A Framework for Digital Twins for Production Network Management

The dynamic and highly complex task of production network management requires decision support through quantitative models. In the industrial praxis, these models are specifically designed and implemented for particular management decisions, requiring significant one-time effort for model creation. This contribution utilizes the digital twin concept to facilitate production network models that are continuously synchronized with the examined production network to support several different management decisions. The approach structures data from existing information systems as a synchronized generic base model, which is used to create problem-specific executable models, thereby saving costs through repeated model use and quicker decision making

Potentials of Traceability Systems - A Cross-Industry Perspective

Recently, traceability systems have become more common, but their prevalence and design vary significantly depending on the industry. Different law and customer-based requirements for traceability systems have led to diverse standards. This contribution offers a framework to compare the state of traceability systems in different industries. A comparison of industry characteristics, motivations for traceability system implementation, common data management, and identification systems are offered. Upon that analysis, the potential of cross-industry traceability systems and approaches is identified. This extended usage of traceability systems supports the quality assurance, process management and counterfeit protection and thus expands customer value

Selection of traceability-based, automated decision-making methods in global production networks

Automating traceability-based decision-making can shorten the reaction time to supply chain disruptions. This paper develops a framework for choosing automated decision-making (ADM) methods based on traceability data. It contains a toolbox comprising methods suitable for ADM, respective selection criteria and a new process to select a suitable ADM method based on companies’ requirements. This process is based on an evaluation matrix matching methods and criteria. As a result, the ADM framework suggests the most suitable method to automate a specifically chosen decision. The developed framework is validated in the supply chain of a globally operating truck manufacturer

Product allocation and network configuration in global production networks – An integrated optimization approach

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

A Circular Economy Strategy Selection Approach: Component-based Strategy Assignment using the Example of Electric Motors

The sustainability of industrial processes and products is a core issue of our time. There are several approaches to move from a linear, inherently wasteful economic principle to a circular economy focused on conserving products, resources, and energy. However, selecting which of the circular economy strategies ranging from reuse, repurpose, and remanufacture to recycling is crucial to ensure the economic viability of the product. This contribution proposes an iterative, component-based circular economy strategy selection method that supports product and production planners in choosing the appropriate circular economy strategy. For this approach, the suitability of each component for circular economy strategies is assessed based on identified key properties. In case of no fitting strategy, further component decomposition is devised, and the process is repeated. To further support the design of circular economy strategies, a modular process build set is suggested, enabling the swift composition of the processing sequence. The approach is then applied to the example of an electric motor of a battery electric vehicle. The presented approach allows a quick first assessment of the viability of different circular economy strategies and helps product and production engineers develop product-specific circular economy strategies

A Circular Economy Strategy Selection Approach: Component-based Strategy Assignment using the Example of Electric Motors

The sustainability of industrial processes and products is a core issue of our time. There are several approaches to move from a linear, inherently wasteful economic principle to a circular economy focused on conserving products, resources, and energy. However, selecting which of the circular economy strategies ranging from reuse, repurpose, and remanufacture to recycling is crucial to ensure the economic viability of the product. This contribution proposes an iterative, component-based circular economy strategy selection method that supports product and production planners in choosing the appropriate circular economy strategy. For this approach, the suitability of each component for circular economy strategies is assessed based on identified key properties. In case of no fitting strategy, further component decomposition is devised, and the process is repeated. To further support the design of circular economy strategies, a modular process build set is suggested, enabling the swift composition of the processing sequence. The approach is then applied to the example of an electric motor of a battery electric vehicle. The presented approach allows a quick first assessment of the viability of different circular economy strategies and helps product and production engineers develop product-specific circular economy strategies