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.

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The topic of supply network disruption recovery has started to receive great attention within the academic as well as the business world. This is due to increasingly complex supply networks and the rise of natural and man-made disasters in quantity and severity. In this paper, the topic is approached in an interdisciplinary bio-inspired way. The transferability of biological self-healing principles to the recovery of supply network disruptions is analysed and first propositions are derived. A single case study of the Japanese microcontroller company Renesas Electronics is analysed with regard to the developed propositions. A strategically important plant of Renesas was severely damaged by the triple disaster in Japan in 2011 which led to a disruption of the company's supply network. Five out of six propositions regarding the transferability of biological self-healing are, at least partly, proven. Furthermore, the importance of close collaboration within a network of suppliers, customers and competitors is emphasized. The results make further research in this academically still underdeveloped field promising, especially with regard to implications and strategies for supply chain risk managers.

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