Abstract

Tolerance design is one of the key activities in the product creation process. It not only directly effects product quality but also has significant impact on manufacturing process and product cost. The tolerance design should never be overlooked in the product creation process. Though the importance of the tolerance design is well understood in the engineering community, a well established process for the tolerance design in the product creation process is still lacking. The practice of the tolerance design in most automotive industries is not consistent, and it largely depends on individual experience. Best practice and valuable knowledge is not captured in a systematic manner, and most often the new design does not benefit from best-in-class design knowledge. Most engineers can only go back to the very previous design for reference due to the lack of knowledge base tools. Therefore, optimal tolerance design could be missed. In addition, most tolerance design at earlier product lifecycle only concentrates on product functionality itself. Some serious manufacturing issues could be overlooked at the beginning and are only uncovered until it is too late. In addition to the delay of the product launch, the cost of fixing these manufacturing problems is often very expensive. Moreover, lack of a tool or process to look at system level tolerance interactions causes designers to miss optimal tolerance for each individual part design. In this paper, a tolerance design process is proposed in order to optimize product tolerance for function, manufacturing cost, and quality. This process will capture the knowledge of product tolerance design and optimize this knowledge to re-apply to every new product design. Also, with the help of feature-based design and knowledge-based technology, manufacturing process, cost, product quality, etc. could be considered at the earliest stage of the design cycle. Therefore, the quality and cost of design will be better understood and controlled compared to an ad hoc tolerance design process.

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