and objective compliance with the system, as well as trust in the system. We present a behavioral study with 50 participants and a business simulation game with a market driven supply chain. Results show that performance (-21%), compliance (-35%), and trust (-25%) is shaped by the correctness of the system. However, this effect is only substantial in later stages of the game and occluded at the be- ginning. Also, people’s subjective evaluations and the objective measures from the simulation are in congruence. The article concludes with open research questions regarding trust and compliance in Decision Support Systems as well as actionable knowledge on how Decision Support Systems can mitigate supply chain disruptions.

Brauner, P., Calero Valdez, A., Philipsen, R., Ziefle, M.: How Correct and Defect Decision Support Systems Influence Trust, Compliance, and Performance in Supply Chain and Quality Management – A Behavioral Study Using Business Simulation Games. In: Nah, F. and Tan, C. (eds.) HCI in Business, Government, and Organizations (HCIGO), HCI International 2017. pp. 333–348. Springer, Cham (2017).

DOI

https://doi.org/10.1007/978-3-319-58484-3_26

Tags

Related Project(s):

Integrative Production Technology for High-Wage countries

Figures and Tables (selection):

Cognition-Enhanced, Self-optimizing Production Networks

philipp — Thu, 20 Aug 2020 16:24:34 +0000

Cognition-Enhanced, Self-optimizing Production Networks philipp Thu, 08/20/2020 - 18:24

Abstract

8.1 Summary
Companies are facing a wide range of challenges in the field of customer demand, dynamic environment conditions, and quality problems regarding the management level. Therefore, they need to adapt themselves and their processes to the dynamic environment conditions. Examples are movements in customer demand, resched- ules in supply, as well as turbulences in networks. Thus, high process efficiency and a wide availability of information are characteristics of a successful production management.
Hereby, the management of negative consequences is challenging. Negative consequences can lead to wrong decisions in the planning processes caused by poor communication or conventional solution approaches based on centralized planning methods. This leads to companies that react slower and more inflexible on internal and external disturbances and consequently to an increasing gap between reality and intention.
Another result of volatile markets and a demand for high flexibility is a fast-changing production environment that requires frequent adjustments of pro- duction control configuration to ensure companies produce at competitive costs. However, companies rarely check and adjust their production control configuration due to the high effort for analyzing the current situation and calculating or simulating alternatives.
On the shop floor, the complexity of automated and semiautomated production systems results in a variety of different objectives that have to be considered in the discrete manufacturing industry. In regard to the planning and control of production processes, the underlying optimization problem is multidimensional. In order to reduce efforts, especially for product orientation and mass customization, methods to automatically adjust to new environments and new objectives are required.
Dealing efficiently with the dynamic environment of production is one of the most challenging tasks of production planning and control (PPC) in high-wage countries. The cluster of excellence “Integrative Production Technologies for High Wage Countries” at RWTH Aachen University addresses these opportunities and challenges and aims at resolving the “polylemma of production” which spans along two dilemmas: plan-oriented versus value-oriented production and scale versus scope. To compete in globalized markets, enterprises must solve this polylemma and growing interconnectivity of technical systems between different tiers of a production network and across companies is a possible solution. While enterprise resource planning (ERP) systems and manufacturing execution systems (MES) are increasingly penetrating manufacturing companies and automated processes increase companies’ productivity by optimizing the flow of resources and information, there are—and always will be—human operators in the loop that maintain control, take responsibility, and who must have a profound understanding of aspects not modeled in these systems.
The main result, which has been achieved in previous phases of the project, is a cybernetic model structuring a self-optimizing production management on its different levels, capable of coping with dynamics and to continuously adjust itself. Based on these results, the project addresses now the comprehensive application of self-optimizing planning and control on all levels of the value chain. This implies the integration of self-optimizing control loops on cell level with those addressing the PPC as well as supply chain and quality management aspects and will lead to an improvement of planning decisions on different levels of the production network. A specific focus is on the consideration of human decisions during the production process when elaborating the cognitive model. To establish socio-technical control loops, it is necessary to understand how human decisions in diffuse working processes as well as cognitive and affective abilities form the human factor within production processes are made.
To enable companies to react fast to these challenges, means of self-optimization have been developed for the different levels of the value chain (supply chain, production control and shop floor).
One main result is a reference model for the intercompany material and information flow between companies. In order to enable the system and subsystem to optimize dynamically and independently, logic from the control theory were adopted and transferred to enable a real-time coordinated PPC between companies on the level of the supply chain. Principles from the viable system model (VSM) have been transferred to the developed concept which serves as a basis for self-optimizing control loops. In order to study the interrelationships between human diversity, novel VSM-based decision support systems, and the technical parts of production systems and the industrial Internet, a novel research framework through business simulation games is proposed. The business simulations used originate from the VSM modeling and allow the identification and quantification of human factors in socio-technical production environments, serving as benchmarks to evaluate decision support systems and their user interfaces. In this research, it is demonstrated that usability of enterprise software has a quantifiable positive influence on effectiveness and efficiency in decision scenarios. It was further established that some users are able to compensate for the negative effect of bad user interfaces, but that the costs of poor usability grow quickly for others if the amount and complexity of information increase.
On the level of the production control, the simulation tool WoPS 4.0 has been developed in order to support the necessary analyses and helping companies with optimally adjusting their production control configuration. This tool consists mainly of architecture for the automatic generation of simulation models and can be connected in a self-optimizing control loop to PPC systems of manufacturing companies for permanently checking production control performance. The production supervisor is only provided with information from the system if action is needed. This results in a highly reduced effort for production supervisors and the possibility to adjust production control configuration in a superior fashion. By enabling companies to produce economically, an important contribution to strengthen companies in high-wage countries is made.
Regarding the shop-floor level, research was carried out to develop self-optimization production lines with incorporate human decision behavior. Thus, a cognitive automation for robotic assembly processes was developed. By means of generic assembly knowledge and cognitive decision-making, the system is not only able to adjust itself to environmental changes, but also to make comprehensible decisions that conform to the operator’s expectations. Further research has shown that introducing anthropomorphic movements for assembly robots can additionally decrease the mental stress of the operator and increase the predictability of the system behavior. Thereby, the human is able to trust the system, which is advantageous especially in case of direct human–robot cooperation.
Furthermore, the developed Viable MES (VMES) focuses on the modeling and integration of a production control unit for automated production systems that are structured according to the VSM. The system is able to incorporate different goals in different hierarchies of the overall factory. Its viability enables a further inte- gration of socio-technical aspects regarding the planning and coordination for the overall factory as well as the specific processes. One major challenge in processes with high cycle times is to increase the overall equipment effectiveness (OEE)— mainly by focusing the technical availability. A common approach is to apply condition monitoring together with predictive maintenance in order to avoid unplanned downtimes. Nevertheless, process interruptions due to wear do not lead to component failure in the first place. The cloud-based integration and therefore combination of a broad data basis, powerful algorithms, and machine, respectively, component models promise significant improvements for wear detection and pro- cess adjustment.

Schlick, C., Stich, V., Schmitt, R., Schuh, G., Ziefle, M., Brecher, C., Blum, M., Mertens, A., Faber, M., Kuz, S., Petruck, H., Fuhrmann, M., Luckert, M., Brambring, F., Reuter, C., Hering, N., Groten, M., Korall, S., Pause, D., Brauner, P., Herfs, W., Odenbusch, M., Wein, S., Stiller, S., Berthold, M.: Cognition-Enhanced, Self-optimizing Production Networks. In: Brecher, C. and Özdemir, D. (eds.) Integrative Production Technology - Theory and Applications. pp. 645–743. Springer International Publishing, Berlin, Heidelberg (2017).

DOI

https://doi.org/10.1007/978-3-319-47452-6_8

Preparing Production Systems for the Internet of Things - The Potential of Socio-Technical Approaches in Dealing with Complexity

philipp — Thu, 20 Aug 2020 16:06:10 +0000

Preparing Production Systems for the Internet of Things - The Potential of Socio-Technical Approaches in Dealing with Complexity philipp Thu, 08/20/2020 - 18:06

Abstract

The Internet of Things will influence how production systems of the future will work. An expected change is the increase in complexity when production system will start communicating with each other. This complexity can be managed by applying socio-technical approaches. This includes analyzing a production system regarding the domains: tasks, actors, technology, and structure. We identified three topics per domain that we think need further investigation, as they may influence complexity to a strong degree. For tasks we suggest looking into urgency, habituation, and strategies; for actors we suggest looking into skills, human factors, and user diversity. In the field of technology we find visualization, decision support, and interactions to be most pressing, while in the field of structure we see responsibility, delegation, and communication.

Calero Valdez, A., Brauner, P., Ziefle, M.: Preparing Production Systems for the Internet of Things - The Potential of Socio-Technical Approaches in Dealing with Complexity. In: Dimitrov, D. and Oosthuizen, T. (eds.) Proceedings of the 6th International Conference on Competitive Manufacturing 2016 (COMA ’16). pp. 483–487. CIRP, Stellenbosch, South Africa (2016).

Interdisciplinary cooperation management in research clusters: A review of twelve years.

philipp — Thu, 20 Aug 2020 15:11:01 +0000

Interdisciplinary cooperation management in research clusters: A review of twelve years. philipp Thu, 08/20/2020 - 17:11

Abstract

As an interdisciplinary research network, the Cluster of Excellence “Integrative Production Technology for High-Wage Countries” (CoE) comprises of around 150 researchers. Their scientific background ranges from mechanical engineering and computer science to social sciences such as sociology and psychology. In addition to content- and method-based challenges, the CoE's employees are faced with heterogenic organizational cultures, different hierarchical levels, an imbalanced gender distribution, and a high employee fluctuation. The sub-project Scientific Cooperation Engineering 1 (CSP1) addresses the challenge of interdisciplinary cooperation and organizational learning and aims at fostering interdisciplinarity and its synergies as a source of innovation. Therefore, the project examines means of reaching an organizational development, ranging from temporal structures to a sustainable network in production technology. To achieve this aim, a broad range of means has been developed during the last twelve years: In addition to physical measures such as regular network events and trainings, virtual measures such as the Terminology App were focused. The app is an algorithmic analysis method for uncovering latent topic structures of publications of the CoE to highlight thematic intersections and synergy potentials. The detection and promotion of has been a vital and long known element in knowledge management. Furthermore, CSP1 focusses on project management and thus developed evaluation tools to measure and control the success of interdisciplinary cooperation. In addition to the cooperation fostering measures, CSP1 conducted studies about interdisciplinarity and diversity and their relationship with innovation. The scientific background of these means and the research results of CSP1 are outlined in this paper to offer approaches for successful interdisciplinary cooperation management.

Müller-Abdelrazeq, S., Brauner, P., Calero-Valdez, A., Jansen, U., Platte, L., Schaar, A.K., Steuer, L., Zachow, S., Schönefeld, K., Haberstroh, M., Leicht-Scholten, C., Ziefle, M., Isenhardt, I.: Interdisciplinary cooperation management in research clusters: A review of twelve years. In: Proceedings of the International Conference on Intellectual Capital, Knowledge Management and Organisational Learning, ICICKM (2018).

Projecting Efficacy and Use of Business Simulation Games in the Production Domain Using Technology Acceptance Models

philipp — Thu, 20 Aug 2020 15:00:54 +0000

Projecting Efficacy and Use of Business Simulation Games in the Production Domain Using Technology Acceptance Models philipp Thu, 08/20/2020 - 17:00

Abstract

Globalized markets, product complexity, and increased requirements on quality lead to growing complexity of business and manufacturing processes. Game-Based learning environments and business simulation games offer great potential to prepare employees the increasing complexity. As it is unclear who profits most from these learning environments, we did a study with 66 partici- pants on a game for conveying Production Planning and Control and Quality Management. In our research model we combined personality attributes and two common technology acceptance models to determine factors projecting perfor- mance in the game and projected later use of business simulation games in gen- eral. We found that main drivers for usage are performance expectancy and trans- fer of skill, i.e., the perceived applicability of the learned knowledge and skills for the later work. The attained performance is unrelated to the projected use. The article concludes with guidelines to increase the likelihood for the later use of business simulation games and for increasing their overall efficacy.

Brauner, P., Philipsen, R., Ziefle, M.: Projecting Efficacy and Use of Business Simulation Games in the Production Domain Using Technology Acceptance Models. In: Schlick, C. and Trzcieliński, S. (eds.) Advances in Ergonomics of Manufacturing: Managing the Enterprise of the Future. pp. 607–620. Springer International Publishing (2016).

DOI

https://doi.org/10.1007/978-3-319-41697-7_52

Tags

Related Project(s):

Integrative Production Technology for High-Wage countries

Figures and Tables (selection):

On Studying Human Factors in Complex Cyber-Physical Systems

philipp — Thu, 20 Aug 2020 14:53:18 +0000

On Studying Human Factors in Complex Cyber-Physical Systems philipp Thu, 08/20/2020 - 16:53

Abstract

Deep penetration of modern information and communication technology in manufacturing companies (vertical integration) and across supply chains (horizontal integration) leads to an increasing amount and complexity of information that needs to be perceived, filtered, processed, and reacted to. Yet, the human factors that influence performance are insufficiently understood. This article outlines that individual factors, interface factors, and system factors affect overall performance and it presents two complementary research methodologies for identifying and quantifying these factors. On one side, we show that controlled laboratory experiments with singular decision tasks can precisely identify and quantify factors contributing to performance. On the other side, we use business simulation games with realistic decision tasks that can quantify the complexity of the underlying system. Our studies show that information amount, complexity, and presentation affect performance and that Decision Support Systems can increase performance and decrease error rates if and only if they are designed correctly. The article concludes with a research agenda to specifically understand which factors influence performance and how humans in the loop can be supported.

Brauner, P., Valdez, A.C., Philipsen, R., Ziefle, M.: On Studying Human Factors in Complex Cyber-Physical Systems. In: Workshop Human Factors in Information Visualization and Decision Support Systems Held as Part of the Mensch und Computer 2016. Gesellschaft für Informatik (2016).

DOI

https://doi.org/http://dx.doi.org/10.18420/muc2016-ws11-0002

Tags

Related Project(s):

Integrative Production Technology for High-Wage countries

Figures and Tables (selection):

Human Factors in Production Systems - Motives, Methods and Beyond

philipp — Thu, 20 Aug 2020 13:59:54 +0000

Human Factors in Production Systems - Motives, Methods and Beyond philipp Thu, 08/20/2020 - 15:59

Abstract

Information and communication technology (ICT) is getting smaller and faster at a dashing pace and is increasingly pervading production technology. This penetration of ICT within and across production technology enables companies to aggregate and utilize massive amounts of data of production processes, both horizontally (across different products) and vertically (from machine level, over the shop floor, to the supply chain level). Presumably, this yields in Smart Factories with adaptable manufacturing processes that adjust to different goals, such as performance, product quality, or resource efficiency. But the increasing amount of available data also raises considerable challenges: Strategic decisions still depend on humans in the loop who have to perceive and process increasingly complex multi dimensional data sets and to make decisions whose effects are increasingly difficult to forecast. This paper is concerned with the potential of the human factor. Along with three case studies, we demonstrate the potential of human factors in the development of applications for Smart Factories and enterprises in the era of Industry 4.0. The paper concludes with a set of guidelines and methods for the user-centred development of applications for Industry 4.0.

Brauner P., Ziefle M. (2015) Human Factors in Production Systems. In: Brecher C. (eds) Advances in Production Technology. Lecture Notes in Production Engineering. Springer, Cham.

DOI

https://doi.org/10.1007/978-3-319-12304-2_14

A Research Framework for Human Aspects in the Internet of Production – An Intra-company Perspective

philipp — Thu, 20 Aug 2020 13:19:34 +0000

A Research Framework for Human Aspects in the Internet of Production – An Intra-company Perspective philipp Thu, 08/20/2020 - 15:19

Abstract

Digitalization in the production sector aims at transferring concepts and methods from the Internet of Things (IoT) to the industry and is, as a result, currently reshaping the production area. Besides technological progress, changes in work processes and organization are relevant for a successful implementation of the “Internet of Production” (IoP). Focusing on the labor organization and organizational procedures emphasizes to consider intra-company factors such as (user) acceptance, ethical issues, and ergonomics in the context of IoP approaches. In the scope of this paper, a research approach is presented that considers these aspects from an intra-company perspective by conducting studies on the shop floor, control level and management level of companies in the production area. Focused on four central dimensions—governance, organization, capabilities, and interfaces—this contribution presents a research framework that is focused on a systematic integration and consideration of human aspects in the realization of the IoP.

Brauner, P., Brillowski, F., Dammers, H., Königs, P., Kordtomeikel, F., Petruck, H., Schaar, A.K., Schmitz, S., Steuer-Dankert, L., Mertens, A., Gries, T., Leicht-Scholten, C., Nagel, S., Nitsch, V., Schuh, G., Ziefle, M.: A Research Framework for Human Aspects in the Internet of Production – An Intra-company Perspective. Adv. Intell. Syst. Comput. 1216 AISC, 3–17 (2020).

DOI

https://doi.org/10.1007/978-3-030-51981-0_1

Tags

Related Project(s):

Internet of Production (IoP)

Figures and Tables (selection):

Understanding Human Factors in Supply Chains and Quality Management by Using Business Simulations

philipp — Thu, 20 Aug 2020 11:11:52 +0000

Understanding Human Factors in Supply Chains and Quality Management by Using Business Simulations philipp Thu, 08/20/2020 - 13:11

Abstract

In a globalized world the complexity of cross-company supply chains is increasing. Within the Cluster of Excellence “Integrative Production Technology For High Wage Countries” and one of its research domains “cognition enhanced self-optimizing production networks” methods to understand the complexity and to increase the overall efficiency are explored. Supply chains are considered as socio-technical systems whose performance is not only determined by technical aspects, such as varying quality, changing demands and delays, but also by humans in-the-loop and their personal experience, their ability to cope with complexity and the decision support given by enterprise software. To investigate how human factors influence the performance of supply chains a controllable game based test environment was developed, in which subjects interact with a simulated supply chain. The simulation model is based on Forrester’s Beer Distribution Game, extended by quality management aspects. Exploratory studies revealed technical and human factors influencing performance. Also, changes in the user interface and the presentation of visual indicators on selected variables increased the performance significantly, indicating the need for in-depth studies on refinements of current Enterprise Resource Planning systems. Furthermore, the study revealed that using the supply chain game increased the awareness for quality management. Hence, the game can be a fun and still highly effective module within the vocational training of both quality managers, as well as supply chain managers.

Brauner, P.: Understanding Human Factors in Supply Chains and Quality Management by Using Business Simulations. In: Brecher, C. and Wesch-Potente, C. (eds.) Proceedings of the Conference of the Cluster Of Excellence “Integrative Production Technology For High Wage Countries” 2014/1. pp. 387–396. Apprimus Verlag, Aachen, Germany, Aachen, Germany (2014).