Transparency in Global Production Networks: Improving Disruption Management by Increased Information Exchange
Final Report Abstract
Today, global production networks are characterised by a lack of information exchange, especially between several companies. Due to this lack of transparency, information about disruptions often reaches the affected companies late and they can only react with delay. This in turn leads to service failures and ultimately to reduced competitiveness. In the course of digitalisation, the rapid exchange of information has become much easier. For example, order-related data can be exchanged automatically via EDI and integrated into operational systems. However, these possibilities are not widely used due to the associated implementation costs and lack of clarity regarding the advantages. In the present research project, a procedure was therefore developed for the simulation-based determination of interference-resistant target states of the information exchange. The generic procedure considers order management, quality problem solving and technical change management. With the procedure, manufacturing companies can determine, depending on their strategic orientation, which design of the information exchange makes the most sense for them. To develop it, production systems and their performance, disruptions and business processes of disruption management and degrees of information exchange were first recorded and modelled in the form of formal description models. These were then implemented and validated in modules for agentbased and discrete-event simulation. Subsequently, an experimental framework was developed that uses meta-models trained on the basis of the simulation model to determine cause-effect relationships between disturbances, information exchange settings and performance indicators of the production network. Subsequently, the meta-models were used within a multi-criteria optimisation to determine target states of the information exchange, considering the risk affinity of the decision-makers. Finally, concrete measures for increasing information exchange and a procedure for prioritising these measures were derived based on the company's production strategy. The procedure was tested in an exemplary case study of industrial practice. With this procedure, manufacturing companies can increase the exchange of information in their production networks in a targeted manner and thus improve their competitiveness. It could be shown that simulation-based optimisation is suitable for improvements in the fault management of manufacturing companies. Subsequent research work could expand the developed procedure to include direct linking with individual machines to create so-called digital twins and adapt it for use in the circular economy.
Publications
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A Framework for Digital Twins for Production Network Management. Procedia CIRP, 104, 1269-1274.
Benfer, Martin; Peukert, Sina & Lanza, Gisela
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Resilience Measures in Global Production Networks: A Literature Review and Conceptual Framework. Die Unternehmung, 75(4), 491-520.
Benfer, Martin; Verhaelen, Bastian; Peukert, Sina & Lanza, Gisela
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Robust optimization of information flows in global production networks using multi-method simulation and surrogate modelling. CIRP Journal of Manufacturing Science and Technology, 32, 491-506.
Treber, Stefan; Benfer, Martin; Häfner, Benjamin; Wang, Lihui & Lanza, Gisela
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Product allocation and network configuration in global production networks. Production Engineering, 17(1), 117-132.
Klenk, Felix; Kerndl, Felix; Heidinger, Felix; Benfer, Martin; Peukert, Sina & Lanza, Gisela
