Enhancement in quality and productivity: a riskless approach based on optimum selection of tolerance and improvement strategiesby Vahab Moradinaftchali, Xiaoguang Wang, Lixin Song

International Journal of Production Research

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International Journal of Production Research

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Enhancement in quality and productivity: a riskless approach based on optimum selection of tolerance and improvement strategies

Vahab Moradinaftchalia, Xiaoguang Wanga & Lixin Songa a School of Mathematical Sciences, Dalian University of Technology, Dalian, China

Published online: 14 Jun 2015.

To cite this article: Vahab Moradinaftchali, Xiaoguang Wang & Lixin Song (2015): Enhancement in quality and productivity: a riskless approach based on optimum selection of tolerance and improvement strategies, International Journal of Production

Research, DOI: 10.1080/00207543.2015.1055346

To link to this article: http://dx.doi.org/10.1080/00207543.2015.1055346

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Enhancement in quality and productivity: a riskless approach based on optimum selection of tolerance and improvement strategies

Vahab Moradinaftchali*, Xiaoguang Wang and Lixin Song

School of Mathematical Sciences, Dalian University of Technology, Dalian, China (Received 5 June 2014; accepted 18 April 2015)

The need of higher quality products from the customers and the tendency of industries to quality improvement for maintaining their competitive position over the long run are the main motives of using improvement methodologies.

However, any use of improvement methodology besides its additional costs will also change the total variability of the process. Changes in total variability will affect the optimal value of tolerance as well as the quality of the product.

Therefore, one of the main concerns of the producers is to find an effective way to manufacture their goods in a manner that reduces the production costs and gains customers’ satisfaction. To meet these goals, this study introduces an algorithm to propose a riskless approach of improvement that results in the maximum amount of net savings. It is shown that using appropriate improvement strategies simultaneous with a proper selection of tolerance have an important impact to enhance productivity and quality.

Keywords: algorithm; cost reduction; optimal tolerance; productivity improvement; process variability 1. Introduction

Over time, quality has become a relevant factor in customers’ service research, decision-making for customers as well as in services assessment. This phenomenon has gained considerable attention to consumers, investors, industrial organisations, military project or retailers in order to maximised profit and high-quality production. Therefore, quality is a key factor to achieve success and better competitive position in business (Feigenbaum 1956). The organisations which use quality as a business strategy and implement effective quality improvement programmes will experience good financial returns by time (Roland et al. 2002).

In order to control the quality of products, the product function variability needs to be controlled. Deviation of a product from its nominal value can occur due to noise factors that are classified in three groups, namely external factors, manufacturing imperfections and product deterioration. In order to reduce the effects of all these noises so as to produce robust products, Taguchi (1985) classified the counteractions for quality improvement to the following three stages: (1) Offline quality control in R&D. (2) Offline quality control in production engineering. (3) Online quality control during production.

The concept of offline quality control has drawn a great interest from researchers and practitioners and has been successfully used by many companies and industries since Taguchi’s pioneering book in 1986 (Taguchi 1986). This stage can be implemented in three phases, i.e. system design, parameter design and tolerance design. Amongst them, tolerance design has a particular importance in optimisation design and helps determine the optimum tolerances which minimise the total cost due to quality and loss. According to Fischer (2011), a tolerance is the specified amount that a feature is allowed to vary from its nominal value which includes the form, size, orientation or location of the feature as applicable.

A feature or characteristic can be any portion of a part which can be measured such as a hole, a notch, a simple surface, a slot and a complex surface (ASME Y14.5 2009).

In the machining industry, design engineers need to set tolerances for parts manufactured by the firms so that customers’ needs and the company’s competitive position in the market can be held by maintaining the product quality and reasonable prices. Therefore, appropriate selection of design tolerance of manufactured parts is recognised by industries as a key factor in their efforts to increase productivity, control product quality and yield significant cost savings with *Corresponding author. Email: Vahab.Moradi25@gmail.com © 2015 Taylor & Francis