Today’s industrial world is characterized by ever-shortening product development cycles and increasing degrees of product individualization which demand tools and enablers for accelerated prototyping. In addition, the existing uncertainty in the product development cycle should be reduced by involving stakeholders as early as possible. However, should an engineering change request (ECR) be necessary in the product development cycle, a fast iteration step into production is inevitable. The methodological description of such an ECR in the product development cycle is described in the previous chapter. Together with researchers from the Internet of Production (IoP), information from the product development process will be transferred to the digital shadow established in the IoP. The digital shadow collects information from all areas of the product lifecycle and provides it to the appropriate departments, adapted to the corresponding task. To tackle this challenge, a new type of product development process, the method of agile product development, is applied. Within the Enablers and Tools project, the development of various advanced manufacturing technologies (AMTs) for agile product development are at the forefront of the work. The enablers and tools are further developed with the principles of agile product development. They also serve to map the requirements for rapidly available and specific prototypes which are used to answer specific questions that arise during the product development cycle. To answer these questions, the concept of the Minimum Viable Product (MVP), an approach to reduce development time and increase customer satisfaction, is introduced and applied to all development tasks.
Although the numbers of sold additive manufacturing (AM) systems are growing rapidly year by year, the applications in series production are only quite a few. Part identification, which aims to identify suitable parts for AM, has turned out to be a difficult task. Because part identification has to consider various aspects such as the given cost structure, scope for redesign, and available data, different part identification methods have been developed. However, the optimal part identification method depends on the context in which it is applied. Therefore, this paper reviews the part identification methods that have been proposed thus far and the use cases in which part identification is applied and classifies them in a user-friendly way. This allows the user to select the right strategy for identifying suitable parts for AM based on the advantages and disadvantages of the approaches in respect to the use case and available resources. Further, the findings of the research conducted so far in the field of part identification are composed to assess how part identification can be improved by future research.
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