Tolerance control in the machining of discrete components

Mittal, Ravi O.; Irani, Shahrukh A.; Lehtihet, E. Amine

doi:10.1016/0278-6125(90)90054-l

Cited by 27 publications

(4 citation statements)

References 10 publications

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“…The beta distribution and the lognormal distribution are better choices than other kinds of statistical distributions. Nevertheless, the inefficient computation performance is a serious disadvantage of the beta distribution (Mittal et al, 1990). Therefore, the lognormal distribution is used in this study.…”

Section: Discussionmentioning

confidence: 99%

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

Huang

Shiau

2009

Assembly Automation

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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.

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Section: Discussionmentioning

confidence: 99%

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

Huang

Shiau

2009

Assembly Automation

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“…Chart in design can be called design tolerance chart (DTC), and chart in process planning can be called process tolerance chart (PTC). The latter has been covered in various literature since the 1950s (Gadzala 1959, Wade 1967, Nicks 1982, Wade 1983, Curtis 1988, Ahluwalia and Karolin 1986, Fainguelernt et al 1986, Irani et al 1989, Whybrew et al 1990, Mittal et al 1990, Abdou et al 1993, Ji 1993, 1995, Ngoi et al 1993, 1994, Britton et al 1997, Krag 1997. Those references, from US sources as well as from outside USA, are not a complete list; but they are the major ones in the subject area.…”

Section: Process Tolerance Chartsmentioning

confidence: 98%

Automatic generation of min/max tolerance charts for tolerance analysis from CAD models

Shen¹,

Shah

Davidson

2008

International Journal of Computer Integrated Manufacturing

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The so-called min/max tolerance charts are popular for analysing tolerance accumulation in parts and assemblies, despite the fact that this method is limited to one-dimensional worst-case analysis. Since different chart construction rules apply to different tolerance classes, the user has to remember all the different rules to construct a valid tolerance chart. Constructing the charts manually, as is common practice in industry today, is time-consuming and error-prone. This paper presents procedures for automating tolerance charting. It requires a computer aided design (CAD) model with GD&T specifications as input. The automation is based on a data model called the constraint-feature-tolerance (CTF) graph and machine interpretable representation of charting rules specific to each tolerance class. This paper also presents procedures for automatically extracting dimension and tolerance stacks for any user defined analysis dimension, and automatic part arrangement in assemblies corresponding to worst case analyses. Important implementation issues are also discussed and several case studies are presented, the results of which have been verified by manual chart construction.

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“…These tolerances are called manufacturing tolerances. Authors including Ahluwalia and Karolin (1984), Irani et al (1989), Mittal et al (1990), Ji (1993a, Ngoi and Teck (1993), Ngoi and Fang (1994), Ngoi and Tan (1995), Ngoi and Seow (1996), Jeang (1998), Ngoi and Ong (1999) and Li et al (2000) have researched this area considering different aspects with varying approaches.…”

Section: Introductionmentioning

confidence: 99%

Simultaneous optimal selection of design and manufacturing tolerances with different stack-up conditions using genetic algorithms

Singh

Jain

2003

International Journal of Production Research

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Tolerance control in the machining of discrete components

Cited by 27 publications

References 10 publications

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

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

Automatic generation of min/max tolerance charts for tolerance analysis from CAD models

Simultaneous optimal selection of design and manufacturing tolerances with different stack-up conditions using genetic algorithms

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