Abstract

The potential innovation and emerging workforce created by autonomous vehicle technologies, which have just entered the lean product development disciplines, play an important role in the development or change of the automotive manufacturing industry. Therefore, the intensity of work and the innovation practices brought by the technologies in question at each step of very different and interdisciplinary studies deeply affect the new and lean product development steps. Comparatively measuring the operating weight of new autonomous vehicle technologies in different company structures in these lean product development steps has important consequences for the development and change of the automotive industry under heavy global competition. On the other hand, it is difficult to measure the innovation input or the use of new autonomous technology under the AHP mathematical model of each part that constitutes the whole of the lean product development process, but it also creates the future predictions of the sector. The Analytical Hierarchy Process (AHP), which is one of the multi-purpose decision-making methods, was used to determine the most intense value creation, the design and development phase where there is innovation input, or the lean product development discipline throughout the whole process. The AHP method was preferred for the comparative analysis and synthesis of different applications or similar approaches in the automotive manufacturing industry companies (global and local) and lean product development processes in the field study of the research, under qualitative data. Under the AHP mathematical model created in the research, it was aimed to measure interdisciplinary clusters with a focus on new technology and to identify similarities or differences under alternative applications created by different company structures and to compare them systematically and evaluate them mathematically. In the study, the AHP mathematical model was used to compare lean product development processes and the use of new autonomous vehicle technologies, and the Expert Choice program was preferred in the application of the method.

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