Interdisciplinary engineering of cyber-physical production systems: highlighting the benefits of a combined interdisciplinary modelling approach on the basis of an industrial case

Abstract

In the context of cross-disciplinary and cross-company cooperation, several challenges in developing manufacturing systems are revealed through industrial use cases. To tackle these challenges, two propositions are used in parallel. First, coupling technical models representing different content areas facilitates the detection of boundary crossing consequences, either by using a posteriori or a priori connection. Second, it is necessary to enrich these coupled technical models with team and organizational models as interventions focusing on the collaboration between individuals and teams within broader organizational conditions. Accordingly, a combined interdisciplinary approach is proposed. The feasibility and benefits of the approach is proven with an industrial use case. The use case shows that inconsistencies among teams can be identified by coupling engineering models and that an integrated organizational model can release the modelling process from communication barriers.

BPMN++ to support managing organisational, multiteam and systems engineering aspects in cyber physical production systems design and operation

“…As appropriate tool support is essential for the successful cooperation in and between engineering teams and organisations (Friedl et al 2014;Dotoli et al 2019;Löwen et al 2020;Vogel-Heuser et al 2020a), it should be explicitly modelled. As more tools are being used to exchange knowledge between teams, they need to be integrated or coupled to support such cooperation processes.…”

“…Cyber physical production systems (CPPS) are complex, interconnected, intelligent and innovative product-service systems that require iterative processes and cross-disciplinary as well as cross-company cooperation in all phases of project realisation. Appropriate cooperation, that is, efficient information exchange between multiple interdisciplinary teams, is therefore crucial for the result of the project as inappropriate cooperation may cause delays, cost overruns and quality problems (Vogel-Heuser et al 2020a). Further impeding this challenge, machines and plants as parts of CPPS may operate for more than 30 years and often evolve already during the commissioning and start-up phases deviating from the as-built documentation of the supplier/contractor team (Birkhofer et al 2012).…”

“…Shared mental models can include models of task (e.g., task procedures and strategies), technology (e.g., equipment, operating procedures and system limitations), team interaction (e.g., roles, responsibilities and communication channels) or the team (e.g., teammates' skills, attitudes, preferences and knowledge) (Mathieu et al 2000). According to prior work (Vogel-Heuser et al 2020a) common understanding among all teams within the MTS (i.e., shared mental model) is emerging about important issues of the MTS like shared mental model of processes in the MTS (e.g., how is work conducted in the MTS? mentioned 20 times by 9 interviewees) and a shared mental model of partners in the MTS (i.e., who in the MTS is doing what with which goal?…”

Analysis of metamodels for model‐based production automation system engineering

“…capturing conflicts by transformation). Vogel‐Heuser et al [31] have found that inconsistencies can be detected easier with coupled technical models by a priori connections or post hoc tracing considering the perspectives of the collaborative human behaviours. They [32] have also presented the multi‐view collaboration method using knowledge‐base and shown a research demonstrator use‐case, still the method works in model level.…”

Intelligentes Rekonfigurationsmanagement selbstorganisierter Produktionssysteme in der diskreten Fertigung

“…Neben dem sich abzeichnenden Trend der CPPS [5] in der Industrieautomatisierung erfordern die zunehmende Volatilität in der globalen und lokalen Wirtschaft, die Verkürzung der Innovations-und Produktlebenszyklen sowie eine enorm steigende Variantenvielfalt Produktionssysteme, die diesen Anforderungsänderungen gerecht werden [6]. Diese sich ändernden Anforderungen führen dazu, dass die konkreten Zielsetzungen für Produktionssysteme in der Phase des Systementwurfs immer unvorhersehbarer werden.…”