Abstract

Integrating multiple sensors into manufacturing systems enables adaptive and flexible automation and increases process adaptivity and quality control. The design of an optimum configuration must be based on a systematic analysis relative to operational and economic considerations. This design should include an evaluation of sensor performance, a decision on how many sensors, of which type they should be, and where to locate them, modes of sensor interaction, and the influence on overall performance based on a cost/benefit analysis. In most real-world applications it is impossible to develop an accurate model to predict sensor performance and therefore, performance must be derived empirically but in a systematic manner. This paper presents research and development of integrated sensor economy principles and selection procedures in addition to a performance assessment model. A systems engineering approach is applied for empirical investigations for assessment of alternative guidance systems. The outcome of this research is a set of general design guidelines for integrating multiple sensors into robotic manufacturing systems.

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