Genetic algorithms applied to optimal tolerance levels of multiattribute inspection errors

In modern manufacturing environment, inspection equipment often can deal with more than one quality characteristic simultaneously. At the design stage of such inspection equipment, it is necessary to identify optimal combination of inspection error tolerance levels of multiattributes. We suggest a genetic algorithm by which one can determine the optimal tolerance levels of errors for multiinspection attributes at a minimum cost of ownership (COO). The COO model is formulated as a function of not only the initial purchase cost but also the inspection cost over lifetime. Our approach is expected to effectively contribute to marketing as well as manufacturing of inspection equipment.