Process Selection Using Variation and Cost Relations

Variations are inherent in all manufacturing processes and can significantly affect the quality of a final assembly, particularly in multistage assembly systems. Existing research in variation management has primarily focused on incorporating GD&T factors into variation propagation models in order to predict product quality and allocate tolerances. However, process induced variation, which has a key influence on process planning, has not been fully studied. Furthermore, the link between variation and cost has not been well established, in particular the effect that assembly process selection has on the final quality and cost of a product. To overcome these barriers, this paper proposes a novel method utilizing process capabilities to establish the relationship between variation and cost. The methodology is discussed using a real industrial case study. The benefits include determining the optimum configuration of an assembly system and facilitating rapid introduction of novel assembly techniques to achieve a competitive edge.

[1]  Jian Liu,et al.  Process-oriented tolerancing using the extended stream of variation model , 2013, Comput. Ind..

[2]  Yan Jin,et al.  Shimless Aerospace Assembly , 2015 .

[3]  Jianjun Shi,et al.  Stream of Variation Modeling and Diagnosis of Multi-Station Machining Processes , 2000, Manufacturing Engineering.

[4]  Richard Curran,et al.  Review of Aerospace Engineering Cost Modelling: The Genetic Causal Approach , 2004 .

[5]  Jian Mao,et al.  Tolerance Optimization Design Based on the Manufacturing-costs of Assembly Quality☆ , 2015 .

[6]  Yoram Koren,et al.  Stream-of-Variation Theory for Automotive Body Assembly , 1997 .

[7]  Jun Ni,et al.  Dimensional Errors of Fixtures, Locating and Measurement Datum Features in the Stream of Variation Modeling in Machining , 2003 .

[8]  Jean-Yves Dantan,et al.  Cost Estimation Method for Variation Management , 2013 .

[9]  Jean-Yves Dantan,et al.  Variation management by functional tolerance allocation and manufacturing process selection , 2008 .

[10]  Qiang Zhou,et al.  Integrating GD&T into dimensional variation models for multistage machining processes , 2010 .

[11]  Yan Jin,et al.  Intelligent Assembly Time Analysis Using a Digital Knowledge-Based Approach , 2009, J. Aerosp. Comput. Inf. Commun..

[12]  Zhenyu Kong,et al.  Variation Propagation Analysis for Multistation Assembly Process With Consideration of GD&T Factors , 2009 .

[13]  Abhishek Das,et al.  Design synthesis methodology for dimensional management of assembly process with compliant non-ideal parts , 2014 .

[14]  Michael McDonald,et al.  Fundamentals of Modern Manufacturing: Materials, Processes and Systems , 2016 .