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Article

Nigel Grigg and Lesley Walls

The purpose of this paper is to examine the theoretical interface between statistical thinking, the statistical method of the control chart, and contemporary theories of…

Abstract

Purpose

The purpose of this paper is to examine the theoretical interface between statistical thinking, the statistical method of the control chart, and contemporary theories of organisational learning in regard to processes and their improvement.

Design/methodology/approach

Theoretical discussion results in an integrated model showing how statistical thinking and methods relate to organisational learning. This is supported by findings from a food industry research project following a design of: exploration (stage 1); theory development (stage 2); and theory testing/refinement (stage 3) incorporating surveys, case studies and key informant interviews.

Findings

Empirical evidence shows that statistical techniques such as the control chart can be of benefit to organisations for creating process improvement and organisational learning, providing the charts are utilised to actively convert the data they contain into information and knowledge about the process. Four distinct categories of use of control charts were observed which impacted on the effectiveness with which the charts were able to achieve this.

Research limitations/implications

The findings have come from a study conducted only on the food industry. The implications are generalisable, however, to the wider industry context.

Practical implications

Findings illustrate problems with control chart application and the vital role of statistical thinking in ensuring that maximum benefit is derived from the charts. We argue that statistical thinking is a fundamental prerequisite to achieving effective double loop learning when using control charts as a basis for process monitoring and improvement

Originality/value

Statistical thinking and knowledge management are both growing areas of interest within the quality management and process improvement literature. The paper examines their interrelationship.

Details

The TQM Magazine, vol. 19 no. 1
Type: Research Article
ISSN: 0954-478X

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Article

Sohail S. Chaudhry and J. Richard Higbie

The implementation and use of statistical process control in a chemicals and plastics firm are examined. The essential external factors are focused upon, which are…

Abstract

The implementation and use of statistical process control in a chemicals and plastics firm are examined. The essential external factors are focused upon, which are associated with the practical implementation of statistical process control. The important components of a Statistical Process Control process optimisation study are discussed in the context of their achievements at a manufacturing facility. Benefits achieved from a successful implementation of statistical process control are also discussed.

Details

International Journal of Quality & Reliability Management, vol. 6 no. 5
Type: Research Article
ISSN: 0265-671X

Keywords

Content available
Article

Mahmoud Alsaid, Rania M. Kamal and Mahmoud M. Rashwan

This paper presents economic and economic–statistical designs of the adaptive exponentially weighted moving average (AEWMA) control chart for monitoring the process mean…

Abstract

Purpose

This paper presents economic and economic–statistical designs of the adaptive exponentially weighted moving average (AEWMA) control chart for monitoring the process mean. It also aims to compare the effect of estimated process parameters on the economic performance of three charts, which are Shewhart, exponentially weighted moving average and AEWMA control charts with economic–statistical design.

Design/methodology/approach

The optimal parameters of the control charts are obtained by applying the Lorenzen and Vance’s (1986) cost function. Comparisons between the economic–statistical and economic designs of the AEWMA control chart in terms of expected cost and statistical measures are performed. Also, comparisons are made between the economic performance of the three competing charts in terms of the average expected cost and standard deviation of expected cost.

Findings

This paper concludes that taking into account the economic factors and statistical properties in designing the AEWMA control chart leads to a slight increase in cost but in return the improvement in the statistical performance is substantial. In addition, under the estimated parameters case, the comparisons reveal that from the economic point of view the AEWMA chart is the most efficient chart when detecting shifts of different sizes.

Originality/value

The importance of the study stems from designing the AEWMA chart from both economic and statistical points of view because it has not been tackled before. In addition, this paper contributes to the literature by studying the effect of the estimated parameters on the performance of control charts with economic–statistical design.

Details

Review of Economics and Political Science, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2356-9980

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Article

Li Xue, Jichao Xu and Yumin Liu

The purpose of this paper is to investigate the economic‐statistical design of EWMA charts with variable sampling intervals (VSIs) under non‐normality to reduce the process

Abstract

Purpose

The purpose of this paper is to investigate the economic‐statistical design of EWMA charts with variable sampling intervals (VSIs) under non‐normality to reduce the process production cycle cost and improve the statistical performance of control charts. The objective is to minimize the cost function by adjusting the control chart parameters which suffice for the statistical restriction.

Design/methodology/approach

First, using the Burr distribution to approximate various non‐normal distributions, the economic‐statistical model of the VSI EWMA charts under non‐normality can be developed. Further, the genetic algorithms will be used to search for the optimal values of parameters of the VSI EWMA charts under non‐normality. Finally, a sensitivity analysis is carried out to investigate the effect of model parameters and statistical restriction on the solution of the economic‐statistical design.

Findings

The result of sensitivity analysis shows that a large lower bound of average time to signal when the process is in control increases the control limit coefficient, no model parameter significantly affects the short sampling intervals, and so on.

Originality/value

The economic‐statistical design method proposed in this paper can improve the statistical performance of economic design of control charts and the general idea can be applied to other VSI control charts.

Details

Asian Journal on Quality, vol. 11 no. 3
Type: Research Article
ISSN: 1598-2688

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Article

Emille Rocha Bernardino de Almeida Prata, José Benício Paes Chaves, Silvane Guimarães Silva Gomes and Frederico José Vieira Passos

Quantitative metrics should be used as a risk management option whenever possible. This work proposes a framework for the risk quantification and the resulting risk-based…

Abstract

Purpose

Quantitative metrics should be used as a risk management option whenever possible. This work proposes a framework for the risk quantification and the resulting risk-based design of control charts to monitor quality control points.

Design/methodology/approach

Two quality control models were considered for the risk quantification analysis. Estimated operating characteristic curves, expressing the defect rate (on a ppm basis) as a function of the sample size, process disturbance magnitude and process capacity, were devised to evaluate the maximum rate of defective product of the processes. The proposed framework applicability on monitoring critical control points in Hazard Analysis and Critical Control Point (HACCP) systems was further evaluated by Monte Carlo simulations.

Findings

Results demonstrate that the proposed monitoring systems can be tuned to achieve an admissible failure risk, conveniently expressed as the number of non-conforming items produced per million products, and these risks can be properly communicated. This risk-based approach can be used to validate critical control point monitoring procedures in HACCP plans. The expected rates of non-conforming items sent out to clients estimated through stochastic simulation procedures agree well with theoretical predictions.

Practical implications

The procedures outlined in this study may be used to establish the statistical validity of monitoring systems that uses control charts. The intrinsic risks of these control systems can be assessed and communicated properly in order to demonstrate the effectiveness of quality control procedures to auditing third parties.

Originality/value

This study provides advancements toward practical directives for the implementation of statistical process control in the food industry. The proposed framework allows the assessment and communication of intrinsic failure risks of quality monitoring systems. It may contribute to the establishment of risk-based thinking in the constitution of quality management systems.

Details

International Journal of Quality & Reliability Management, vol. 38 no. 2
Type: Research Article
ISSN: 0265-671X

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Article

Yinhua Liu, Rui Sun and Sun Jin

Driven by the development in sensing techniques and information and communications technology, and their applications in the manufacturing system, data-driven quality…

Abstract

Purpose

Driven by the development in sensing techniques and information and communications technology, and their applications in the manufacturing system, data-driven quality control methods play an essential role in the quality improvement of assembly products. This paper aims to review the development of data-driven modeling methods for process monitoring and fault diagnosis in multi-station assembly systems. Furthermore, the authors discuss the applications of the methods proposed and present suggestions for future studies in data mining for quality control in product assembly.

Design/methodology/approach

This paper provides an outline of data-driven process monitoring and fault diagnosis methods for reduction in variation. The development of statistical process monitoring techniques and diagnosis methods, such as pattern matching, estimation-based analysis and artificial intelligence-based diagnostics, is introduced.

Findings

A classification structure for data-driven process control techniques and the limitations of their applications in multi-station assembly processes are discussed. From the perspective of the engineering requirements of real, dynamic, nonlinear and uncertain assembly systems, future trends in sensing system location, data mining and data fusion techniques for variation reduction are suggested.

Originality/value

This paper reveals the development of process monitoring and fault diagnosis techniques, and their applications in variation reduction in multi-station assembly.

Details

Assembly Automation, vol. 39 no. 4
Type: Research Article
ISSN: 0144-5154

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Article

B.L. MacCarthy and Thananya Wasusri

The principal application domain for statistical process control (SPC) charts has been for process control and improvement in manufacturing businesses. However, the number…

Abstract

The principal application domain for statistical process control (SPC) charts has been for process control and improvement in manufacturing businesses. However, the number of applications reported in domains outside of conventional production systems has been increasing in recent years. Implementing SPC chart approaches in non‐standard applications gives rise to many potential complications and poses a number of challenges. This paper reviews non‐standard applications of SPC charts reported in the literature from the period 1989 to 2000, inclusive. Non‐standard applications are analysed with respect to application domain, data sources used and control chart techniques employed. Applications are classified into five groups according to the types of problem to which control chart techniques have been applied. For each group the nature of the applications is described and analysed. The review does not show a paradigm shift in the types of SPC control chart applications but does show clearly that the application boundaries extend considerably beyond manufacturing and that the range of problems to which SPC control chart techniques can be applied is much wider than commonly assumed. The paper highlights the critical fundamental and technical issues that need to be addressed when applying SPC chart techniques in a range of non‐standard applications. Wider managerial issues of importance for successful implementations in non‐standard applications of SPC control charts are also discussed.

Details

International Journal of Quality & Reliability Management, vol. 19 no. 3
Type: Research Article
ISSN: 0265-671X

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Article

Maurizio Bevilacqua, Filippo Emanuele Ciarapica, Giancarlo Giacchetta and Barbara Marchetti

The purpose of this paper is to present the application of a procedure for the quality control of stainless steel tubes produced for automotive exhaust systems from a…

Abstract

Purpose

The purpose of this paper is to present the application of a procedure for the quality control of stainless steel tubes produced for automotive exhaust systems from a leading company in the steel sector, based on the Delphi method in accordance with the ISO/TS 16949:2009 and the ISO 9000:2008. Using Delphi methodology, it was possible to identify the main problems in the production lines object of the study, the main defects and their causes. Statistical methods were used to monitor process compliance and capacity. The panel of experts involved in Delphi method was able to identify causes of non‐compliance and suggest corrective actions.

Design/methodology/approach

The quality procedure implemented involves the application of the Delphi method and the ISO/TS 16949:2009 standard in conjunction with ISO 9000:2008 to the production line of welded tubes for exhaust systems. The statistical methods used to monitor the process were mainly control charts. Capability index, Cp and Cpk, were used to measure the process attitude to produce compliant outputs. Dimensional data were acquired by non‐destructive testing on diameters and X‐R charts were used to graphically represent the process state of control. Destructive tests were performed to monitor the welding quality and P‐chart were used to assess the proportion of nonconforming units.

Findings

In this work, a procedure was developed in order to characterize the production process of TXM tubes realized in the line 31 of the leader company plant. The use of Delphi methodology, in order to incorporate experts opinions in the quality control of stainless steel tubes, was one of the main points of this work. The panel of experts worked together to identify process issues, define their causes and propose corrective actions. The paper provides an overview about the quality approach of one of the world's largest companies in the production of steel and shows also how the statistical tools are used in order to manage process behavior.

Originality/value

The value of this paper is to illustrate an innovative approach to a real life quality problem; it demonstrates how the application of qualitative and quantitative quality instruments in accordance with technical specification can help in increasing and maintaining product compliance and in optimizing the management of resources.

Details

International Journal of Quality & Reliability Management, vol. 28 no. 8
Type: Research Article
ISSN: 0265-671X

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Article

Sagar Sikder, Subhash Chandra Panja and Indrajit Mukherjee

The purpose of this paper is to develop a new easy-to-implement distribution-free integrated multivariate statistical process control (MSPC) approach with an ability to…

Abstract

Purpose

The purpose of this paper is to develop a new easy-to-implement distribution-free integrated multivariate statistical process control (MSPC) approach with an ability to recognize out-of-control points, identify the key influential variable for the out-of-control state, and determine necessary changes to achieve the state of statistical control.

Design/methodology/approach

The proposed approach integrates the control chart technique, the Mahalanobis-Taguchi System concept, the Andrews function plot, and nonlinear optimization for multivariate process control. Mahalanobis distance, Taguchi’s orthogonal array, and the main effect plot concept are used to identify the key influential variable responsible for the out-of-control situation. The Andrews function plot and nonlinear optimization help to identify direction and necessary correction to regain the state of statistical control. Finally, two different real life case studies illustrate the suitability of the approach.

Findings

The case studies illustrate the potential of the proposed integrated multivariate process control approach for easy implementation in varied manufacturing and process industries. In addition, the case studies also reveal that the multivariate out-of-control state is primarily contributed by a single influential variable.

Research limitations/implications

The approach is limited to the situation in which a single influential variable contributes to out-of-control situation. The number and type of cases used are also limited and thus generalization may not be debated. Further research is necessary with varied case situations to refine the approach and prove its extensive applicability.

Practical implications

The proposed approach does not require multivariate normality assumption and thus provides greater flexibility for the industry practitioners. The approach is also easy to implement and requires minimal programming effort. A simple application Microsoft Excel is suitable for online implementation of this approach.

Originality/value

The key steps of the MSPC approach are identifying the out-of-control point, diagnosing the out-of-control point, identifying the “influential” variable responsible for the out-of-control state, and determining the necessary direction and the amount of adjustment required to achieve the state of control. Most of the approaches reported in open literature are focused only until identifying influencing variable, with many restrictive assumptions. This paper addresses all key steps in a single integrated distribution-free approach, which is easy to implement in real time.

Details

International Journal of Quality & Reliability Management, vol. 34 no. 8
Type: Research Article
ISSN: 0265-671X

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Article

P. Castagliola, G. Celano and S. Fichera

The aim of this study is to present the economic‐statistical design of an EWMA control chart for monitoring the process dispersion.

Abstract

Purpose

The aim of this study is to present the economic‐statistical design of an EWMA control chart for monitoring the process dispersion.

Design/methodology/approach

The optimal economic‐statistical design of the S EWMA chart was determined for a wide benchmark of examples organized as a two level factorial design and was compared with the designs obtained for the S Shewhart chart. Both the two charts have been designed so that an equal number of false alarms (in‐control Average Run Length) is expected.

Findings

The S EWMA allows significant hourly cost savings to be achieved for the entire set of process scenarios with respect to the S Shewhart; a mean percentage cost saving of 6.77 per cent is obtained for processes characterized by a reduction in process dispersion (i.e. processes whose natural variability is reduced through an external technological intervention), whereas up to a 9.78 per cent saving is achieved for processes whose dispersion is increased by the occurrence of an undesired special cause.

Practical implications

The proposed S EWMA chart can be considered as an effective tool when statistical process control procedures should be implemented on a process with the aim of monitoring its data dispersion.

Originality/value

In literature the economic design of EWMA charts covers only the process cost evaluation when the sample mean is monitored; here, the study is extended to the sample standard deviation to investigate if the EWMA scheme still outperforms the Shewhart chart. An extensive analysis is proposed to evaluate the influence of the process operating parameters on the EWMA chart design variables.

Details

Journal of Quality in Maintenance Engineering, vol. 13 no. 3
Type: Research Article
ISSN: 1355-2511

Keywords

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