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Research Papers

A Multistage Approach to the Selective Assembly of Components Without Dimensional Distribution Assumptions

[+] Author and Article Information
Abolfazl Rezaei Aderiani

Department of Industrial and Materials Science,
Chalmers University of Technology,
Gothenburg SE 41296, Sweden
e-mail: aderiani@chalmers.se

Kristina Wärmefjord

Department of Industrial and Materials Science,
Chalmers University of Technology,
Gothenburg SE 41296, Sweden
e-mail: kristina.warmefjord@chalmers.se

Rikard Söderberg

Department of Industrial and Materials Science,
Chalmers University of Technology,
Gothenburg SE 41296, Sweden
e-mail: rikard.soderberg@chalmers.se

1Corresponding author.

Manuscript received January 16, 2018; final manuscript received March 20, 2018; published online May 14, 2018. Editor: Y. Lawrence Yao.

J. Manuf. Sci. Eng 140(7), 071015 (May 14, 2018) (8 pages) Paper No: MANU-18-1034; doi: 10.1115/1.4039767 History: Received January 16, 2018; Revised March 20, 2018

Selective assembly is a means of obtaining higher quality product assemblies by using relatively low-quality components. Components are selected and classified according to their dimensions and then assembled. Past research has often focused on components that have normal dimensional distributions to try to find assemblies with minimal variation and surplus parts. This paper presents a multistage approach to selective assembly for all distributions of components and with no surplus, thus offering less variation compared to similar approaches. The problem is divided into different stages and a genetic algorithm (GA) is used to find the best combination of groups of parts in each stage. This approach is applied to two available cases from the literature. The results show improvement of up to 20% in variation compared to past approaches.

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References

Söderberg, R. , Wärmefjord, K. , Carlson, J. S. , and Lindkvist, L. , 2017, “ Toward a Digital Twin for Real-Time Geometry Assurance in Individualized Production,” CIRP Ann., 66(1), pp. 137–140. [CrossRef]
Wang, Y. , Shi, J. , Lu, S. , and Wang, Y. , 2016, “ Selective Laser Melting of Graphene-Reinforced Inconel 718 Superalloy: Evaluation of Microstructure and Tensile Performance,” ASME J. Manuf. Sci. Eng., 139(4), p. 041005. [CrossRef]
Gu, D. , Dai, D. , Chen, W. , and Chen, H. , 2016, “ Selective Laser Melting Additive Manufacturing of Hard-to-Process Tungsten-Based Alloy Parts With Novel Crystalline Growth Morphology and Enhanced Performance,” ASME J. Manuf. Sci. Eng., 138(8), p. 081003. [CrossRef]
Mansor, E. , 1961, “ Selective Assembly—Its Analysis and Applications,” Int. J. Prod. Res., 1(1), pp. 13–24. [CrossRef]
Desmond, D. , and Setty, C. , 1962, “ Simplification of Selective Assembly,” Int. J. Prod. Res., 1(3), pp. 3–18. [CrossRef]
Pugh, G. A. , 1992, “ Selective Assembly With Components of Dissimilar Variance,” Comput. Ind. Eng., 23(1–4), pp. 487–491. [CrossRef]
Fang, X. , and Zhang, Y. , 1995, “ A New Algorithm for Minimizing the Surplus Parts in Selective Assembly,” Comput. Ind. Eng., 28(2), pp. 341–350. [CrossRef]
Fang, X. , and Zhang, Y. , 1996, “ Assuring the Matchable Degree in Selective Assembly Via a Predictive Model Based on Set Theory and Probability Method,” ASME J. Manuf. Sci. Eng., 118(2), pp. 252–258. [CrossRef]
Chan, K. , and Linn, R. , 1999, “ A Grouping Method for Selective Assembly of Parts of Dissimilar Distributions,” J. Qual. Eng., 11(2), pp. 221–234. [CrossRef]
Mease, D. N. , Vijayan, N. , and Sudjivnto, A. , 2004, “ Selective Assembly in Manufacturing: Statistical Issues and Optimal Binning Strategies,” Technometrics, 46(2), pp. 165–175. [CrossRef]
Mohammed, A. , Schmidt, B. , and Wang, L. , 2016, “ Energy-Efficient Robot Configuration for Assembly,” ASME J. Manuf. Sci. Eng., 139(5), p. 051007. [CrossRef]
Farzad, H. , and Ebrahimi, R. , 2016, “ Die Profile Optimization of Rectangular Cross Section Extrusion in Plane Strain Condition Using Upper Bound Analysis Method and Simulated Annealing Algorithm,” ASME J. Manuf. Sci. Eng., 139(2), p. 021006. [CrossRef]
Xing, Y. , 2017, “ Fixture Layout Design of Sheet Metal Parts Based on Global Optimization Algorithms,” ASME J. Manuf. Sci. Eng., 139(10), p. 101004. [CrossRef]
Aboutaleb, A. M. , Tschopp, M. A. , Rao, P. K. , and Bian, L. , 2017, “ Multi-Objective Accelerated Process Optimization of Part Geometric Accuracy in Additive Manufacturing,” ASME J. Manuf. Sci. Eng., 139(10), p. 101001. [CrossRef]
Brika, S. E. , Zhao, Y. F. , Brochu, M. , and Mezzetta, J. , 2017, “ Multi-Objective Build Orientation Optimization for Powder Bed Fusion by Laser,” ASME J. Manuf. Sci. Eng., 139(11), p. 111011. [CrossRef]
Ponnambalam, S. , Sankar, S. S. , Sriram, S. , and Gurumarimuthu, M. , 2006, “ Parallel Populations Genetic Algorithm for Minimizing Assembly Variation in Selective Assembly,” International Conference on Automation Science and Engineering (CASE), Shanghai, China, Oct. 8–10, pp. 496–500.
Kumar, M. , Kannan, S. , and Jayabalan, V. , 2007, “ A New Algorithm for Minimizing Surplus Parts in Selective Assembly by Using Genetic Algorithm,” Int. J. Prod. Res., 45(20), pp. 4793–4822. [CrossRef]
Asha, A. , Kannan, S. , and Jayabalan, V. , 2008, “ Optimization of Clearance Variation in Selective Assembly for Components With Multiple Characteristics,” Int. J. Adv. Manuf. Technol., 38(9–10), pp. 1026–1044. [CrossRef]
Kannan, S. , Asha, A. , and Jayabalan, V. , 2005, “ A New Method in Selective Assembly to Minimize Clearance Variation for a Radial Assembly Using Genetic Algorithm,” J. Qual. Eng., 17(4), pp. 595–607. [CrossRef]
Kumar, M. , Sivasubramanian, R. , and Jayabalan, V. , 2009, “ Particle Swarm Optimization for Minimizing Assembly Variation in Selective Assembly,” Int. J. Adv. Manuf. Technol., 42(7–8), pp. 793–803. [CrossRef]
Kumar, M. , Sivasubramanian, R. , and Jayabalan, V. , 2009, “ A New Method in Selective Assembly for Components With Skewed Distributions,” Int. J. Prod. Qual. Manage., 4, pp. 569–589. http://www.inderscience.com/offer.php?id=25186
Wang, W. , and Li , D., and Chen, J. , 2009, “ Minimizing Assembly Variation in Selective Assembly for Complex Assemblies Using Genetic Algorithm,” Second International Conference of Mechanic Automation and Control Engineering (MACE), Hohhot, China, July 15–17, pp. 1401–1406.
Raj, M. V. , Sankar, S. S. , and Ponnambalam, S. G. , 2011, “ Genetic Algorithm to Optimize Manufacturing System Efficiency in Batch Selective Assembly,” Int. J. Adv. Manuf. Technol., 57(5–8), pp. 795–810. [CrossRef]
Xu, H. Y. , Kuo, S. H. , and Tsai, J. W. H. , 2014, “ A Selective Assembly Strategy to Improve the Components Utilization Rate With an Application to Hard Disk Drives,” Int. J. Adv. Manuf. Technol., 75(1–4), pp. 247–255. [CrossRef]
Bäck, T. , 1996, Evolutionary Algorithms in Theory and Practice, Oxford University Press, New York.

Figures

Grahic Jump Location
Fig. 1

Grouping of parts based on their dimensions

Grahic Jump Location
Fig. 3

Linear assembly of sample case 2

Grahic Jump Location
Fig. 4

Flow chart of the presented methodology

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