Intuitionistic fuzzy manufacture knowledge-driven robust tolerance design

Motivated by fuzziness and uncertainty of manufacture factors in their expression, measurement and effects on the production cost, a methodology of intuitionistic fuzzy manufacture knowledge-driven robust tolerance design was developed systematically based on the intuitionistic fuzzy set and robust design theories. An intuitionistic fuzzy manufacture knowledge set was established according to such five aspects as the values of equipments, the machinabilities of product, the process features, the product features and the technical skills of worker. The constitution and level division of every knowledge subset was also discussed. A system of evaluating goals of manufacturing cost involving the target layer, the rule layer and the knowledge layer was developed, and an intuitionistic fuzzy comprehensive evaluation algorithm was used to calculate the manufacture cost factor φ. This method is more comply with the human logic compared with the traditional fuzzy evaluation. A fuzzy robust tolerance optimization model was established combining a cost-tolerance model with a proposed fuzzy quality loss function. Complying with the DFM concept, this methodology considers a comprehensive effect of various manufacturing factors on tolerance design. A case study on the tolerance optimization of certain aerospace fuel tank illustrates the feasibility, flexibility and robustness of the proposed approach.