Developing Quality Control Charts for the Control Points of a Food Product
Ключевые слова:
Quality Control Charts, Food Chain, CUSUM, EWMA, Grey ModelАннотация
Monitoring the production process is a critical issue for improving the quality of product and for reducing the costs regarding external failures. Quality control charts are often used to visualize measurements on the process during the monitoring activities. This paper presents a case study based on the use of advanced charts, Cumulative Summation (CUSUM) and Estimated Weighted Moving Average (EWMA) charts, for visualizing the control points of a particular chicken product in fast-food industry. Furthermore, GM (1,1) and GM (1,1) Markov models were built to generate predictions to see the trends and future values to maintain a follow-up procedure for the fluctuations in the process performance. In this context, three control points are considered that are weight of the chicken wings, sterilizer temperature, and grid-pan temperature. The findings provide a significant feedback for the efficiency of the corresponding processes. Results show that the methodology selected to develop these charts has an important impact on creating an effective quality control process.
Библиографические ссылки
Adegoke Nurudeen A., Muhammad Riaz, Ridwan A. Sanusi, Adam N.H. Smith, Matthew D.M. Pawley. (2017). EWMA-type scheme for monitoring location parameter using auxiliary information, Computers & Industrial Engineering, Volume 114, Pages 114-129, ISSN 0360-8352, https://doi.org/10.1016/j.cie.2017.10.013.
Bakker M., D. Jung, J. Vreeburg, M. van de Roer, L. Rietveld. (2014). Detecting Pipe Bursts Using Heuristic and CUSUM Methods, Procedia Engineering, Volume 70, Pages 85-92
Bissel, A. F. (1969). Cusum techniques for quality control. Applied Statistics, 18, 1–30.
Chan, Chi Kin, Stephen F. Witt, Y.C.E. Lee, H. Song. (2010) Tourism forecast combination using the CUSUM technique, Tourism Management, Volume 31, Issue 6, 2010, Pages 891-897, ISSN 0261-5177, https://doi.org/10.1016/j.tourman.2009.10.004.
Chen, Shinn-Horng, Jyh-Horng Chou, Jin-Jeng Li, (2002) Optimal grey-fuzzy controller design for a constant turning force system, International Journal of Machine Tools and Manufacture, Volume 42, Issue 3, 2002, Pages 343-355, ISSN 0890-6955, https://doi.org/10.1016/S0890-6955(01)00128-6.
Chen, Ssu-Han. (2016). The gamma CUSUM chart method for online customer churn prediction, Electronic Commerce Research and Applications, Volume 17, 2016, Pages 99-111, ISSN 1567-4223, https://doi.org/10.1016/j.elerap.2016.04.003.
Chen, X., Jiang, K., Liu, Y. (2015), “Inflation prediction for China based on the Grey-Markov model”, in Grey Systems and Intelligent Services (GSIS), 2015 IEEE International Conference on (pp. 301-306). IEEE.
Chou, Jyh-Horng, Shinn-Horng Chen, Jin-Jeng Li. (2000). Application of the Taguchi-genetic method to design an optimal grey-fuzzy controller of a constant turning force system, Journal of Materials Processing Technology, Volume 105, Issue 3, 2000, Pages 333-343, ISSN 0924-0136, https://doi.org/10.1016/S0924-0136(00)00651-8.
Feigenbaum A.V., (1999) "The new quality for the twenty first century", The TQM Magazine, Vol. 11 Issue: 6, pp.376-383, https://doi.org/10.1108/09544789910287656
Deng, J. (1989), “Introduction to Grey Systems Theory”, the Journal of Grey System, Vol. 1, pp. 1-24. doi:10.1.1.678.3477.
Guo, Renkuan and Tim Dunne (2006) Grey Predictive Process Control Charts, Communications in Statistics—Theory and Methods, 35:10, 1857-1868, DOI: 10.1080/03610920600728518
Harrou Fouzi, Mohamed N. Nounou, Hazem N. Nounou, Muddu Madakyaru. (2015). PLS-based EWMA fault detection strategy for process monitoring, Journal of Loss Prevention in the Process Industries, Volume 36, Pages 108-119, ISSN 0950-4230, https://doi.org/10.1016/j.jlp.2015.05.017.
Juan, L., Yong, X., Lai, Z.Y. (2012), “An improved Grey Markov forecasting model and its application”, in Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on, pp. 190-193, IEEE.
Karmakar, Subhankar, P.P. Mujumdar. (2006). Grey fuzzy optimization model for water quality management of a river system, Advances in Water Resources, Volume 29, Issue 7, 2006, Pages 1088-1105, ISSN 0309-1708,https://doi.org/10.1016/j.advwatres.2006.04.003.
Kollmann-Camaiora, A., N. Brogly, E. Alsina, F. Gilsanz. (2017). Use of the cumulative sum method (CUSUM) to assess the learning curves of ultrasound-guided continuous femoral nerve block, Revista Española de Anestesiología y Reanimación (English Edition), Volume 64, Issue 8, 2017, Pages 453-459, ISSN 2341-1929, https://doi.org/10.1016/j.redare.2017.06.002.
Kwak Hee Yong, Sang Hoon Kim, Byung Joo Chae, Byung Joo Song, Sang Seol Jung, Ja Seong Bae. (2014). Learning curve for gasless endoscopic thyroidectomy using the trans-axillary approach: CUSUM analysis of a single surgeon's experience, International Journal of Surgery, Volume 12, Issue 12, 2014, Pages 1273-1277, ISSN 1743-9191, https://doi.org/10.1016/j.ijsu.2014.10.028.
Li, G-D., Yamaguchi, D., Nagai, M. (2007), “A GM (1,1)-Markov chain combined model with an application to predict the number of Chinese international airlines”, Technological Forecasting & Social Change, Vol. 74 No. 8, pp. 1465-1481. doi:10.1016/j.techfore.2006.07.010
Montgomery, D. C. (1996). Introduction to statistical quality control. New York: Wiley.
Önalan, Ö. (2014), “Currency exchange rate estimation using the Grey Markov prediction model”, Journal of Economics Finance and Accounting, Vol.1 No.3, pp. 205-217.
Özdemir, A., & Özdagoglu, G. (2017). Predicting product demand from small-sized data: grey models. Grey Systems: Theory and Application, 7(1), 80-96.
Page, E., (1954). Continuous inspection schemes. Biometrika 41, 100–114.
Parikh, A.M., A.M. Park, J. Sumfes. (2014). Cumulative summation (CUSUM) charts in the monitoring of hypospadias outcomes: A tool for quality improvement initiative, Journal of Pediatric Urology, Volume 10, Issue 2, April 2014, Pages 306-311
Reeves Carol A. and Bednar David A. (1994). Defining Quality: Alternatives And Implications, Academy of Management Review, 19:3, 419-445
Segna, E., J.-B. Caruhel, P. Corre, A. Pichart, D. Biau, R.H. Khonsari. (2017) Quantitative assessment of the learning curve for cleft lip repair using LC-CUSUM, International Journal of Oral and Maxillofacial Surgery, https://doi.org/10.1016/j.ijom.2017.10.005.
Şentürk, Sevil, Nihal Erginel, İhsan Kaya, Cengiz Kahraman. (2014). Fuzzy exponentially weighted moving average control chart for univariate data with a real case application, Applied Soft Computing, Volume 22,2014, Pages 1-10, ISSN 1568-4946,https://doi.org/10.1016/j.asoc.2014.04.022.
Shams M.A. Bin, H.M. Budman, T.A. Dueve (2011) Fault detection, identification and diagnosis using CUSUM based PCA, Chemical Engineering Science, Volume 66, Issue 20, 15 October 2011, Pages 4488-4498
Vargas Vera do Carmo C. de, Luis Felipe Dias Lopes, Adriano Mendonça Souza. (2004). Comparative study of the performance of the CuSum and EWMA control charts, Computers & Industrial Engineering, Volume 46, Issue 4, 2004, Pages 707-724, ISSN 0360-8352, https://doi.org/10.1016/j.cie.2004.05.025.
Vargas, Vera do Carmo C. de. Lopes, Luis Felipe Dias. Souza, Adriano Mendonca. (2004). “Comparative study of the performance of the CuSum and EWMA control charts”, Computers & Industrial Engineering, 46, 707–724. doi:10.1016/j.cie.2004.05.025.
Vaughn, R. C. (1990). Quality assurance. Iowa: Iowa State University Press.
Woodall, W. H. (1985). The statistical design of quality control charts. The Statistician, 34, 155–160
Wu, Chunjie. Yu, Miaomiao. Zhuang, Fang. (2017). “Properties and enhancements of robust likelihood CUSUM control chart”, Computers & Industrial Engineering, 114. 80–100. Doi: 10.1016/j.cie.2017.10.005.
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