Purpose – In micro cold forming, the high degree of technological dependencies between manufacturing, quality inspection and handling technologies leads to an extremely complex planning of process chains. In addition, the lack of standardised processes and interfaces further complicates the planning. The paper aims to discuss these issues. Design/methodology/approach – In order to provide consistent and comprehensive planning of micro manufacturing processes, this paper discusses a method, which integrates the planning of process flows, the planning of technological dependencies and capabilities, as well as of the corresponding material flow. Findings – The paper presents the micro-process chain planning and analysis (μ-ProPlAn) framework. It consists of a specific modelling method, a simultaneous engineering procedure model for the model creation, as well as of methods for the analysis of technological dependencies and logistic key values along the modelled process chains. Research limitations/implications – As the results presented in this paper originate from an on-going research project, the paper focuses on a detailed presentation of the modelling methodology and the procedure model. Practical implications – In practice, the μ-ProPlAn framework provides process designers in the field of micro manufacturing with tools and methods to clearly depict the interdependencies between and within a product's different manufacturing stages. Originality/value – By following a simultaneous engineering approach, μ-ProPlAn aims to reduce the efforts in process design by supporting the design of manufacturing processes in the early stages of the product design and by providing suitable methods for the analysis of these process chains.

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Over the last decades, supplier development has become an increasingly important concept to remain competitive in today’s markets. Therefore, manufacturers invest resources in their suppliers to increase their abilities and, ultimately, to reduce their product prices. Thereby, most approaches found in the literature focus on long-term supplier development programs. Nevertheless, today’s volatile and dynamic markets require flexible approaches to deal with this complexity. We apply Model Predictive Control to optimize the number of supplier development projects in order to achieve flexibility while maintaining a certain level of security for all parties. Thereby, the article focusses on a multimanufacturer scenario, where two manufacturers aim to develop the same supplier. These manufacturers can establish different levels of horizontal collaboration. While previous results already show the benefits of applying this approach to a static scenario, this article extends this formulation by introducing market dynamics in the numerical simulations as well as into the optimization approach. Thus, the article proposes to derive regression models using real-world data. The article evaluates the effects of real-world market dynamics on two use cases: an automotive use case and a use case from the mobile phone sector. The results show that assuming market dynamics during the optimization leads to increased or at least close-to-equal revenues across the involved partners. The average increase ranges from approximately 1% to 5% depending on the type and magnitude of the dynamics. Thereby, the results differ depending on the selected collaboration scheme. While a full-cooperative collaboration scheme benefits the least from regarding dynamics in the optimization, it results in the highest overall revenue across all partners.

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