Case based reasoning method for computer aided welding fixture design
Introduction
“Welding is essential to a high dollar volume of manufacturing processes, including national defense industries. The contribution of welding to the U.S. economy in 1999 via these industries was no less than $7.85 billion. This figure represented 7% of total expenditures by these firms in 1999 [1], [2].” Widely used in the welding sector, fixtures have a direct impact upon welding quality, productivity and cost. Generally, the costs associated with fixture design and manufacture can account for 10%–20% of the total cost of a manufacturing system [3].
Traditionally, fixture design often heavily relies on fixture design engineers’ experience/knowledge and it usually requires over 10 years manufacturing practice to design quality fixtures. Furthermore, it is also a tedious and time-consuming task [4]. An experienced fixture designer may get tired of the routine grind of daily work and its low efficiency, while a new fixture engineer has to accumulate years of experience before mastering the fixture design expertise. Although abundant technical knowledge and many good design cases in manufacturing companies are readily available, and computer aided design and manufacturing technologies (CAD/CAM) have become sufficiently advanced, related applications in welding fixture design are very limited. Therefore, there is good potential for developing advanced fixture design methods that can generate significant benefits, including cost reduction.
Currently, most of reported research has been mainly focused on machining fixture, and the applications of computer aided fixture design (CAFD) technology are still very limited in the welding sector. One key reason is the lack of an effective method that can utilize massive welding-related production data, existing fixture solutions and fixture design experience that is available in a lot of manufacturing companies.
The remainder of this paper is organized as follow: Section 2 provides a discussion on current fixture design research. Section 3 presents a detailed description of our cased-based welding fixture design research. Firstly, the information representation method is given, which uses a multi-level data abstraction mechanism as its core. This representation method offers an opportunity to objectify a welding fixture design solution as an organized object relationship model. Then, based on the information representation method, a case-based reasoning (CBR) method for welding fixture design, with a hybrid mode of 3-level CBRs and designer–machine interaction, is provided. Finally, a case is presented to illustrate the process of our proposed CBRs method.
Section snippets
Literature review
Fixtures are designed to position and hold one or more workpiece(s) within some specifications. Generally, there are four main stages within a fixture design process — setup planning, fixture planning, fixture unit design and verification, as Fig. 1 illustrates [5], [6]. Setup planning determines the number of setups required to perform all the manufacturing processes, the task for each setup, e.g., the ongoing manufacturing process and workpiece, orientation and position of the workpiece in
Background and objective of our work
Over the last decade, the research group led by Professor Kevin Rong has devoted a great deal of the effort to fixture design research and promoting relevant applications for industrial practice. Our initial goal is to develop a theory and method for general fixture design in industrial applications. In recent years, we have had the opportunity to cooperate with several industrial partners to systemize and test our theory and method in the welding field.
Generally, welding fixture design of
Conclusions
Case based design method has significant technical and commercial advantages in industrial fixture design applications. Breakthroughs on design solution representation (information modeling) and integration of case-based reasoning (CBR) into computer aided fixture design could lead to a revolutionary progress in traditional fixture design. By studying the achievements in fixture design research over the past years, we propose this CBR based method that can pave a clear way to more in-depth and
Acknowledgments
We would like to thank Caterpillar Inc., for excellent cooperation on the development project of computer aided fixture design system. Our special thanks to Dr. David Yang of Caterpillar Inc., for his active participation and support. The authors also acknowledge the support of the research from Bluco Corporation and Shanghai University in China. We appreciate the constructive comments from all reviewers. Their suggestions are crucial for us to improve the quality of this paper.
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