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Success factors in the implementation of statistical process control: action research in a chemical plant

Abstract

Despite the Statistical Process Control (SPC) be extensively explored in the literature, there are still difficulties in the implementation and maintenance, usually due to lack of attention to Critical Success Factors (CSF). This paper identified by literature review, critical factors that contribute to the success of the SPC and through an action research was implemented a control chart in a chemical plant using these factors. The attention to CSF during planning, implementation and the discussion with the process team resulted in the implementation and acceptance of control charts by the operational teams of the company, with continuing indications of use. The results enabled a framework to apply control charts based on CSF.

Keywords
Control charts; Critical success factors; Implementation; Statistical process control

1. Introduction

The Statistical Process Control (SPC) have been used in industrial processes since the 1920s, with an increase during the Second World War. The emergence of Six Sigma Program intensified the use because of the incorporation of the systematic use of the SPC in its methodology (Montgomery, 2014Montgomery, D. C. (2014). Introdução ao controle estatístico da qualidade (4th ed.). Rio de Janeiro: Gen-LTC.).

Although the use is relatively easy, studies describe steps for implementation and examples of SPC in specific processes (Hradesky, 1989Hradesky, J. L. (1989). Aperfeiçoamento da qualidade e da produtividade: guia prático para implementação do Controle Estatístico de Processo – CEP. São Paulo: McGraw-Hill.; Kumar & Motwani, 1996Kumar, A., & Motwani, J. (1996). Doing it right the second time. Industrial Management & Data Systems, 96(6), 14-19. http://dx.doi.org/10.1108/02635579610126818.
http://dx.doi.org/10.1108/02635579610126...
; Antony & Taner, 2003Antony, J., & Taner, T. (2003). A conceptual framework for the effective implementation of statistical process control. Business Process Management Journal, 9(4), 473-489. http://dx.doi.org/10.1108/14637150310484526.
http://dx.doi.org/10.1108/14637150310484...
). However, there is no information whether the results obtained in the process control were continued and the control chart was adopted as a working process.

The application of SPC demands organizational and behavioral changes and it is important the dialogue and integration between management and operators aiming exchange of information and learning for the successful use of control charts. It indicates the need for consideration of factors that transcend the technical aspects of implementation (Grigg & Walls, 2007aGrigg, N., & Walls, L. (2007a). Developing statistical thinking for performance improvement in the food industry. International Journal of Quality & Reliability Management, 24(4), 347-369. http://dx.doi.org/10.1108/02656710710740536.
http://dx.doi.org/10.1108/02656710710740...
).

In the North American chemical industry in the 1980s, there was a renewed interest in the use of the SPC. The SPC was mainly used to replace the inspection of the quality of the final product, in order to reduce the variability of the product, generating increased productivity, reduce energy consumption and stock levels (Chowdhury, 1986Chowdhury, J. (1986). Quality-Control moves upstream in CPI plants. Chemical Engineering (Albany, N.Y.), 93(8), 19-23.).

There are difficulties in the use of SPC in continuous processes involving liquids and gases, common in chemical industries (Gallagher, 1990Gallagher, W. M. (1990). SPC application in the chemical industry. In Proceedings of the IEE Colloquium on Applied Statistical Process Control, London.), although the SPC provide an effective means for this monitoring (Haslego, 2000Haslego, C. (2000). Apply statistical process control with intelligence. Chemical Engineering, 107(3), 86. Retrieved in 8 September 2016, from http://search.proquest.com/openview/72f090549d20ac47b48caaadb1e10a13/1?pq-origsite=gscholar&cbl=41910
http://search.proquest.com/openview/72f0...
). Process control engineers can use control charts to monitor the stability, capacity and process performance and at the same time, those responsible for quality may follow if the process is following the quality standards (Haslego, 2000Haslego, C. (2000). Apply statistical process control with intelligence. Chemical Engineering, 107(3), 86. Retrieved in 8 September 2016, from http://search.proquest.com/openview/72f090549d20ac47b48caaadb1e10a13/1?pq-origsite=gscholar&cbl=41910
http://search.proquest.com/openview/72f0...
).

In publications on the subject, it is possible to observe the value of the SPC in different production processes and that there are several factors identified as important to the success of its implementation (Rohani et al., 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
). This paper aims, through action research in a chemical plant, implement SPC charts applying critical success factors and discussing the relevance for continuous use.

2. Success factors in the implementation of the SPC

The factors that affect the implementation of the SPC are complex and numerous (Rohani et al., 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
) and can be called Critical Success Factors (CSF). If there is a better control over these factors, the chance of success in the implementation of SPC is higher (Gordon et al., 1994Gordon, M. E., Philpot, J. W., Bounds, G. M., & Long, W. S. (1994). Factors associated with the success of the implementation of statistical process control. The Journal of High Technology Management Research, 5(1), 101-121. http://dx.doi.org/10.1016/1047-8310(94)90016-7.
http://dx.doi.org/10.1016/1047-8310(94)9...
; Elg et al., 2008Elg, M., Olsson, J., & Dahlgaard, J. (2008). Implementing statistical process control: an organizational perspective. International Journal of Quality & Reliability Management, 25(6), 545-560. http://dx.doi.org/10.1108/02656710810881872.
http://dx.doi.org/10.1108/02656710810881...
; Rohani et al., 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
).

The implementation of the SPC involves technical factors and organizational factors, both are considered critical for successful implementation (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
; Elg et al., 2008Elg, M., Olsson, J., & Dahlgaard, J. (2008). Implementing statistical process control: an organizational perspective. International Journal of Quality & Reliability Management, 25(6), 545-560. http://dx.doi.org/10.1108/02656710810881872.
http://dx.doi.org/10.1108/02656710810881...
). Xie & Goh (1999)Xie, M., & Goh, T. N. (1999). Statistical techniques for quality. The TQM Magazine, 11(4), 238-242. http://dx.doi.org/10.1108/09544789910272913.
http://dx.doi.org/10.1108/09544789910272...
emphasize an holistic approach to the implementation of SPC, based on three basis: the first, related to the SPC Management, which involves issues such as the role of senior management, focus on Continuous Improvement, training and teamwork; the second, related to the human factor, which presents resistance to change issues, difficulties with the use of computer technologies and the need for incentives; the third, focuses on the implementation of the SPC, including the use of appropriate tools for monitoring the process.

Although SPC is superficially a simple technique, the application is a more complex issue (Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
). The main reasons for failures in implementing are related to: organizational and social factors (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
); lack of senior management commitment (Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
); lack of training and understanding of SPC (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
; Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
); decreased attention after the introduction (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
) and the lack of understanding of the potential benefits of the SPC (Mason & Antony, 2000Mason, B., & Antony, J. (2000). Statistical process control: an essential ingredient for improving service and manufacturing quality. Managing Service Quality: An International Journal, 10(4), 233-238. http://dx.doi.org/10.1108/09604520010341618.
http://dx.doi.org/10.1108/09604520010341...
).

SPC implementation does not only refer to the sequence of actions to build the control charts and interpret the process is under control. The implementation is also related to social, environmental, technical and cultural factors that will make sure that the use of these charts is integrated into the routine process. For the analysis of critical success factors for SPC, a Systematic Literature Review (SLR) was held to identify the publications that address these factors (Table 1).

Table 1
Stages of the systematic literature review.

Considering the low number of returns in Web of Science, Scopus and Engineering Village, the same search was made in Google Scholar, but the search terms were found throughout the body of the paper, returning 310 publications. Results related to patents were excluded, leaving 298 publications, of which the titles and abstracts were read, 41 were selected, including those found in Web of Science, Scopus and Engineering Village. After a complete reading of the 41 papers, it was identified that 25 contributed to the subject.

A compilation and analysis of CSF present in these publications has been made, considering that different authors refer to the same content with different names and some factors are contained in others. After the compilation, 19 CSF were found with more than one citation.

The three most cited factors are related to SPC management, the first one is the “Commitment and senior management responsibility” (Gordon et al., 1994Gordon, M. E., Philpot, J. W., Bounds, G. M., & Long, W. S. (1994). Factors associated with the success of the implementation of statistical process control. The Journal of High Technology Management Research, 5(1), 101-121. http://dx.doi.org/10.1016/1047-8310(94)90016-7.
http://dx.doi.org/10.1016/1047-8310(94)9...
; Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
; Rungtusanatham et al., 1999Rungtusanatham, M., Anderson, J. C., & Dooley, K. J. (1999). Towards measuring the “SPC implementation/practice” construct: some evidence of measurement quality. International Journal of Quality & Reliability Management, 16(4), 301-329. http://dx.doi.org/10.1108/02656719910239938.
http://dx.doi.org/10.1108/02656719910239...
; Xie & Goh, 1999Xie, M., & Goh, T. N. (1999). Statistical techniques for quality. The TQM Magazine, 11(4), 238-242. http://dx.doi.org/10.1108/09544789910272913.
http://dx.doi.org/10.1108/09544789910272...
; Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
; Rungasamy et al., 2002Rungasamy, S., Antony, J., & Ghosh, S. (2002). Critical success factors for SPC implementation in UK small and medium enterprises: some key findings from a survey. The TQM Magazine, 14(4), 217-224. http://dx.doi.org/10.1108/09544780210429825.
http://dx.doi.org/10.1108/09544780210429...
; Antony & Taner, 2003Antony, J., & Taner, T. (2003). A conceptual framework for the effective implementation of statistical process control. Business Process Management Journal, 9(4), 473-489. http://dx.doi.org/10.1108/14637150310484526.
http://dx.doi.org/10.1108/14637150310484...
; Grigg & Walls, 2007bGrigg, N., & Walls, L. (2007b). The role of control charts in promoting organisational learning: New perspectives from a food industry study. The TQM Magazine, 19(1), 37-49. http://dx.doi.org/10.1108/09544780710720826.
http://dx.doi.org/10.1108/09544780710720...
; Chen et al., 2008Chen, S. H., Yang, C. C., Lin, W. T., & Yeh, T. M. (2008). Performance evaluation for introducing statistical process control to the liquid crystal display industry. International Journal of Production Economics, 111(1), 80-92. http://dx.doi.org/10.1016/j.ijpe.2006.12.055.
http://dx.doi.org/10.1016/j.ijpe.2006.12...
; Elg et al., 2008Elg, M., Olsson, J., & Dahlgaard, J. (2008). Implementing statistical process control: an organizational perspective. International Journal of Quality & Reliability Management, 25(6), 545-560. http://dx.doi.org/10.1108/02656710810881872.
http://dx.doi.org/10.1108/02656710810881...
; Phyanthamilkumaran & Fernando, 2008Phyanthamilkumaran, S. Z., & Fernando, Y. (2008). The role of cultural change in the relationship between critical factors with the success of Statistical Process Control (SPC) projects. Proceedings of Annual London Conference on Money, Economy and Management, 3(4), 1-11.; Putri & Yusof, 2008Putri, T. N., & Yusof, S. R. M. (2008). Critical success factors for implementing quality engineering (QE) in Malaysian’s and Indonesian’s automotive industries: a proposed model. International Journal of Automotive Industry and Management, 2, 1-15. Retrieved in 8 September 2016, from http://kari.hyundai.com/karifile/IJAIM_reports/Vol2_No2/vol2_no2_01_Critical%20Success%20Factors%20for%20Implementing%20Quality%20Engineering%20(QE)%20In%20Malaysian's%20and%20Indonesian's%20Automotive%20Industries-A%20Proposed%20Model.pdf
http://kari.hyundai.com/karifile/IJAIM_r...
, 2009Putri, N. T., & Yusof, S. M. (2009). Critical success factors for implementing quality engineering tools and techniques in malaysian’s and indonesian’s automotive industries: an exploratory study. In Proceedings of the International MultiConference of Engineers and Computer Scientists (pp. 18-20), Hong Kong, China.; Rohani et al., 2009aRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009a). The relationship between statistical process control critical success factors and performance: a structural equation modeling approach. In Proceedings of the 2009 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1352-1356), Hong Kong, China. http://dx.doi.org/10.1109/ieem.2009.5373033.
http://dx.doi.org/10.1109/ieem.2009.5373...
, bRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009b). Statistical process control success factors and performance: an exploratory analysis. In Proceedings of the Advances in Quality Engineering and Management Reserch, Malaysia. Retrieved in 8 September 2016, from http://eprints.uthm.edu.my/2571/
http://eprints.uthm.edu.my/2571/...
; 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
; Mahanti & Evans, 2012Mahanti, R., & Evans, J. R. (2012). Critical success factors for implementing statistical process control in the software industry. Benchmarking: An International Journal, 19(3), 374-394. http://dx.doi.org/10.1108/14635771211244309.
http://dx.doi.org/10.1108/14635771211244...
; Lim & Antony, 2013Lim, S. A. H., & Antony, J. (2013). A conceptual readiness framework for statistical process control deployment. In Proceedings of the IEEE International Conference Industrial Engineering and Engineering Management (pp. 300-304), Bangkok, Thailand. http://dx.doi.org/10.1109/ieem.2013.6962422.
http://dx.doi.org/10.1109/ieem.2013.6962...
; 2014Lim, S. A. H., & Antony, J. (2014). The implementation of statistical process control in the food industry: a systematic review. In Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management (pp. 1682-1691), Bali, Indonesia.; Rantamäki et al., 2013Rantamäki, J., Tiainen, E. L., & Kässi, T. (2013). A case of implementing SPC in a pulp mill. International Journal of Lean Six Sigma, 4(3), 321-337. http://dx.doi.org/10.1108/IJLSS-05-2013-0029.
http://dx.doi.org/10.1108/IJLSS-05-2013-...
; Lim et al., 2014Lim, S. A. H., Antony, J., & Albliwi, S. (2014). Statistical Process Control in the food industry–A systematic review and future research agenda. Trends in Food Science & Technology, 37(2), 137-151. http://dx.doi.org/10.1016/j.tifs.2014.03.010.
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; 2016Lim, S. A. H., Antony, J., & Arshed, N. (2016). A Critical Assessment on SPC Implementation in the UK Food Industry. Systemics. Cybernetics and Informatics, 14(1), 37-42. Retrieved in 8 September 2016, from http://www.iiisci.org/journal/CV$/sci/pdfs/SA430BZ15.pdf
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; Sharma & Kharub, 2014Sharma, R., & Kharub, M. (2014). Attaining competitive positioning through SPC – an experimental investigation from SME. Measuring Business Excellence, 18(4), 86-103. http://dx.doi.org/10.1108/MBE-10-2013-0050.
http://dx.doi.org/10.1108/MBE-10-2013-00...
), which is related to support the implementation with financial, human resources and training and is related to the second factor, “Education and training in SPC”, the training in concepts and techniques needs resources and senior management support, and it was appointed as CSF by the same number of authors in the literature (Gordon et al., 1994Gordon, M. E., Philpot, J. W., Bounds, G. M., & Long, W. S. (1994). Factors associated with the success of the implementation of statistical process control. The Journal of High Technology Management Research, 5(1), 101-121. http://dx.doi.org/10.1016/1047-8310(94)90016-7.
http://dx.doi.org/10.1016/1047-8310(94)9...
; Rungtusanatham et al., 1999Rungtusanatham, M., Anderson, J. C., & Dooley, K. J. (1999). Towards measuring the “SPC implementation/practice” construct: some evidence of measurement quality. International Journal of Quality & Reliability Management, 16(4), 301-329. http://dx.doi.org/10.1108/02656719910239938.
http://dx.doi.org/10.1108/02656719910239...
; Xie & Goh, 1999Xie, M., & Goh, T. N. (1999). Statistical techniques for quality. The TQM Magazine, 11(4), 238-242. http://dx.doi.org/10.1108/09544789910272913.
http://dx.doi.org/10.1108/09544789910272...
; Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
; Mason & Antony, 2000Mason, B., & Antony, J. (2000). Statistical process control: an essential ingredient for improving service and manufacturing quality. Managing Service Quality: An International Journal, 10(4), 233-238. http://dx.doi.org/10.1108/09604520010341618.
http://dx.doi.org/10.1108/09604520010341...
; Rungasamy et al., 2002Rungasamy, S., Antony, J., & Ghosh, S. (2002). Critical success factors for SPC implementation in UK small and medium enterprises: some key findings from a survey. The TQM Magazine, 14(4), 217-224. http://dx.doi.org/10.1108/09544780210429825.
http://dx.doi.org/10.1108/09544780210429...
; Antony & Taner, 2003Antony, J., & Taner, T. (2003). A conceptual framework for the effective implementation of statistical process control. Business Process Management Journal, 9(4), 473-489. http://dx.doi.org/10.1108/14637150310484526.
http://dx.doi.org/10.1108/14637150310484...
; Grigg & Walls, 2007bGrigg, N., & Walls, L. (2007b). The role of control charts in promoting organisational learning: New perspectives from a food industry study. The TQM Magazine, 19(1), 37-49. http://dx.doi.org/10.1108/09544780710720826.
http://dx.doi.org/10.1108/09544780710720...
; Chen et al., 2008Chen, S. H., Yang, C. C., Lin, W. T., & Yeh, T. M. (2008). Performance evaluation for introducing statistical process control to the liquid crystal display industry. International Journal of Production Economics, 111(1), 80-92. http://dx.doi.org/10.1016/j.ijpe.2006.12.055.
http://dx.doi.org/10.1016/j.ijpe.2006.12...
; Elg et al., 2008Elg, M., Olsson, J., & Dahlgaard, J. (2008). Implementing statistical process control: an organizational perspective. International Journal of Quality & Reliability Management, 25(6), 545-560. http://dx.doi.org/10.1108/02656710810881872.
http://dx.doi.org/10.1108/02656710810881...
; Phyanthamilkumaran & Fernando, 2008Phyanthamilkumaran, S. Z., & Fernando, Y. (2008). The role of cultural change in the relationship between critical factors with the success of Statistical Process Control (SPC) projects. Proceedings of Annual London Conference on Money, Economy and Management, 3(4), 1-11.; Putri & Yusof, 2008Putri, T. N., & Yusof, S. R. M. (2008). Critical success factors for implementing quality engineering (QE) in Malaysian’s and Indonesian’s automotive industries: a proposed model. International Journal of Automotive Industry and Management, 2, 1-15. Retrieved in 8 September 2016, from http://kari.hyundai.com/karifile/IJAIM_reports/Vol2_No2/vol2_no2_01_Critical%20Success%20Factors%20for%20Implementing%20Quality%20Engineering%20(QE)%20In%20Malaysian's%20and%20Indonesian's%20Automotive%20Industries-A%20Proposed%20Model.pdf
http://kari.hyundai.com/karifile/IJAIM_r...
; 2009Putri, N. T., & Yusof, S. M. (2009). Critical success factors for implementing quality engineering tools and techniques in malaysian’s and indonesian’s automotive industries: an exploratory study. In Proceedings of the International MultiConference of Engineers and Computer Scientists (pp. 18-20), Hong Kong, China.; Rohani et al., 2009aRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009a). The relationship between statistical process control critical success factors and performance: a structural equation modeling approach. In Proceedings of the 2009 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1352-1356), Hong Kong, China. http://dx.doi.org/10.1109/ieem.2009.5373033.
http://dx.doi.org/10.1109/ieem.2009.5373...
, bRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009b). Statistical process control success factors and performance: an exploratory analysis. In Proceedings of the Advances in Quality Engineering and Management Reserch, Malaysia. Retrieved in 8 September 2016, from http://eprints.uthm.edu.my/2571/
http://eprints.uthm.edu.my/2571/...
; 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
; Mahanti & Evans, 2012Mahanti, R., & Evans, J. R. (2012). Critical success factors for implementing statistical process control in the software industry. Benchmarking: An International Journal, 19(3), 374-394. http://dx.doi.org/10.1108/14635771211244309.
http://dx.doi.org/10.1108/14635771211244...
; Lim & Antony, 2013Lim, S. A. H., & Antony, J. (2013). A conceptual readiness framework for statistical process control deployment. In Proceedings of the IEEE International Conference Industrial Engineering and Engineering Management (pp. 300-304), Bangkok, Thailand. http://dx.doi.org/10.1109/ieem.2013.6962422.
http://dx.doi.org/10.1109/ieem.2013.6962...
; 2014Lim, S. A. H., & Antony, J. (2014). The implementation of statistical process control in the food industry: a systematic review. In Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management (pp. 1682-1691), Bali, Indonesia.; Rantamäki et al., 2013Rantamäki, J., Tiainen, E. L., & Kässi, T. (2013). A case of implementing SPC in a pulp mill. International Journal of Lean Six Sigma, 4(3), 321-337. http://dx.doi.org/10.1108/IJLSS-05-2013-0029.
http://dx.doi.org/10.1108/IJLSS-05-2013-...
; Lim et al., 2014Lim, S. A. H., Antony, J., & Albliwi, S. (2014). Statistical Process Control in the food industry–A systematic review and future research agenda. Trends in Food Science & Technology, 37(2), 137-151. http://dx.doi.org/10.1016/j.tifs.2014.03.010.
http://dx.doi.org/10.1016/j.tifs.2014.03...
; 2016Lim, S. A. H., Antony, J., & Arshed, N. (2016). A Critical Assessment on SPC Implementation in the UK Food Industry. Systemics. Cybernetics and Informatics, 14(1), 37-42. Retrieved in 8 September 2016, from http://www.iiisci.org/journal/CV$/sci/pdfs/SA430BZ15.pdf
http://www.iiisci.org/journal/CV$/sci/pd...
; Sharma & Kharub, 2014Sharma, R., & Kharub, M. (2014). Attaining competitive positioning through SPC – an experimental investigation from SME. Measuring Business Excellence, 18(4), 86-103. http://dx.doi.org/10.1108/MBE-10-2013-0050.
http://dx.doi.org/10.1108/MBE-10-2013-00...
). The third CSF is “Team work”, for SPC implementation is important to have a specific working group with leaders, a board of directors committee and an operational team to lead, coordinate and carry out the implementation (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
; Rungtusanatham et al., 1999Rungtusanatham, M., Anderson, J. C., & Dooley, K. J. (1999). Towards measuring the “SPC implementation/practice” construct: some evidence of measurement quality. International Journal of Quality & Reliability Management, 16(4), 301-329. http://dx.doi.org/10.1108/02656719910239938.
http://dx.doi.org/10.1108/02656719910239...
; Xie & Goh, 1999Xie, M., & Goh, T. N. (1999). Statistical techniques for quality. The TQM Magazine, 11(4), 238-242. http://dx.doi.org/10.1108/09544789910272913.
http://dx.doi.org/10.1108/09544789910272...
; Mason & Antony, 2000Mason, B., & Antony, J. (2000). Statistical process control: an essential ingredient for improving service and manufacturing quality. Managing Service Quality: An International Journal, 10(4), 233-238. http://dx.doi.org/10.1108/09604520010341618.
http://dx.doi.org/10.1108/09604520010341...
; Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
; Rungasamy et al., 2002Rungasamy, S., Antony, J., & Ghosh, S. (2002). Critical success factors for SPC implementation in UK small and medium enterprises: some key findings from a survey. The TQM Magazine, 14(4), 217-224. http://dx.doi.org/10.1108/09544780210429825.
http://dx.doi.org/10.1108/09544780210429...
; Chen et al., 2008Chen, S. H., Yang, C. C., Lin, W. T., & Yeh, T. M. (2008). Performance evaluation for introducing statistical process control to the liquid crystal display industry. International Journal of Production Economics, 111(1), 80-92. http://dx.doi.org/10.1016/j.ijpe.2006.12.055.
http://dx.doi.org/10.1016/j.ijpe.2006.12...
; Elg et al., 2008Elg, M., Olsson, J., & Dahlgaard, J. (2008). Implementing statistical process control: an organizational perspective. International Journal of Quality & Reliability Management, 25(6), 545-560. http://dx.doi.org/10.1108/02656710810881872.
http://dx.doi.org/10.1108/02656710810881...
; Phyanthamilkumaran & Fernando, 2008Phyanthamilkumaran, S. Z., & Fernando, Y. (2008). The role of cultural change in the relationship between critical factors with the success of Statistical Process Control (SPC) projects. Proceedings of Annual London Conference on Money, Economy and Management, 3(4), 1-11.; Putri & Yusof, 2008Putri, T. N., & Yusof, S. R. M. (2008). Critical success factors for implementing quality engineering (QE) in Malaysian’s and Indonesian’s automotive industries: a proposed model. International Journal of Automotive Industry and Management, 2, 1-15. Retrieved in 8 September 2016, from http://kari.hyundai.com/karifile/IJAIM_reports/Vol2_No2/vol2_no2_01_Critical%20Success%20Factors%20for%20Implementing%20Quality%20Engineering%20(QE)%20In%20Malaysian's%20and%20Indonesian's%20Automotive%20Industries-A%20Proposed%20Model.pdf
http://kari.hyundai.com/karifile/IJAIM_r...
; 2009Putri, N. T., & Yusof, S. M. (2009). Critical success factors for implementing quality engineering tools and techniques in malaysian’s and indonesian’s automotive industries: an exploratory study. In Proceedings of the International MultiConference of Engineers and Computer Scientists (pp. 18-20), Hong Kong, China.; Rohani et al., 2009aRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009a). The relationship between statistical process control critical success factors and performance: a structural equation modeling approach. In Proceedings of the 2009 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1352-1356), Hong Kong, China. http://dx.doi.org/10.1109/ieem.2009.5373033.
http://dx.doi.org/10.1109/ieem.2009.5373...
, bRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009b). Statistical process control success factors and performance: an exploratory analysis. In Proceedings of the Advances in Quality Engineering and Management Reserch, Malaysia. Retrieved in 8 September 2016, from http://eprints.uthm.edu.my/2571/
http://eprints.uthm.edu.my/2571/...
; 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
; Mahanti & Evans, 2012Mahanti, R., & Evans, J. R. (2012). Critical success factors for implementing statistical process control in the software industry. Benchmarking: An International Journal, 19(3), 374-394. http://dx.doi.org/10.1108/14635771211244309.
http://dx.doi.org/10.1108/14635771211244...
; Lim & Antony, 2013Lim, S. A. H., & Antony, J. (2013). A conceptual readiness framework for statistical process control deployment. In Proceedings of the IEEE International Conference Industrial Engineering and Engineering Management (pp. 300-304), Bangkok, Thailand. http://dx.doi.org/10.1109/ieem.2013.6962422.
http://dx.doi.org/10.1109/ieem.2013.6962...
; Rantamäki et al., 2013Rantamäki, J., Tiainen, E. L., & Kässi, T. (2013). A case of implementing SPC in a pulp mill. International Journal of Lean Six Sigma, 4(3), 321-337. http://dx.doi.org/10.1108/IJLSS-05-2013-0029.
http://dx.doi.org/10.1108/IJLSS-05-2013-...
).

The fourth and fifth CSF are related to technical aspects of the SPC implementation; “Identification and measurement of critical product characteristics”, which involves identification and measurement of characteristics that impact the client and generate significant quality problems (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
; Rungtusanatham et al., 1999Rungtusanatham, M., Anderson, J. C., & Dooley, K. J. (1999). Towards measuring the “SPC implementation/practice” construct: some evidence of measurement quality. International Journal of Quality & Reliability Management, 16(4), 301-329. http://dx.doi.org/10.1108/02656719910239938.
http://dx.doi.org/10.1108/02656719910239...
; Mason & Antony, 2000Mason, B., & Antony, J. (2000). Statistical process control: an essential ingredient for improving service and manufacturing quality. Managing Service Quality: An International Journal, 10(4), 233-238. http://dx.doi.org/10.1108/09604520010341618.
http://dx.doi.org/10.1108/09604520010341...
; Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
; Rungasamy et al., 2002Rungasamy, S., Antony, J., & Ghosh, S. (2002). Critical success factors for SPC implementation in UK small and medium enterprises: some key findings from a survey. The TQM Magazine, 14(4), 217-224. http://dx.doi.org/10.1108/09544780210429825.
http://dx.doi.org/10.1108/09544780210429...
; Antony & Taner, 2003Antony, J., & Taner, T. (2003). A conceptual framework for the effective implementation of statistical process control. Business Process Management Journal, 9(4), 473-489. http://dx.doi.org/10.1108/14637150310484526.
http://dx.doi.org/10.1108/14637150310484...
; Grigg & Walls, 2007bGrigg, N., & Walls, L. (2007b). The role of control charts in promoting organisational learning: New perspectives from a food industry study. The TQM Magazine, 19(1), 37-49. http://dx.doi.org/10.1108/09544780710720826.
http://dx.doi.org/10.1108/09544780710720...
; Chen et al., 2008Chen, S. H., Yang, C. C., Lin, W. T., & Yeh, T. M. (2008). Performance evaluation for introducing statistical process control to the liquid crystal display industry. International Journal of Production Economics, 111(1), 80-92. http://dx.doi.org/10.1016/j.ijpe.2006.12.055.
http://dx.doi.org/10.1016/j.ijpe.2006.12...
; Elg et al., 2008Elg, M., Olsson, J., & Dahlgaard, J. (2008). Implementing statistical process control: an organizational perspective. International Journal of Quality & Reliability Management, 25(6), 545-560. http://dx.doi.org/10.1108/02656710810881872.
http://dx.doi.org/10.1108/02656710810881...
; Rohani et al., 2009aRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009a). The relationship between statistical process control critical success factors and performance: a structural equation modeling approach. In Proceedings of the 2009 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1352-1356), Hong Kong, China. http://dx.doi.org/10.1109/ieem.2009.5373033.
http://dx.doi.org/10.1109/ieem.2009.5373...
, bRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009b). Statistical process control success factors and performance: an exploratory analysis. In Proceedings of the Advances in Quality Engineering and Management Reserch, Malaysia. Retrieved in 8 September 2016, from http://eprints.uthm.edu.my/2571/
http://eprints.uthm.edu.my/2571/...
; 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
; Mahanti & Evans, 2012Mahanti, R., & Evans, J. R. (2012). Critical success factors for implementing statistical process control in the software industry. Benchmarking: An International Journal, 19(3), 374-394. http://dx.doi.org/10.1108/14635771211244309.
http://dx.doi.org/10.1108/14635771211244...
; Lim & Antony, 2013Lim, S. A. H., & Antony, J. (2013). A conceptual readiness framework for statistical process control deployment. In Proceedings of the IEEE International Conference Industrial Engineering and Engineering Management (pp. 300-304), Bangkok, Thailand. http://dx.doi.org/10.1109/ieem.2013.6962422.
http://dx.doi.org/10.1109/ieem.2013.6962...
; Rantamäki et al., 2013Rantamäki, J., Tiainen, E. L., & Kässi, T. (2013). A case of implementing SPC in a pulp mill. International Journal of Lean Six Sigma, 4(3), 321-337. http://dx.doi.org/10.1108/IJLSS-05-2013-0029.
http://dx.doi.org/10.1108/IJLSS-05-2013-...
; Sharma & Kharub, 2014Sharma, R., & Kharub, M. (2014). Attaining competitive positioning through SPC – an experimental investigation from SME. Measuring Business Excellence, 18(4), 86-103. http://dx.doi.org/10.1108/MBE-10-2013-0050.
http://dx.doi.org/10.1108/MBE-10-2013-00...
); and “Definition and correct application of control charts” (selection of appropriate control chart, sampling, etc), this factor points out that should be proper selection of the chart, which depends on the type of variable to be analyzed, the data to be collected and the process (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
; Rungtusanatham et al., 1999Rungtusanatham, M., Anderson, J. C., & Dooley, K. J. (1999). Towards measuring the “SPC implementation/practice” construct: some evidence of measurement quality. International Journal of Quality & Reliability Management, 16(4), 301-329. http://dx.doi.org/10.1108/02656719910239938.
http://dx.doi.org/10.1108/02656719910239...
; Mason & Antony, 2000Mason, B., & Antony, J. (2000). Statistical process control: an essential ingredient for improving service and manufacturing quality. Managing Service Quality: An International Journal, 10(4), 233-238. http://dx.doi.org/10.1108/09604520010341618.
http://dx.doi.org/10.1108/09604520010341...
; Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
; Rungasamy et al., 2002Rungasamy, S., Antony, J., & Ghosh, S. (2002). Critical success factors for SPC implementation in UK small and medium enterprises: some key findings from a survey. The TQM Magazine, 14(4), 217-224. http://dx.doi.org/10.1108/09544780210429825.
http://dx.doi.org/10.1108/09544780210429...
; Antony & Taner, 2003Antony, J., & Taner, T. (2003). A conceptual framework for the effective implementation of statistical process control. Business Process Management Journal, 9(4), 473-489. http://dx.doi.org/10.1108/14637150310484526.
http://dx.doi.org/10.1108/14637150310484...
; Grigg & Walls, 2007bGrigg, N., & Walls, L. (2007b). The role of control charts in promoting organisational learning: New perspectives from a food industry study. The TQM Magazine, 19(1), 37-49. http://dx.doi.org/10.1108/09544780710720826.
http://dx.doi.org/10.1108/09544780710720...
; Chen et al., 2008Chen, S. H., Yang, C. C., Lin, W. T., & Yeh, T. M. (2008). Performance evaluation for introducing statistical process control to the liquid crystal display industry. International Journal of Production Economics, 111(1), 80-92. http://dx.doi.org/10.1016/j.ijpe.2006.12.055.
http://dx.doi.org/10.1016/j.ijpe.2006.12...
; Elg et al., 2008Elg, M., Olsson, J., & Dahlgaard, J. (2008). Implementing statistical process control: an organizational perspective. International Journal of Quality & Reliability Management, 25(6), 545-560. http://dx.doi.org/10.1108/02656710810881872.
http://dx.doi.org/10.1108/02656710810881...
; Phyanthamilkumaran & Fernando, 2008Phyanthamilkumaran, S. Z., & Fernando, Y. (2008). The role of cultural change in the relationship between critical factors with the success of Statistical Process Control (SPC) projects. Proceedings of Annual London Conference on Money, Economy and Management, 3(4), 1-11.; Putri & Yusof, 2008Putri, T. N., & Yusof, S. R. M. (2008). Critical success factors for implementing quality engineering (QE) in Malaysian’s and Indonesian’s automotive industries: a proposed model. International Journal of Automotive Industry and Management, 2, 1-15. Retrieved in 8 September 2016, from http://kari.hyundai.com/karifile/IJAIM_reports/Vol2_No2/vol2_no2_01_Critical%20Success%20Factors%20for%20Implementing%20Quality%20Engineering%20(QE)%20In%20Malaysian's%20and%20Indonesian's%20Automotive%20Industries-A%20Proposed%20Model.pdf
http://kari.hyundai.com/karifile/IJAIM_r...
; Rohani et al., 2009aRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009a). The relationship between statistical process control critical success factors and performance: a structural equation modeling approach. In Proceedings of the 2009 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1352-1356), Hong Kong, China. http://dx.doi.org/10.1109/ieem.2009.5373033.
http://dx.doi.org/10.1109/ieem.2009.5373...
; 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
; Mahanti & Evans, 2012Mahanti, R., & Evans, J. R. (2012). Critical success factors for implementing statistical process control in the software industry. Benchmarking: An International Journal, 19(3), 374-394. http://dx.doi.org/10.1108/14635771211244309.
http://dx.doi.org/10.1108/14635771211244...
; Lim & Antony, 2013Lim, S. A. H., & Antony, J. (2013). A conceptual readiness framework for statistical process control deployment. In Proceedings of the IEEE International Conference Industrial Engineering and Engineering Management (pp. 300-304), Bangkok, Thailand. http://dx.doi.org/10.1109/ieem.2013.6962422.
http://dx.doi.org/10.1109/ieem.2013.6962...
).

The sixth CSF is “Cultural change and communication”, this factor considers that behavioral and resistance to change issues must be considered; operators, engineers and managers need to be aware of the benefits of the SPC for the continuous improvement of products and processes and to base its actions on facts and data (Xie & Goh, 1999Xie, M., & Goh, T. N. (1999). Statistical techniques for quality. The TQM Magazine, 11(4), 238-242. http://dx.doi.org/10.1108/09544789910272913.
http://dx.doi.org/10.1108/09544789910272...
; Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
; Rungasamy et al., 2002Rungasamy, S., Antony, J., & Ghosh, S. (2002). Critical success factors for SPC implementation in UK small and medium enterprises: some key findings from a survey. The TQM Magazine, 14(4), 217-224. http://dx.doi.org/10.1108/09544780210429825.
http://dx.doi.org/10.1108/09544780210429...
; Chen et al., 2008Chen, S. H., Yang, C. C., Lin, W. T., & Yeh, T. M. (2008). Performance evaluation for introducing statistical process control to the liquid crystal display industry. International Journal of Production Economics, 111(1), 80-92. http://dx.doi.org/10.1016/j.ijpe.2006.12.055.
http://dx.doi.org/10.1016/j.ijpe.2006.12...
; Elg et al., 2008Elg, M., Olsson, J., & Dahlgaard, J. (2008). Implementing statistical process control: an organizational perspective. International Journal of Quality & Reliability Management, 25(6), 545-560. http://dx.doi.org/10.1108/02656710810881872.
http://dx.doi.org/10.1108/02656710810881...
; Phyanthamilkumaran & Fernando, 2008Phyanthamilkumaran, S. Z., & Fernando, Y. (2008). The role of cultural change in the relationship between critical factors with the success of Statistical Process Control (SPC) projects. Proceedings of Annual London Conference on Money, Economy and Management, 3(4), 1-11.; Putri & Yusof, 2008Putri, T. N., & Yusof, S. R. M. (2008). Critical success factors for implementing quality engineering (QE) in Malaysian’s and Indonesian’s automotive industries: a proposed model. International Journal of Automotive Industry and Management, 2, 1-15. Retrieved in 8 September 2016, from http://kari.hyundai.com/karifile/IJAIM_reports/Vol2_No2/vol2_no2_01_Critical%20Success%20Factors%20for%20Implementing%20Quality%20Engineering%20(QE)%20In%20Malaysian's%20and%20Indonesian's%20Automotive%20Industries-A%20Proposed%20Model.pdf
http://kari.hyundai.com/karifile/IJAIM_r...
; 2009Putri, N. T., & Yusof, S. M. (2009). Critical success factors for implementing quality engineering tools and techniques in malaysian’s and indonesian’s automotive industries: an exploratory study. In Proceedings of the International MultiConference of Engineers and Computer Scientists (pp. 18-20), Hong Kong, China.; Rohani et al., 2009aRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009a). The relationship between statistical process control critical success factors and performance: a structural equation modeling approach. In Proceedings of the 2009 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1352-1356), Hong Kong, China. http://dx.doi.org/10.1109/ieem.2009.5373033.
http://dx.doi.org/10.1109/ieem.2009.5373...
, bRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009b). Statistical process control success factors and performance: an exploratory analysis. In Proceedings of the Advances in Quality Engineering and Management Reserch, Malaysia. Retrieved in 8 September 2016, from http://eprints.uthm.edu.my/2571/
http://eprints.uthm.edu.my/2571/...
; 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
; Mahanti & Evans, 2012Mahanti, R., & Evans, J. R. (2012). Critical success factors for implementing statistical process control in the software industry. Benchmarking: An International Journal, 19(3), 374-394. http://dx.doi.org/10.1108/14635771211244309.
http://dx.doi.org/10.1108/14635771211244...
; Lim & Antony, 2013Lim, S. A. H., & Antony, J. (2013). A conceptual readiness framework for statistical process control deployment. In Proceedings of the IEEE International Conference Industrial Engineering and Engineering Management (pp. 300-304), Bangkok, Thailand. http://dx.doi.org/10.1109/ieem.2013.6962422.
http://dx.doi.org/10.1109/ieem.2013.6962...
; 2014Lim, S. A. H., & Antony, J. (2014). The implementation of statistical process control in the food industry: a systematic review. In Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management (pp. 1682-1691), Bali, Indonesia.; Lim et al., 2014Lim, S. A. H., Antony, J., & Albliwi, S. (2014). Statistical Process Control in the food industry–A systematic review and future research agenda. Trends in Food Science & Technology, 37(2), 137-151. http://dx.doi.org/10.1016/j.tifs.2014.03.010.
http://dx.doi.org/10.1016/j.tifs.2014.03...
; Sharma & Kharub, 2014Sharma, R., & Kharub, M. (2014). Attaining competitive positioning through SPC – an experimental investigation from SME. Measuring Business Excellence, 18(4), 86-103. http://dx.doi.org/10.1108/MBE-10-2013-0050.
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).

The seventh and eighth factors are also technical: “Measurement system analysis in relation to its capability and applicability” (process of measuring the quality characteristics must be analyzed considering the effect of the inspector, the measuring instrument and the interactions between these factors) (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
; Rungtusanatham et al., 1999Rungtusanatham, M., Anderson, J. C., & Dooley, K. J. (1999). Towards measuring the “SPC implementation/practice” construct: some evidence of measurement quality. International Journal of Quality & Reliability Management, 16(4), 301-329. http://dx.doi.org/10.1108/02656719910239938.
http://dx.doi.org/10.1108/02656719910239...
; Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
; Rungasamy et al., 2002Rungasamy, S., Antony, J., & Ghosh, S. (2002). Critical success factors for SPC implementation in UK small and medium enterprises: some key findings from a survey. The TQM Magazine, 14(4), 217-224. http://dx.doi.org/10.1108/09544780210429825.
http://dx.doi.org/10.1108/09544780210429...
; Antony &Taner, 2003Antony, J., & Taner, T. (2003). A conceptual framework for the effective implementation of statistical process control. Business Process Management Journal, 9(4), 473-489. http://dx.doi.org/10.1108/14637150310484526.
http://dx.doi.org/10.1108/14637150310484...
; Grigg & Walls, 2007aGrigg, N., & Walls, L. (2007a). Developing statistical thinking for performance improvement in the food industry. International Journal of Quality & Reliability Management, 24(4), 347-369. http://dx.doi.org/10.1108/02656710710740536.
http://dx.doi.org/10.1108/02656710710740...
, bGrigg, N., & Walls, L. (2007b). The role of control charts in promoting organisational learning: New perspectives from a food industry study. The TQM Magazine, 19(1), 37-49. http://dx.doi.org/10.1108/09544780710720826.
http://dx.doi.org/10.1108/09544780710720...
; Chen et al., 2008Chen, S. H., Yang, C. C., Lin, W. T., & Yeh, T. M. (2008). Performance evaluation for introducing statistical process control to the liquid crystal display industry. International Journal of Production Economics, 111(1), 80-92. http://dx.doi.org/10.1016/j.ijpe.2006.12.055.
http://dx.doi.org/10.1016/j.ijpe.2006.12...
; Rohani et al., 2009bRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009b). Statistical process control success factors and performance: an exploratory analysis. In Proceedings of the Advances in Quality Engineering and Management Reserch, Malaysia. Retrieved in 8 September 2016, from http://eprints.uthm.edu.my/2571/
http://eprints.uthm.edu.my/2571/...
; 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
; Mahanti & Evans, 2012Mahanti, R., & Evans, J. R. (2012). Critical success factors for implementing statistical process control in the software industry. Benchmarking: An International Journal, 19(3), 374-394. http://dx.doi.org/10.1108/14635771211244309.
http://dx.doi.org/10.1108/14635771211244...
; Lim & Antony, 2013Lim, S. A. H., & Antony, J. (2013). A conceptual readiness framework for statistical process control deployment. In Proceedings of the IEEE International Conference Industrial Engineering and Engineering Management (pp. 300-304), Bangkok, Thailand. http://dx.doi.org/10.1109/ieem.2013.6962422.
http://dx.doi.org/10.1109/ieem.2013.6962...
; Rantamäki et al., 2013Rantamäki, J., Tiainen, E. L., & Kässi, T. (2013). A case of implementing SPC in a pulp mill. International Journal of Lean Six Sigma, 4(3), 321-337. http://dx.doi.org/10.1108/IJLSS-05-2013-0029.
http://dx.doi.org/10.1108/IJLSS-05-2013-...
; Lim et al., 2016Lim, S. A. H., Antony, J., & Arshed, N. (2016). A Critical Assessment on SPC Implementation in the UK Food Industry. Systemics. Cybernetics and Informatics, 14(1), 37-42. Retrieved in 8 September 2016, from http://www.iiisci.org/journal/CV$/sci/pdfs/SA430BZ15.pdf
http://www.iiisci.org/journal/CV$/sci/pd...
) and “Process definition and prioritization, focusing on waste, rework or variability problems” (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
; Xie & Goh, 1999Xie, M., & Goh, T. N. (1999). Statistical techniques for quality. The TQM Magazine, 11(4), 238-242. http://dx.doi.org/10.1108/09544789910272913.
http://dx.doi.org/10.1108/09544789910272...
; Antony et al., 2000Antony, J., Balbontin, A., & Taner, T. (2000). Key ingredients for the effective implementation of statistical process control. International Journal of Productivity and Performance Management, 49(6), 242-247. http://dx.doi.org/10.1108/00438020010343417.
http://dx.doi.org/10.1108/00438020010343...
; Rungasamy et al., 2002Rungasamy, S., Antony, J., & Ghosh, S. (2002). Critical success factors for SPC implementation in UK small and medium enterprises: some key findings from a survey. The TQM Magazine, 14(4), 217-224. http://dx.doi.org/10.1108/09544780210429825.
http://dx.doi.org/10.1108/09544780210429...
; Chen et al., 2008Chen, S. H., Yang, C. C., Lin, W. T., & Yeh, T. M. (2008). Performance evaluation for introducing statistical process control to the liquid crystal display industry. International Journal of Production Economics, 111(1), 80-92. http://dx.doi.org/10.1016/j.ijpe.2006.12.055.
http://dx.doi.org/10.1016/j.ijpe.2006.12...
; Elg et al., 2008Elg, M., Olsson, J., & Dahlgaard, J. (2008). Implementing statistical process control: an organizational perspective. International Journal of Quality & Reliability Management, 25(6), 545-560. http://dx.doi.org/10.1108/02656710810881872.
http://dx.doi.org/10.1108/02656710810881...
; Rohani et al., 2009aRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009a). The relationship between statistical process control critical success factors and performance: a structural equation modeling approach. In Proceedings of the 2009 IEEE International Conference on Industrial Engineering and Engineering Management (pp. 1352-1356), Hong Kong, China. http://dx.doi.org/10.1109/ieem.2009.5373033.
http://dx.doi.org/10.1109/ieem.2009.5373...
, bRohani, J. M., Yusof, S. R. M., & Mohamad, I. (2009b). Statistical process control success factors and performance: an exploratory analysis. In Proceedings of the Advances in Quality Engineering and Management Reserch, Malaysia. Retrieved in 8 September 2016, from http://eprints.uthm.edu.my/2571/
http://eprints.uthm.edu.my/2571/...
; 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
; Mahanti & Evans, 2012Mahanti, R., & Evans, J. R. (2012). Critical success factors for implementing statistical process control in the software industry. Benchmarking: An International Journal, 19(3), 374-394. http://dx.doi.org/10.1108/14635771211244309.
http://dx.doi.org/10.1108/14635771211244...
; Lim & Antony, 2013Lim, S. A. H., & Antony, J. (2013). A conceptual readiness framework for statistical process control deployment. In Proceedings of the IEEE International Conference Industrial Engineering and Engineering Management (pp. 300-304), Bangkok, Thailand. http://dx.doi.org/10.1109/ieem.2013.6962422.
http://dx.doi.org/10.1109/ieem.2013.6962...
).

These and the others factors and the corresponding authors are listed in Table 2, following the highest to lowest number of citations, it is also presented a brief definition of these factors and the percentage of authors who cite.

Table 2
Compilation of the CSF found in SLR.

There is a convergent opinion on the importance of these CSF for the implementation of SPC, both in academy as in managers (Rohani et al., 2010Rohani, J. M., Yusof, S. R. M., & Mohamad, I. (2010). The development of a survey instrument for measuring a relationship between statistical process control success factors and performance. Jurnal Mekanikal, 30, 1-16. Retrieved in 8 September 2016, from http://s3.amazonaws.com/academia.edu.documents/41145791/The_development_of_a_survey_instrument_f20160114-15835-1ffuvz1.pdf?AWSAccessKeyId=AKIAJ56TQJRTWSMTNPEA&Expires=1472739132&Signature=MUN%2FuZmuKzRKEldEFgaA0YxvHgI%3D&response-content-disposition=inline%3B%20filename%3DThe_development_of_a_survey_instrument_f.pdf
http://s3.amazonaws.com/academia.edu.doc...
). This list of factors summarizes the arguments of authors and will be the reference adopted in research reported in this paper.

Some authors propose methodologies for SPC Implementation. Krumwiede & Sheu (1996)Krumwiede, D., & Sheu, C. (1996). Implementing SPC in a small organization: a TQM approach. Integrated Manufacturing Systems, 7(1), 45-51. http://dx.doi.org/10.1108/09576069610108435.
http://dx.doi.org/10.1108/09576069610108...
present six steps for implementation: getting support from senior management, choosing a leader of the SPC, determination of the production process for the pilot study, process documentation preparation, training in SPC and the construction of control charts.

Kumar & Motwani (1996)Kumar, A., & Motwani, J. (1996). Doing it right the second time. Industrial Management & Data Systems, 96(6), 14-19. http://dx.doi.org/10.1108/02635579610126818.
http://dx.doi.org/10.1108/02635579610126...
suggest 16 steps to lead to the implementation, ranging from staff training for deployment to actions for process control. Does et al. (1997)Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
present a model with four phases, involving awareness, pilot projects, full implementation and total quality. Mason & Antony (2000)Mason, B., & Antony, J. (2000). Statistical process control: an essential ingredient for improving service and manufacturing quality. Managing Service Quality: An International Journal, 10(4), 233-238. http://dx.doi.org/10.1108/09604520010341618.
http://dx.doi.org/10.1108/09604520010341...
and Antony & Taner (2003)Antony, J., & Taner, T. (2003). A conceptual framework for the effective implementation of statistical process control. Business Process Management Journal, 9(4), 473-489. http://dx.doi.org/10.1108/14637150310484526.
http://dx.doi.org/10.1108/14637150310484...
propose a conceptual model for the implementation of the SPC, developed from the critical analysis of publications on the subject, which focuses on four key areas: management issues, engineering skills, statistical knowledge and skills for group work. In general, these models for SPC implementation include some of the CSF mentioned.

The problems faced in implementation are also related to CSF: it needs to invest time, money and training in the implementation of the SPC (Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
); it needs constant attention and Senior Management support (Antony & Taner, 2003Antony, J., & Taner, T. (2003). A conceptual framework for the effective implementation of statistical process control. Business Process Management Journal, 9(4), 473-489. http://dx.doi.org/10.1108/14637150310484526.
http://dx.doi.org/10.1108/14637150310484...
; Does et al., 1997Does, R. J. M. M., Trip, A., & Schippers, W. A. J. (1997). A framework for implementation of statistical process control. International Journal of Quality Science, 2(3), 181-198. http://dx.doi.org/10.1108/13598539710170821.
http://dx.doi.org/10.1108/13598539710170...
); it is important the effective use and correct interpretation of control charts; it must overcome the difficulties in the use of statistics to build the chart, understanding and identification of corrective actions; it is important to plan for the implementation of the SPC and the management after implementation (Antony & Taner, 2003Antony, J., & Taner, T. (2003). A conceptual framework for the effective implementation of statistical process control. Business Process Management Journal, 9(4), 473-489. http://dx.doi.org/10.1108/14637150310484526.
http://dx.doi.org/10.1108/14637150310484...
). The identification of CSF for the implementation of the SPC is crucial, but only the consideration of factors is not enough, they must be connected in a coherent plan (Lim & Antony, 2014Lim, S. A. H., & Antony, J. (2014). The implementation of statistical process control in the food industry: a systematic review. In Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management (pp. 1682-1691), Bali, Indonesia.).

3. Research method

The method used for field research was the emancipatory action research, considering the company's interest in conducting a learning experience and participation of operational staff and technical support in the implementation and consolidation of the SPC in a chemical processing unit. The method determines the researcher to share responsibilities with the other participants and enables organizational learning.

The company had already conducted an implementation of SPC in the past, which was not successful and decided to hold a new experience observing the CSF. This represented an opportunity to conduct a research on the implementation and verify in loco the theory of CSF for SPC.

Action research is a cyclical process with well-defined phases to plan the intervention, collect, analyze data, plan and perform the intervention. After the implementation of the actions there is the evaluation and returns to the beginning of the cycle with the planning. The research stages (Figure 1) were based on Coughlan & Coghlan (2002)Coughlan, P., & Coghlan, D. (2002). Action research for operations management. International Journal of Operations & Production Management, 22(2), 220-240. http://dx.doi.org/10.1108/01443570210417515.
http://dx.doi.org/10.1108/01443570210417...
.

Figure 1
Overall scheme of action research. Source: Adapted from Coughlan & Coghlan (2002)Coughlan, P., & Coghlan, D. (2002). Action research for operations management. International Journal of Operations & Production Management, 22(2), 220-240. http://dx.doi.org/10.1108/01443570210417515.
http://dx.doi.org/10.1108/01443570210417...
.

The Pre-Planning Step aimed the understanding of the research context and definition of purpose. It included the survey of the theoretical framework for the action research, the CSF, the understanding of the company’s history with the use of control charts and its organizational environment, the choice of the process to the action research application and identification of expectations of the involved team.

The data collection phase aimed to carry out visits and meetings with the action research team and observe the existence of the CSF in the unit. In the feedback stage, the objective was to discuss with the team the information and data collected. The data analysis enabled the interpretation of the collected data, assisted in the prioritization of selected actions for the next step, the action plan, in which the actions, deadline and responsible for the effective implementation of the SPC were defined. The fifth step was the implementation of actions and identification of the generated results, followed by the action evaluation step, which involves discussion of the effectiveness of actions implemented and whether they have met the expectations. At each step was performed a continuous monitoring, communicating to staff through formal presentations of the research, the actions performed and their evaluation.

It was conducted three cycles of all the six steps and the action research monitoring.

4. Action research

4.1. Pre-planning step

In pre-planning step, the researcher held meetings with the Production Manager, the Production Coordinator, who is responsible for the operational teams and the Process Manager, who is responsible for technical improvements in the plant.

Initially, it was explained to the researcher who in the past have already tried to adopt SPC charts, but unsuccessful in its continuity. Many operators at the time of these initiatives are still part of the current team and could generate resistance.

It has formed a monitoring group to support action research, with the participation of the researcher, Production Manager, Process Manager and Industrial Manager.

At this stage the expectations were identified: to understand the failures of past initiatives; involve all the plant workers; generate clear procedure for operational use of control charts and embed it to the ISO 9000 Quality System (International Organization for Standardization, 2015International Organization for Standardization. (2015). ISO 9001: 2015: quality management systems: requirements. Geneva: ISO.); the variables to be monitored should be important to the operation result (customer satisfaction) and the utilization of the software for using the chart should be easy.

The purpose of action research, set with the Monitoring Group, was the implementation of control charts with the use of the CSF and the assessment of their effective incorporation into the operators’ work routine. The aims of the action research and team expectations were released for the entire organization.

The Monitoring Group decided that the research was a pilot project focused on a specific process. Silica production was chosen by the potential improvements generated by the control. Only after the results of the research, with the actions implemented, it would start institutionalization of the SPC.

4.2. First cycle of action research

This cycle was performed in order to identify the expectations and barriers by operators and production leaders in relation to the charts and start the implementation.

4.2.1. Data collection and feedback

Data collection involved individual interviews with some members of the operating team and three formal meetings with shift leaders and operators separately. The purpose of separating the leadership was not inhibit operators in relation to providing information on past experiences in the use of control charts and on their expectations and difficulties. It sought to identify and understand, from the perspective of operators, the possible restraints, as in the opinion of the leaders, operators have the perception that the use of control charts is reserved for engineers and managers. The leaders warned that in previous experiments the operators had no control over the chosen variable, therefore, the choice of the process and the variable has been identified as important to success.

It was detected the concern of operators with the amount of data to be read, if the control chart would be done by hand (paper) or through some software, how often they should monitor the variable and the responsibility of operators to the variable behavior. It was perceived that the working procedure, in the case of the presence of special cause indication, was considered by operators as a critical factor.

In one of the meetings between researchers and operators, there was a brief presentation of the concepts of SPC and the opportunity was used to detect the interest of operators on training in SPC. It also was discussed the interest of teamwork for implementation of control charts and the use of facilitators. The proposals were accepted without restrictions by operators and are very important for the implementation.

Another important aspect was to report to operators and leaders that this project would be considered as a pilot, the results would be analyzed for replication in other plants and processes.

The data obtained after the meetings were organized in a document submitted to the Monitoring Group. This information was also communicated to other stakeholders, such as Production Managers from other plants.

4.2.2. Data analysis, action plans and execution

After the data analysis was decided by the Monitoring Group, that at this first moment the following factors would be focused on: Commitment and senior management responsibility; Pilot project use; SPC implementation team; Facilitator use; Definition and prioritization of the process to be focused; Education and training in SPC; Definition of the critical quality characteristic and Management of cultural change. Table 3 presents the results of the analysis and the actions.

Table 3
Situation analysis and proposed actions.

The chosen critical quality characteristic was a variable with direct impact on the natural gas consumption of the factory. In the silica process, there is a step where the suspension is filtered through a filter-press and then pass through a gas dryer. The humidity of the silica at the end of the filtration is important, as it impacts on gas consumption in the dryer and correlates with the pressure applied to the filter plates. It was defined as variable to be controlled, the pressure applied to the filtration plates. The control chart would have as an objective to monitor the filtration process to ensure low humidity level and lower gas consumption for drying. Figure 2 illustrates the focus process for the implementation of the control chart.

Figure 2
Process Flow with SPC Chart Focus Indication. Source: Authors.

The motivation to have a statistically controlled variable is that, despite being a stable operation, if there are problems in the pressurization system of the plates, hardly, the operators will immediately detect because the pressure will gradually reduce until it is perceived that the humidity of the silica in the dryer entry is high.

4.2.3. Evaluation and monitoring after the first cycle of action research

The facilitator's role proved to be essential to the connection between the Monitoring Group and the SPC team and to answer questions of the operators. There was a need for a clear definition of its functions, so that there was no conflict with other leaders. It was also noted the strong influence of the company culture and the plant's own staff in the actions. The engagement of leaders proved essential in the first cycle, as there was between them the belief that research would bring benefits to all. In this first cycle it was observed the expectation created by the operators about what would happen in the coming months.

For the Monitoring Group, the first cycle of action research implantation helped strengthen the existing theoretical framework in the group, increasing the knowledge to the next steps.

4.3. Second cycle of action research

4.3.1. Data collection and feedback

For the pilot project, other implementation steps have been introduced by SPC team, for example, the measuring system validation. The team identified two aspects, one technical and other behavioral. As regards the technical side, the measurements must be validated statistically by means of a study of repeatability and reproducibility, compared to the inherent variability of the measurement in relation to process variability or tolerance (upper and lower specification limits) to be achieved by facilitator. The behavioral aspect concerns the perception of the reliability of measurements by operators. It is not enough to show through calculations and documents that the measuring system is suitable if, on a daily routine operators do not trust the measurement. To identify behavioral problems, it was asked if any measurement or measuring system was not trusted and had suggestions for improvement.

The next step was the definition and correct application of the control chart. It was decided along with the SPC team, from the simplest type, with the mean chart for the filtration cycle pressure control, which lasts 60 minutes. In two meetings with the process and production engineers, a proposal to monitor and plot the mean compression pressure in the last three minutes of the filtration cycle came up, because the most important to the process is the final pressure applied to silica plates. The need to conduct an analysis of autocorrelation has been raised, since according to Montgomery (2014)Montgomery, D. C. (2014). Introdução ao controle estatístico da qualidade (4th ed.). Rio de Janeiro: Gen-LTC. the most important premise for control charts is the independence of the observations.

Another problem associated with CSF was the software for the control chart. In interviews with operators, all of them dismissed to manually do the control chart. Data collection and calculations would be laborious. During group meetings operators suggested a spreadsheet in Excel® to be used, the lack of control indication rules were shown in the worksheet and, if possible, be alerted when the next phase could get out of control. Discussions were made with the computer technicians of the company to verify that there were options to meet these requirements.

In this phase were applied and analyzed the following CSF: “Measurement system analysis in relation to their capability and applicability”; “Definition and correct application of control charts” and “Use of computers and software for SPC.” Two other factors continued to be used throughout the implementation project: “Education and training in SPC” and “Management of Cultural Change.”

It was presented to the Monitoring Group that for the factor “Measurement system analysis in relation to their capability and applicability” were necessary studies on the measurement system and the confidence improvement of operators in the data.

An oral presentation to the Monitoring Group on the factors “Definition and correct application of control charts” was made and “Use of computers and software for SPC,” discussing the suggestion of spreadsheet using Excel. On-site visits were also carried out to check where the monitor could be allocated, so the operators could accompany the control chart.

4.3.2. Data analysis, action plans and execution

Table 4 shows the results of the analysis and actions for CSF in the second cycle of Action Research.

Table 4
Data analysis and actions to the CSF of the second cycle.

4.3.3. Evaluation and monitoring after the second cycle

The action concerning the “Use of computers and software for SPC” was successful and started to impact on the behavior of operators. The control chart in Excel began to be viewed in the control room for all operators. All of them were aware of the pilot that was being done and has contributed, showing problems that occurred in the factory when the points came out of the control limits (± 3σ), although it is not yet mandatory to use the control chart and record the occurrences.

4.4. Third cycle of action research

4.4.1. Data collection and feedback

It was identified that the operating procedures of the filtering process did not include corrective actions in the case of a point outside the control limits. Therefore, it would be necessary to update the procedure. Some corrective actions can be done from within the control room, such as check other variables as flow and level. Other actions need the checking of the equipment for visual inspection and local action, these actions needed to be inserted in the instructions. Another finding was that operators no longer wanted to be trained in the concepts, but in the new procedures related to the chart, both in identifying special causes and the procedures for eliminating the causes.

It was proposed by the SPC team that morning meetings could help in monitoring and eliminating special causes identified by the control chart. It would be a formal meeting between the production team, process and maintenance engineers to check the previous day's performance, analyzing some indicators and possible special causes.

In meetings with members of the process, it was questioned the need to review the control charts and change in control limits in the case of process changes.

In this action research cycle the following critical success factors for implementation of SPC charts were investigated, “Interpretation capacity of control charts and execution of appropriate actions in case of being out of control”; “Documentation and knowledge updating about the process,” which involves updating the operating procedures in the case of the process have special causes; “Auditing, analysis and review of control charts with a view to Continuous Improvement” and the review of control limits when the process changes.

The findings of the third cycle of research were exposed and discussed by the facilitator to the Monitoring Group.

4.4.2. Data analysis and action plan

Table 5 shows the results of the analysis and actions to the CSF of the third cycle of research.

Table 5
Data analysis and actions to the CSF of the third cycle of research.

4.4.3. Evaluation and monitoring after third cycle

Finishing the third cycle operators included, naturally, the control chart in their work. The chart, in addition to help correct process deviations, also assisted in the identification of the moment of exchange of the filter plates. Over the course of time they will degrade and leak, no longer being able to achieve the necessary compression pressure.

After three cycles of research, there was an improvement in the stability of the process, which reflected in energy gain (natural gas consumption). The SPC becomes therefore, a tool to collect facts and data with a focus on continuous improvement.

4.5. Practical results

After three cycles of action research, the following practical results were found:

a) Stability of the filtration process, reducing the final filtration pressure variability using X-bar and R charts, resulting reduction in gas consumption in 4% with recurring gains of approximately 150 thousand dollars per year.

b) Standardization of the corrective actions in the case of instability, with review of the operational procedure.

c) Implementation of morning meetings with discussion of operating performance indicators, including the control chart.

d) Implementation of computer apparatus for viewing and monitoring real time process data in control chart. The tool allows instant visualization of tendencies in the chart. It was also included in the application, the record of the alert of out of control points (special causes) and any corrective actions to be typed by operators. The data were to be available for further exploration and analysis with the purpose of improvement or innovation in the process.

e) A framework for the implementation of the SPC chart in other processes.

4.6. A framework proposal for the implementation of SPC charts

As a result of the action research, it was proposed a framework (Figure 3) to guide the implementation of SPC charts. The framework presents the main CSF to be executed in four stages, planning, definition, implementation and consolidation; involving three actors, senior management, the SPC team and the facilitator. The colored boxes indicate more than one actor responsibilities. After the consolidation phase, the SPC should be incorporated into the dynamics of Continuous Improvement of the company, providing facts and data to identify improvement opportunities.

Figure 3
Framework for SPC chart implementation. Source: Authors.

The factor “Project Launch with the Team”, which was not foreseen in the literature, was included as a CSF’s to highlight the importance of a formal launch and effective communication to all involved. The framework should be applied, mainly, to the first implementation of the control chart and as a guide to evaluate existing implementations to verify if the CSFs were considered, which could contribute to their support. The factor “Commitment and Responsibility of senior management”, despite appearing explicitly in the planning stage is a necessary factor throughout the conduct of the implementation.

Comparing this model with the CSFs raised in the literature, four of them do not appear in the framework: “Involvement and empowerment of employees,” which is incorporated in the factor “Management of cultural change”; “Feedback, continuous learning and knowledge sharing,” translated into the ability of interpreting control charts, executing appropriate actions and also practicing morning meetings; “Development of statistical thinking”, which is distributed in all stages of implementation and consolidation of the SPC chart and “Focus on customer satisfaction”, which is inserted in the correct identification of critical quality characteristic.

This framework and CSFs can be used by other companies because they deal with needs and general objectives and not specific to the chemical industry where the action research was conducted.

The CSFs for the implementation of the SPC can be related to three types of actions for implementation (Table 6): managerial actions, involving the support and establishment of appropriate infrastructure and culture, so that the implementation occurs and that the use of SPC can be sustained; organizational actions, involving the structuring of the project and the team to implementation activities; and technical actions and training, promoting the knowledge and dissemination of SPC tools, so that those involved feel safe for the implementation.

Table 6
Actions and CSF for SPC implementation.

5. Conclusions

Through action research, it was implemented a control chart in a chemical plant. It was identified the need for the use of nineteen success factors (Table 2) considered critical, identified in the literature, for the effective implementation and sustained use of control charts. Each of the factors was tested in action research, isolated or combined, which helped in proposing a framework to guide the implementation and continued use.

An identified feature was the need for the chart to be physically next to the operator and displayed constantly. Regarding the use of computer monitors, if possible, it should be a unique monitor to the chart.

The framework, its steps and the recognition of its importance constitute a reference to guide control charts implementation in other chemical plants and other companies. The effort required for each factor in each step may differ depending on the history and site characteristics implementation.

The actions implemented during the research contributed to change the culture and behavior of the plant’s operators, to improve the studied object (silica process) and to deploy the initiative to other plants of the company. It was also possible to prove in practice the relevance of the success factors to support the technical traditional focus on SPC implementations.

  • How to cite this article: Toledo, J. C., Lizarelli, F. L., & Santana Junior, M. B. (2017). Success factors in the implementation of statistical process control: action research in a chemical plant. Production, 27, e20162208. http://dx.doi.org/10.1590/0103-6513.220816

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Publication Dates

  • Publication in this collection
    2017

History

  • Received
    08 Sept 2016
  • Accepted
    26 Apr 2017
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