Key Success Factors for the Implementation of SPC

Jiju Antony and Ben Mason

School of Engineering, University of Warwick, UK

E-mail: Jiju.Antony@warwick.ac.uk

Mr Tolga Taner

Boaziçi University

Institute of Biomedical Engineering

Bebek 80015, Istanbul, Turkey

Current consumer markets experience an ever-increasing demand for high quality products and services at low costs. It is therefore logical that if a company wishes to be competitive in the modern market place, one of its main aims should be to focus upon producing products/processes of a consistently high quality. Total Quality Management (TQM) is a broad management philosophy used within the organizations with the aim of promoting a culture and attitude of continuous improvement of product/service quality. Statistical Process Control (SPC) is a technique used within the TQM framework for reducing variation in processes which we deal with everyday. It is a powerful technique to control, manage, analyze and improve the performance of a process by eliminating special causes of variation in processes such as tool wear, operator error, errors in measurements, use of improper raw material, and so on [1].

In the western world, the general consensus is that techniques like SPC should be implemented for customer satisfaction rather than part of a strategic plan by the company. The full benefits of SPC tend to be realized only when the motivation is appropriate. According to Brannstrom-Stenberg & Deleryd, "Organisations that have implemented statistical process control of their own free will experience advantages to a greater extent" [2]. In Japan, many companies have embraced the technique SPC with great success for tackling quality related problems such as high scrap rate, increased number of customer complaints, high rework costs, incapable processes etc. SPC has not proved to be similarly successful in the West due to various reasons. Some noticeable reasons are:

·      Lack of commitment from senior management

·      Lack of training and education in SPC

·      Lack of awareness of the potential benefits of SPC

·      Lack of knowledge on what to measure and how to measure in a certain process

·      Inadequate measurement system in place

·      Lack of knowledge to prioritize processes

·      Misinterpretation of control charts

·      Negative reaction of operators and middle managers

·      Resistance to change, and so on.

In order to effectively apply SPC in any organization, it is fundamental to understand the essential ingredients that will make the application of SPC successful. These ingredients are:

Management issues – total management support and commitment, necessary resources for training and education + follow-up of training from time to time, actions on the system/processes whenever needed

Engineering skills – understanding the key benefits from the introduction and application of SPC, measurement system analysis (stability, capability, linearity etc.), process prioritization, understanding what key characteristics or process parameters to measure and how to measure them, etc.

Statistical skills – statistical stability, calculation of control limits, interpretation of control limits, selection of control charts, determination of sample size & sub-group size, etc.

Teamwork skills – company-wide understanding of SPC and its benefits, co-operation from all levels of the organization, brainstorm what needs to measure in a process and so on.

Statistical Education for Engineering Students in the UK

Perhaps the training and education towards SPC implementation should be taught at an earlier stage and on a wider front in the education system, especially to engineering students in higher education. Currently, within engineering institutions very little time is spent on management and implementation aspects of SPC. The main focus seems to be on control charting of various processes. According to Xie and Goh " Too often Organizations look at the control chart as the only approach to handle issues – and this will not work" [3]. Very few engineers graduating today from the UK higher education institutions are exposed to powerful problem solving techniques such as SPC, Design of Experiments (DOE) and Taguchi methods [Antony et al., 1999].

The first two authors are currently developing a useful and practical framework for the implementation of SPC that will assist industrial engineers with limited skills and knowledge in SPC. The conceptual framework will consider the ingredients, which are essential for the success of SPC initiatives in organizations. The framework will take the form of a systematic methodology for the effective implementation of SPC in any industrial setting.

References

[1]. Ben Mason and Jiju Antony, "Is SPC Just about Control Charts", Unpublished work.

[2]. Brannstorm-Stenberg and Deleryd, "Implementation of Statistical Process Control and Process Capability Studies: Requirements or Free will?", TQM Journal, July 1999.

[3]. Xie and Goh, "Statistical Techniques for Quality", The TQM Magazine, 1999.

[4]. Antony, J et al., "Experimental Quality – A Strategic Approach to Achieve and Improve Quality", Kluwer Academic Publishers, 1999.

Learn more about the SPC principles and tools for process improvement in Statistical Process Control Demystified (2011, McGraw-Hill) by Paul Keller, in his online SPC Concepts short course (only $39), or his online SPC certification course ($350) or online Green Belt certification course ($499).