Graeme Knowles

Critical success factors of TQM implementation in Hong Kong industries

Total quality management (TQM) is an integrative management philosophy aimed at continuously improving the performance of products, processes and services to achieve and exceed customer expectations. This paper provides an empirical study on the identification of the critical success factors (CSFs) of TQM implementation in Hong Kong industries. Through a thorough and detailed analysis of the literature, 11 success factors with 72 elements were identified to develop a questionnaire. These items were empirically tested by data collected from 32 companies in Hong Kong. A factor analysis was carried out that identified seven CSFs with 38 elements of the implementation of TQM. These factors were shown to be reliable and valid and offer new insights into the understanding of TQM success factors in Hong Kong industries.

A conceptual model for the application of Six Sigma methodologies to supply chain improvement

This paper hypothesises that, whilst Six Sigma as a change and improvement strategy is delivering significant business benefit to practitioner organisations, it has not been successfully adapted to deliver similar benefits across supply chains. It demonstrates by reference to the literature that most published applications of Six Sigma in supply chains are related to the application of traditional internal Six Sigma methodologies to the internal processes of a supplier to the “Six Sigma Organisation”. In this paper, the issues particular to an application of Six Sigma in a broader supply chain context are discussed, with reference to specific supply chain issues. It is concluded that Six Sigma does have something novel to offer organisations over and above the contribution of existing approaches to supply chain improvement, and a conceptual model is proposed that is consistent with the literature and has potential to support such an introduction. The model integrates the Balanced Scorecard, SCOR model (Supply Chain Reference model) and Six Sigma DMAIC (define, measure, analyse and improve) methodology in a two-level framework. This is a strategic-level cycle, developing focused projects to generate maximum business benefit, and an operational-level cycle, applying Six Sigma and lean tools in a DMAIC cycle to deliver supply chain improvements. Cautions and requirements for the success in practice of such a model are discussed and it is concluded that the model should be tested in practice to validate and develop further the methodology.

An investigation into Japanese 5‐S practice in UK industry

This paper presents the findings of a survey on the use of the Japanese practice of 5‐S for workplace organisation in the UK. The research methodology was to review the literature, conduct a survey using a questionnaire, follow‐up the questionnaire with a series of semi‐structured interviews and critique findings with the literature. The conclusions of the research are that practice and theory are closely related and any differences in the implementation of 5‐S can be attributed mainly to the maturity of the 5‐S programme. Clearly, there is great scope for the application of 5‐S in the non‐manufacturing environment.

Determinants of performance amongst shop‐floor employees

Purpose – The paper aims to explore the determinants of perceived job performance in a sample of shop‐floor employees in a manufacturing plant in northern Mexico.Design/methodology/approach – It is hypothesised that job satisfaction, age and education levels are significant predictors of job performance. A thorough literature review reveals that studies of the variables that influence job performance within a manufacturing setting are basically lacking. A questionnaire distributed amongst shop‐floor employees and their immediate supervisors was used in order to measure the variables included in the study. Statistical analyses were performed with the data in order to test for the reliability and validity of the measures, and also to test the three main research hypotheses.Findings – It was found that two variables that measure job satisfaction are positively and significantly associated with job performance. This result is consistent with previous studies. Nevertheless, age and education levels do not show...

An application of experimental design for process optimisation

Dr Taguchi is a Japanese engineer and an international quality consultant who has made breakthrough improvements in product and process quality through the use of statistical design of experiments (SDOE). The Taguchi method became popular in the West in the 1980s as a means to design robust products and processes. Although many companies and industries have used the method with success, the real benefits of the approach were not realised and fully understood in many cases. This lack of success could be attributed to a number of factors, but mainly because the experiments were treated in isolation and not integrated into a continuous improvement strategy. This paper briefly presents the results of the application of the Taguchi methodology in the UK industry. The paper also illustrates the application of the Taguchi method for optimising the production process of retaining a metal ring in a plastic body in a braking system.

Strategic consensus on manufacturing competitive priorities

Purpose – The purpose of this paper is to provide a critical analysis of studies on strategic consensus along manufacturing competitive priorities. Based on this analysis, a new methodology to measure strategic consensus on manufacturing competitive priorities that is more consistent with mainstream operations management theory is proposed. The paper also includes novel proposals for future research.Design/methodology/approach – The new methodology and proposals for research are mainly based on a literature review of previous studies on strategic consensus regarding manufacturing competitive priorities and also on relevant research and works in the field of operations management.Findings – Previous methodologies used to measure strategic consensus regarding manufacturing competitive priorities are mainly based on studies in the business strategy field. Thus, these methodologies are deemed as inadequate in the operations management field. It is also found that there are very few studies that have analysed ...

Gauge Capability Analysis: classical versus ANOVA.

In order to use Statistical Process Control (SPC) efficiently and effectively in todays modern industrial environment, it is essential to analyze and determine the extent of gauge variability. The variation that occurs on a control chart is essentially a combination of product and gauge variation. Studies of measurement or gauge variation are absolutely a waste of resources unless they can lead to a substantial reduction in process variability or to an improvement in process and product quality. The goal of gauge capability analysis is an understanding and quantification of the various sources of variability present in the measurement process. The purpose of this paper is to illustrate the fundamental difference between Classical Gauge Capability Analysis (CGCA) and the use of a more powerful approach based on the Analysis of Variance (ANOVA). The author recommends that the latter approach is more useful and powerful in the presence of an interaction between the parts and the operators involved in the measurement process. An example is illustrated in the paper to demonstrate the two approaches.

Evaluating Process Capability for Geometrically Toleranced Parts: A Practical Approach

The practice of geometric tolerancing has gained in industry popularity since the 1990s. This approach has advantages over conventional tolerancing in defining both geometry and associated tolerance and, thus, generating a more realistic “acceptable design space.” There have been a number of highly mathematical treatments of the subject over the years which have not found their way into popular usage. We look at a specific example of geometric tolerancing and derive a simple approach based on the geometry of the situation and standard C p and C pk calculations. The study describes an approach based on understanding the limiting conditions of acceptable operation. In the example of a pin and clearance hole, we derive the limiting condition as a zero radial gap for a hole and a perfectly centered pin at maximum metal condition. We then performed a standard C pk calculation with the limiting condition acting as the effective tolerance limit. Because we are dealing with radial gaps, we have an effective one-sided tolerance with a minimum acceptable value of 0 for the radial gaps. We tested the approach using Normally distributed simulated data and found that it provides an accurate evaluation of process capability and projected scrap levels. With minor cautions, we conclude that this methodological approach could be extrapolated to other geometrically toleranced situations.

A practical methodology for analysing and improving the measurement system

Measurement systems are used widely in manufacturing organisations in order to make many important decisions. These decisions range from the acceptability of a given product against tolerance requirements to the level of statistical control of a process or its capability to consistently perform a given task. In most situations, however, little thought is given to the quality of the data generated by such measurement processes. By using potentially flawed data in making fundamental manufacturing decisions, organisations undermine the quality of the decision-making process itself. This paper reviews the approaches presently available from both a technical and a practical point of view, based on the priorities of process improvement practitioners. The conclusion of the paper is that the Evaluation of the Measurement Process proposed by Wheeler and Lyday offers the best balance of accuracy and utility.