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Through the use of recent technological advances, such as virtual- and augmented-reality validation techniques, many companies were able to reduce the number of physical prototypes used during their production planning process and thus improve their Time-To-Market. However, substituting physical prototypes in production planning comes at a cost, as validation results obtained from virtual- or augmented-reality techniques are not as reliable as those conventionally generated. Considering the fact that up to 85% of a product's life cycle costs are determined during product- and production planning [1] , [2] raises the question, at which point accelerating the planning process compromises its effectiveness and thus has a negative impact on the Life Cycle Costs. To answer this question, this paper discusses a novel approach to measure the success rate of non-physical prototype validation techniques and, using a Monte-Carlo Simulation, calculate a product's production-readiness. This contemplation allows an algorithm-based identification of part-specific validation activities that need to be carried out in order to ensure a satisfying degree of production-readiness while minimizing the number of physical prototypes needed. Our time-saving and effective approach has been implemented as a software-tool ( Simbaplan ® ) and put to use at a German Commercial Vehicle Manufacturer. Based on this use case, potentials and limitations of the approach are discussed and areas for future research are derived.

Ensuring Time-saving and Effective Production Planning by Prioritizing Activities based on Company-specific Validation Success Rates