An optimal tolerance allocation model for assemblies with consideration of manufacturing cost, quality loss and reliability index

Abstract

Purpose -The purpose of this paper is to provide an optimal tolerance allocation model for assemblies with consideration of the manufacturing cost, the quality loss, the design reliability index with various distributions to enhance existing models. Results of two case studies are presented. Design/methodology/approach -The paper develops a model with consideration of the manufacturing cost, the Taguchi's asymmetric quadratic quality loss and the design reliability index for the optimal tolerance allocation of assemblies. The dimensional variables in normal distributions are initially used as testing and compared with the data from the prior researches. Then, the dimensional variables in lognormal distributions with the mean shift and the correlation are applied and investigated. Findings -The results obtained based on a lognormal distribution and a normal distribution of the dimension are similar, but the tolerance with a lognormal distribution is little smaller than that with a normal distribution. The result of the reliability with the lognormal distribution obtained by the Monte-Carlo is higher than that with a normal distribution. This paper shows that effects of the mean shift, the correlation coefficient and the replacement cost on the cost are significant and designers should pay attention to them during the tolerance optimization. The optimum tolerances of components of a compressor are recommended.Research limitations/implications -The model is limited to the dimensions of components with the normal distribution and lognormal distributions. The implication should be enhanced with more data of dimension distributions and cost of assembly components. Practical implications -Two case studies are presented. One is an assembly of two pieces and another is a compressor with many components. Originality/value -This model provides an optimal tolerance allocation method for assemblies with the lowest manufacturing cost, the minimum quality loss, and the required reliability index for the normal distribution and lognormal distribution.

Research on assembly quality adaptive control system for complex mechanical products assembly process under uncertainty

“…Assembly quality optimization Liu et al [6] Assembly cost-tolerance model Cheng and Tsai [7] Cost-tolerance model Xiaoqing et al [8] Assembly process model, activity control model and quality data model Huang et al [9] Tolerance optimal allocation model by introducing the reliability index Assembly performance prediction Su et al [11,12] A novel defect-rate prediction model Liu et al [13] Maximum compatible constraint model Zhang et al [14] Relationship model with grey system theory based on determining reliability control points Xu et al [15] Predictive performances using the neural network time series models Hong et al [16] Generic mathematical model and state space model to predict and control the variation Hu et al [17] Assembly precision prediction for spacecraft Du et al [18] A stream of variation methodology developed and applied…”

“…In addition to considering the manufacturing cost and the quality loss, Huang and Shiau [9] improved the tolerance optimal allocation model by introducing the reliability index. To improve the assembly quality of product, Karmakar and Maiti [10] proposed the issues of tolerance synthesis, such as construction of design function, construction of the objective function, and selection of suitable optimization methods.…”

Transmission system accuracy optimum allocation for multiaxis machine tools’ scheme design

“…Maximum screw pitch cumulate error in the X-axis x 11 Á 4 (y) max Maximum screw pitch cumulate error in the Y-axis x 12 Á 4 (z) max Maximum screw pitch cumulate error in the Z-axis x 13 Á 5 () max Maximum worm gear pitch cumulate error in the C-axis x 14 Á 6 () max Maximum worm gear pair axis angle error in the C-axis x 15 Á 7 () max Maximum worm gear pair axis angle error in the C-axis x 16 Á 9max þ Á 10max Maximum squareness between the X-and Y-axes…”

“…Muthu et al 15 formulated the tolerance allocation problem as a nonlinear integer model by considering both the manufacturing cost of each component and the quality loss of assemblies, so as to minimize the manufacturing cost. An assembly tolerance allocation model was provided in consideration with the manufacturing cost and the quality loss, the design reliability index by Huang et al 16 Sivakumar et al 17 presented a general methodology using non-dominated sorting genetic algorithm (NSGA) and multiobjective particle swarm optimization for simultaneous optimal selection of design and manufacturing tolerances with alternative manufacturing process selection in part mechanical design. Shin et al 18 developed a sequential robust tolerance design method to determine the best factor settings and the closed-form solutions for the optimal specification limits.…”

Improving an Electrostatic Powder Coating Process via Signal to Noise Response Surface

“…The height of the braze normalized by the wire diameter is the least influential design parameter. Various Taguchi parameter designs and performance measures were applied on many engineering problems and brought proper levels of operating conditions and expenses (Kumar and Khamba, 2008;Jailani et al, 2009;Huang and Shiau, 2009).…”