Multivariate tolerance design using quality loss

Moskowitz, Herbert; Plante, Robert; Duffy, Jeff

doi:10.1080/07408170108936843

Cited by 25 publications

(18 citation statements)

References 11 publications

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“…The assessment of tolerance allocation plays a vital role in product/process design. In this paper [5] they proposed both Parametric and nonparametric procedures that determine tolerance allocations. The parametric method determines tolerances that minimize the expected total loss, where loss consists of both internal (supplier processes) and external (loss to society) costs.…”

Section: Literature Reviewmentioning

confidence: 99%

Simultaneous Optimization of Design Tolerance and Total Cost for a Piston and Cylinder Assembly

Kumar

Alagumurthy

Ramesh

2009

2009 International Conference on Advances in Recent Technologies in Communication and Computing

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Rapid changes in the market place have led designers and manufacturers to continuously develop new products to satisfy the demands of more exigent customers. Therefore, to be competitive, designers and manufacturers have to perform those steps accurately to ensure final Product quality and manufacturing cost. So Product quality and manufacturing cost have a significant impact on Tolerance. A more scientific approach is often desirable for better performance to overcome this Tolerance problem. In this paper, Design and machining tolerances have been allocated based on optimum total machining cost. New global nonlinear optimization techniques called Pattern Search algorithm and Genetic algorithm have been implemented to find the optimal tolerance allocation and total cost. Finally with respect to total cost both the methods have been compared.

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Section: Literature Reviewmentioning

confidence: 99%

Simultaneous Optimization of Design Tolerance and Total Cost for a Piston and Cylinder Assembly

Kumar

Alagumurthy

Ramesh

2009

2009 International Conference on Advances in Recent Technologies in Communication and Computing

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“…They presented optimization models for the first-order and second-order empirical loss functions. Moskowitz et al 18 and Plante 19 conducted parametric and non-parametric studies for allocating the tolerances on design parameters affecting a response.…”

Section: Literature Reviewmentioning

confidence: 99%

Integrating the LambertW Function to a Tolerance Optimization Problem

Shin¹,

Govindaluri²,

Cho³

2005

Qual. Reliab. Engng. Int.

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This paper explores the integration of the Lambert W function to a tolerance optimization problem with the assessment of costs incurred by both the customer and a manufacturer. By trading off manufacturing and rejection costs, and a quality loss, this paper shows how the Lambert W function, widely used in physics, can be efficiently applied to the tolerance optimization problem, which may be the first attempt in the literature related to tolerance optimization and synthesis. Using the concept of the Lambert W function, a closed-form solution is derived, which may serve as a means for quality practitioners to make a quick decision on their optimal tolerance without resorting to rigorous optimization procedures using numerical methods. A numerical example is illustrated and a sensitivity analysis is performed.

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“…Shin et al (2005) integrated the Lambert W function into the tolerance optimisation problem; a closed-form solution was derived efficiently by a computer program. Moskowitz et al (2001) and Plante (2002) conducted parametric and non-parametric studies in multivariate design cases. For cases in which quality characteristics are non-normal, Kapur and Wang (1987), Kapur and Cho (1994), and Cho and Phillips (1998) investigated tolerance optimisation problems using lognormal distribution, Weibull, and gamma distributions, respectively.…”

Section: Literature Reviewmentioning

confidence: 99%

Economic tolerance design for folded normal data

Liao

2009

International Journal of Production Research

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An important issue for design engineers is how to assign tolerance limits economically. Most work related to tolerance design is for nominal-is-best (N-type) quality characteristics and restricted by a normality assumption. However, smaller-is-better (S-type) quality characteristics and larger-is-better (L-type) quality characteristics are common in real applications. The practical distributions for S-type data or L-type data are typically skewed, and the normality assumption is violated. Determining tolerance with non-normal data using methodologies based on a normality assumption is not appropriate. This study considers the case in which measurements are recorded without their algebraic signs. The folded normal distribution works well to fit these absolute data. Based on the statistical properties of the folded normal distribution, this study develops an economic model encompassing quality loss, manufacturing costs, and re-work costs to determine tolerances. By minimising total costs, a procedure based on the Newton-Raphson method is utilised to obtain the optimal solution. Finally, a welding machine experiment is carried out to demonstrate the applicability of the proposed model.

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Multivariate tolerance design using quality loss

Cited by 25 publications

References 11 publications

Simultaneous Optimization of Design Tolerance and Total Cost for a Piston and Cylinder Assembly

Simultaneous Optimization of Design Tolerance and Total Cost for a Piston and Cylinder Assembly

Integrating the LambertW Function to a Tolerance Optimization Problem

Economic tolerance design for folded normal data

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