A Fixture Design Retrieving Method Based on Constrained Maximum Common Subgraph

Fixtures are widely used in almost any modern manufacturing. They add directly to the cost base, impact manufacturing firms' responsiveness and contribute to the overall product quality. Computer-aided intelligent fixture design was developed over the years to give a competitive edge to the manufacturing firms who are facing unprecedented competition and challenges. Among the techniques, case-based reasoning (CBR) method leverages previous design experience and emerged as one of the most popular methods. However, existing CBR methods are more focused on frame work building and less on detailed techniques on case retrieving, which is the central part of any CBR methods. This would inevitably impose negative impact on the overall efficiency of any CBR-based methods. In light of this, this paper presents a new case retrieving method based on a constrained common subgraph technique. This technique tracks down similar cases from a case library through comparing the maximal common subgraphs constrained by meeting fixturing functional requirement. Efficient and robust algorithms have been developed subsequently to implement this technique. The developed method can be highly effective for retrieving cases related to some manufacturing parts with complex geometry. An illustrative example, combined with other key fixture design factors, demonstrates the effectiveness of the proposed method. The presented method is intuitive and can be used in combination with existing CBR methods and well positioned for the upcoming “big data” manufacturing.