Browsing by Author "Dietz, Thomas"

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    Knowledge-based cost-benefit analysis of robotics for SME-like manufacturing
    (Stuttgart : Fraunhofer Verlag, 2019) Dietz, Thomas; Verl, Alexander (Prof. Dr.-Ing. Dr. h.c. mult.)
    Robot systems promise high potential for improvement of production processes in small and medium-sized enterprises (SME). Often, reliable data for the assessment of costs and benefits of robot systems is missing, because they are special machinery and because the required information is distributed among component manufacturer, system integrator and end-user. The problem of cost-benefit assessment of industrial robot systems in the face of uncertain and incomplete information is of high relevance for unlocking the potential of robotics in SME-like production environments. In order to solve this problem, methods from business economics and from knowledge management in robotics are combined in a cost-benefit model for robot systems. This cost-benefit model builds on the established PPR-approach, which separates the concerns of product, process and resources. The PPR-approach is expanded with specific cost-relevant aspects. Domain specific costing models, borrowing from activity-based costing (ABC), for product, process, resources and cost information are proposed. These models and the meta-information required for their usage are collected in a knowledge base. The input for the cost-benefit assessment is a description of the current planning status in AutomationML. This information is matched to the information in the knowledge base through reasoning. This allows to automatically build an overall cost-benefit model for the robot system. Missing or inaccurate information causes uncertainties. These uncertainties are modeled using interval arithmetics. The overall cost-benefit model is able to process interval numbers and hence to compute on the uncertain information. The interval representation offers an intuitive description of uncertainties in costs and benefits. An amortization graph allows to intuitively represent the results of the cost-benefit assessment for the entire life-cycle. A test implementation of the cost-benefit assessment method allows an evaluation of its results for two realistic use cases. The resulting costs, benefits, and project planning are plausible and in agreement with real experience. Concluding, the cost-benefit assessment method has high potential to improve decision making in the development of robot systems.