The major advantage of using selective assembly in manufacturing is that it allows the use of low precision parts to achieve high precision assembly. However, two problems arise: (a) the surplus parts due to unbalanced mating parts in some selective groups (b) there is no quantitative method to predict the matchable degree before assembly, and correspondingly no quantitative criterion on how to adjust manufacturing processes so that the desired match between mating parts could be guaranteed. By adopting the concepts of intersection and union from set theory and incorporating with the probability method, this paper develops a predictive model for quantitatively estimating the matchable degree between mating parts for selective assembly. Based on such a quantitative reference, together with the criterion for guaranteeing process capability index Cpk, an optimal algorithm for adjusting biases of dimensional distributions can be achieved to assure the matchable degree, thus improving the effectiveness of selective assembly.

1.
Arai
T.
,
1992
, “
A Simulation System on Assembly Accuracy
,”
Annals of the CIRP
, Vol.
41
, No.
1
, pp.
37
40
.
2.
Berzak, N., 1992, “Selective Robotic Assembly,” The 4th International Conference on Design Theory and Methodology, Scottsdale, AZ, ASME Design Engineering Division, Vol. 48, pp. 71–75.
3.
Boyer, D. E., and Nazemetz, J. W., 1985, “Introducing Statistical Selective Assembly—A Means of Producing High Precision Assemblies From Low Precision Components,” Annual International Industrial Engineering Conference, Institute of Industrial Engineers, pp. 562–570.
4.
Conway, H. G., 1962, Engineering Tolerances, Sir Isaac Pitman & Son Ltd, London, pp. 63–66.
5.
Desmond
D. J.
, and
Setty
,
1962
, “
Simplification of Selective Assembly
,”
Int. J. Prod. Res
, Vol.
1
, pp.
3
18
.
6.
English
J. R.
, and
Taylor
G. D.
,
1993
, “
Process Capability Analysis—a Robustness Study
,”
Int. J. Prod. Res
, Vol.
31
, No.
7
, pp.
1621
1635
.
7.
Fang
X. D.
, and
Zhang
Y.
,
1995
, “
A New Algorithm for Minimizing the Surplus Parts in Selective Assembly
,”
Computer & Industrial Engineering
, Vol.
28
, No.
2
, pp.
341
350
.
8.
Kalpakjian, S., 1992, Manufacturing Engineering and Technology, Addison-Wesley Publishing Company, Reading, MA, pp. 1258.
9.
Kulkarni, S. V., and Garg, T. K., 1985, “Optimal Allocation of Tolerances in Engineering Designs Governed by Systems of Simultaneous Tolerance Equations using Selective Assembly,” Journal of Inst. Eng. India, Part ME 5–65, pp. 160–168.
10.
Mansoor
E. M.
,
1961
, “
Selective Assembly—Its Analysis and Application
,”
Int. J. Prod. Res
, Vol.
1
, No.
1
, pp.
13
24
.
11.
Parrish, A., 1973, Mechanical Engineer’s Reference Book, Butterworths, London, pp. 3: 33–76.
12.
Pugh
G. A.
,
1986
, “
Partitioning for Selective Assembly
,”
Computer & Industrial Engineering
, Vol.
11
, No.
1
, pp.
175
179
.
13.
Pugh
G. A.
,
1992
, “
Selective Assembly with Components of Dissimilar Variance
,”
Computer & Industrial Engineering
, Vol.
23
, No.
4
, pp.
487
491
.
14.
Robinson
D. C.
, and
Mazharsolook
E.
,
1993
, “
Optimised Selective Assembly Using Model-based Quality Control
,”
Quality Forum
, Vol.
19
, No.
1
, pp.
20
25
.
15.
Wakefield, L. P., 1964, Dimensioning for Interchangeability, Pergamon Press LTD, pp. 209–211.
16.
Zehna, P. W., and Johnson, R. L., 1973, Elements of Set Theory, 2nd ed, Alley and Bacon, Boston, pp. 21–45.
17.
O̸yvind Bjo̸rke, 1989, Computer-Aided Tolerancing, ASME Press, New York, pp. 79–82.
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