Small and medium-sized enterprises (SMEs), many of which operate as suppliers in global production networks (GPN), often times lack behind large enterprises in terms of Industry 4.0 implementation. For this reason, scientific contributions recommend SMEs to approach Industry 4.0 through pilot projects in which individual Industry 4.0 use cases are developed and implemented. Hence, to allow for a targeted development and implementation of Industry 4.0 use cases for SMEs in GPN, this paper proposes a five-step process model that seeks to make use of Industry 4.0 potentials in terms of increased product qualities and logistics performances within such networks. In contrast to existing process models, this paper follows a holistic approach that initially focuses on the identification of potential problems that impede increased product qualities and logistics performances. Building upon these problems, potential Industry 4.0 solutions are derived and transferred into use cases using a structured idea generation and selection process. After the successful implementation of the use case, the procedure is completed by the conversion of the use case into a showcase that might serve as a lighthouse project illustrating the potentials of Industry 4.0 for other production network partners. For testing its practicability, the procedure is exemplarily applied to the GPN of an automotive supplier.

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Driven by an increasing demand for individualized products and shorter product life-cycles, companies continuously extend their product portfolio. Simultaneously, companies expand into new markets to reach customers and to exploit varying location factors to reduce costs. Global production networks (GPNs) have to be adapted constantly to react to new circumstances and changes in the demand of products. To remain competitive, product allocation and production network configuration are essential. At the same time, companies face an increasing complexity while handling these tasks. This poses a challenge particularly for small and medium sized companies, which have limited planning capacities and management resources. Current literature describes optimization-based approaches for the integrated product allocation and network configuration of production networks. Yet, multi-objective models lack transparency of results and user friendliness. Therefore, this paper presents a multi-objective optimization model that incorporates flexibility and reconfiguration aspects to determine an optimal product allocation and network configuration of a GPN over a given planning horizon. The preemptive goal programming approach is used to identify Pareto-optimal solutions and to increase user friendliness. The subsequent verification, validation and post-optimality analysis combined in a structured process enables a wide range of companies to apply the approach. The model is successfully applied in the GPN of a special machine manufacturer, which produces high precision metrology machines. Due to its transparent approach for complex planning problems, the developed method provides a solid base for well-founded, objective decisions. Hence, the risk of costly errors in the planning phase is reduced.

The trend of globalization has led to a structural change in the sales and procurement markets of manufacturing companies in recent decades. In order not to be left behind by this change, companies have internationalized their production structures. Global production networks with diverse supply and service interdependencies are the result. However, the management of global production networks is highly complex. Key performance indicator (KPI) networks already exist at the corporate level and site level to support the management of complex systems. However, such KPI networks are not yet available to support the management of entire production networks. In this article, a KPI network for global production networks is presented, which links the key figures of the site level and the corporate level. By integrating both levels into a comprehensive KPI network, cause and effect relationship between the production-related KPIs and the strategic KPIs of a corporate strategy become transparent. To this end, this KPI network is integrated into a Performance Measurement and Management (PMM) methodology. This methodology consists of three phases: performance planning, performance improvement, and performance review. For testing the practical suitability, the PMM methodology is applied to the production network of an automotive supplier using a simulation model to estimate the effects of proposed improvement actions of the methodology.

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