Yıl: 2020 Cilt: 4 Sayı: 1 Sayfa Aralığı: 388 - 408 Metin Dili: İngilizce İndeks Tarihi: 02-05-2021

Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility

Öz:
Inventory management and control represent a crucial activity required in any successful organization for the modern industry generally and the healthcare field specifically. Rigorous monitoring of the goods inspection properties is important for the delivery of products with appropriate quality that meets customer needs. In the present study, random records have been selected that cover a year simulation period of monitoring for container deliveries to a warehouse that were used as primary packaging materials for topical healthcare products from three different manufacturers. Statistical Process Control (SPC) methodologies and analyses such as box plots, histograms, Pareto diagrams, process-behavior charts and Gaussian Mixture Model (GMM) were applied for processed and stratified data to evaluate a single product property. Integration between the material stock database and statistical processing platform was established through excel dataset and/or Comma-Separated Values (CSV) files where the results of the monitored inspection characteristic were reported for each freightage. The analysis showed that the most dominant supplier dispatched products with specifications that have become very close to the target value, despite initial unstable variations in the inspection characteristic. The less common manufacturer showed product quality values that are shifted slightly above the previous one with a lower rate of out-of-control alarms. The least contacted vendor demonstrated the highest precision (which might be partially accounted to a very few numbers of the received batches of the packaging product) with the lowest accurate values that were very close to the upper specification limit. The study was useful in manufacturers' quality assessment and follow-ups.
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  • 1.Bartholdi, J .J. & Hackman, S. T. (2014). Warehouse & Distribution Science: Release 0.97. Atlanta , USA, Supply Chain and Logistics Institute. Retrieved from: https://www2.isye.gatech.edu/~jjb/wh/book/editions/wh-sci-0.96.pdf Bienert, G. (2018). Development and evaluation of product delivery strategies for demand-driven productiondistribution systems [Doctor of Philosophy, UNIVERSITY OF NEW SOUTH WALES]. unsworks.unsw.edu.au. Retrieved from http://unsworks.unsw.edu.au/fapi/datastream/unsworks:54287/SOURCE02 view=true
  • 2.Bora, A., Deshmukh, S., & Swain, K. (2014). Recent advances in semisolid dosage form. International Journal of Pharmaceutical Sciences and Research, 5(9), 3596. doi: 10.13040/IJPSR.0975-8232.5(9).3594-08
  • 3.Carey, R., Bhattacharyya, S., Kehl, S., Matukas, L., Pentella, M., Salfinger, M., & Schuetz, A. (2018). Implementing a Quality Management System in the Medical Microbiology Laboratory. Clinical Microbiology Reviews, 31(3). doi: https://doi.org/10.1128/cmr.00062-17. doi: 10.1128/CMR.00062-17
  • 4.Cato, W., & Mobley, R. (2002). Computer-managed maintenance systems in process plants. Gulf Pub. Co.: Houston, TX, USA.
  • 5.Celeux, G., & Govaert, G. (1992). A classification EM algorithm for clustering and two stochastic versions. Computational statistics & Data analysis, 14(3), 315-332. Retrieved from: https://doi.org/10.1016/0167- 9473(92)90042-E Center for Biologics Evaluation and Research. (2003). Guidance for industry. U.S. Dept. of Health and Human Services, Food and Drug Administration, Center for Drug Evaluation and Research, Rockville, Maryland. Retrieved from: http://blog-es.hygiena.com/l-por/docs/tech_lib/FDA_cGMP_Pharma.pdf
  • 6.Chambers, J. M., Cleveland, W. S., Kleiner, B., & Tukey, P. A. Graphical methods for data analysis. 1983. Wadsworth & Brooks/Cole: Duxbury, Boston, USA.
  • 7.Chesney, D. L. (2005). Management controls for GMP compliance. Pharmaceutical Technology, 4, 2005. Retrieved from: http://files.dvm360.com/alfresco_images/pharma/2014/08/22/b96657d2-d401-4d2e-a6ce-e3208b9d8ad7/article- 155376.pdf
  • 8.Costantino, F., Di Gravio, G., Shaban, A., & Tronci, M. (2015). A real-time SPC inventory replenishment system to improve supply chain performances. Expert Systems with Applications, 42(3), 1665-1683. Retrieved from: https://doi.org/10.1016/j.eswa.2014.09.028
  • 9.Deelman, E., Singh, G., Su, M., Blythe, J., Gil, Y., & Kesselman, C. et al. (2005). Pegasus: A Framework for Mapping Complex Scientific Workflows onto Distributed Systems. Scientific Programming, 13(3), 219-237. doi: https://doi.org/10.1155/2005/128026.
  • 10.Eissa, M. (2019c). Application of Control Charts in Monitoring of Surgical Site Infection Trending Records Using Statistical Software. Asian Journal Of Applied Sciences, 12(2), 76-84. Retrived from: https://doi.org/10.3923/ajaps.2019.76.84
  • 11.Eissa, M. E. (2018). Role of Statistical Process Control of Pharmaceutical Product to Monitor Consistency of the Manufacturing Operation. EC Pharmacology and Toxicology, 6, 439-444. Retrieved from: https://www.ecronicon.com/ecpt/pdf/ECPT-06-00182.pdf
  • 12.Eissa, M. E. (2019a). Monitoring of Cryptosporidium spp. Outbreaks Using Statistical Process Control Tools and Quantitative Risk Analysis Based on NORS Long-term Trending 9,1-7. doi: 10.3923/mj.2019.1.7
  • 13.Eissa, M. E. (2019b). Statistical Analysis Review and Lessons Learned from Recent Outbreak Trends of Highest Population Density States in USA: Massachusetts, New Jersey and Rhode Island. Journal Of Food Chemistry & Nanotechnology, 05(01). Retrived from: https://doi.org/10.17756/jfcn.2019-066
  • 14.Eissa, M., & Abid, A. (2018). Application of statistical process control for spotting compliance to good pharmaceutical practice. Brazilian Journal Of Pharmaceutical Sciences, 54(2). Retrieved from: https://doi.org/10.1590/s2175- 97902018000217499
  • 15.Food and Drug Administration (FDA). (2006). Guidance for industry: Quality systems approach to pharmaceutical cGMP regulations. Pharmaceutical CGMPs. Retrieved from: https://www.fda.gov/media/71023/download
  • 16.Harel, Z., Silver, S., McQuillan, R., Weizman, A., Thomas, A., & Chertow, G. et al. (2016). How to Diagnose Solutions to a Quality of Care Problem. Clinical Journal Of The American Society Of Nephrology, 11(5), 901-907. https://doi.org/10.2215/cjn.11481015
  • 17.Henderson, G. R. (2011). Six Sigma quality improvement with MINITAB. John Wiley & Sons: West Sussex. Retrieved from: https://books.google.com.eg/books?hl=en&lr=&id=EM5_VS7wEdUC&oi=fnd&pg=PP8&dq=Six+Sigma+quality+improvement+with+MINITAB+2011&ots=PtzzYZqbrO&sig=XeiVE9Wwvx9di7JScDUV85SpXA&redir_esc=y#v=onepage&q=Six%20Sigma%20quality%20improvement%20with%20MINITAB%202011&f=false
  • 18.Hou, S. W., Feng, S., & Wang, H. (2016). Intelligent process abnormal patterns recognition and diagnosis based on fuzzy logic. Computational intelligence and neuroscience, 2016. Retrieved from: https://doi.org/10.1155/2016/8289508
  • 19.Huschka, K. (2009). Using statistical process control to monitor inventory accuracy (Doctoral dissertation, Kansas State University). Manhattan, Kan. Retrieved from: http://hdl.handle.net/2097/1407
  • 20.Institute of Medicine (US) Committee to Design a Strategy for Quality Review and Assurance in Medicare, & Lohr,
  • 21.K. N. (Eds.). (1990). Medicare: A Strategy for Quality Assurance. National Academies Press (US). doi: http://doi.10.17226/1547
  • 22.Iyer, H., & Prasad, S. (2007). Statistical process control approach to reduce the bullwhip effect (Doctoral dissertation, Massachusetts Institute of Technology). MIT Libraries. Retrieved from: http://hdl.handle.net/1721.1/40105
  • 24.Jacoby, W. (1997). Statistical graphics for univariate and bivariate data. Sage Publications. Retrieved from ; https://books.google.com.eg/books?hl=en&lr=&id=-m7yE3E9iPkC&oi=fnd&pg=PR5&dq=Statistical+Graphics+for+Univariate+and+Bivariate+Data&ots=71HBGNTU_v&sig=Y2glCSHp2k6rr-C3aSfKh5eZCOs&redir _esc=y#v=onepage&q=Statistical%20Graphics%20for%20Univariate%20and%20Bivariate%20Data&f=false
  • 25.Jones, G., & Govindaraju, K. (2001). A GRAPHICAL METHOD FOR CHECKING ATTRIBUTE CONTROL CHART ASSUMPTIONS. Quality Engineering, 13(1), 19-26. https://doi.org/10.1080/08982110108918620
  • 26.Judson, L. V. H. (1976). Weights and measures standards of the United States: a brief history (Vol. 447). Department of Commerce, National Bureau of Standards, USA. Retrieved from: https://books.google.com.eg/books?hl=en&lr=&id=gCWCVcYlgRcC&oi=fnd&pg=PA1&dq=Weights+and+measure s+standards+of+the+United+States:+a+brief+history&ots=bq8To7mxLH&sig=WDIE2ZXe4P5Zu-VUDONi55P8hws&redir_esc=y#v=onepage&q=Weights%20and%20measures%20standards%20of%20the%20United%20States%3A%20a%20brief%20history&f=false
  • 27.Juran. J. M. (1960). Pareto, Lorenz, Cournot, Bernouli, Juran and others. Industrial Quality-Control 17(4),: 25. Retrieved from: https://books.google.com.eg/books?hl=en&lr=&id=v_fprq_XtFAC&oi=fnd&pg= PA47&dq=Juran,+J.+M+(1960).+Pareto,+Lorenz,+Cournot.+Bernoulli,+Juran+and+others,+op.+cit,+25.&ots=uC_pB-UJnc&sig=tPoGeCYpp-dwFKItfVVti35mPnE&redir_esc=y#v=one page&q=Juran%2C%20J.%20M.%20(1960).%20Pareto%2C%20Lorenz%2C%20Cournot.%20Bernoulli%2C%20Juran%20and%20others%2C%20op.%20cit%2C%2025.&f=false
  • 28.Kumar, D. (2006). Six sigma best practices: a guide to business process excellence for diverse industries. J. Ross. Publishing: USA. Retrieved from: https://books.google.com.eg/books?hl=en&lr=&id=IB0rfMTOkqYC&oi=fnd&pg=PA1&dq=Six+sigma+best+practic es:+a+guide+to+business+process+excellence+for+diverse+industries&ots=gdKlCfnZfU&sig=9azHwRLQAtqtDfcWhIRasrK5IkU&redir_esc=y#v=onepage&q=Six%20sigma%20best%20practices%3A%20a%20guide%20to%20bus iness%20process%20excellence%20for%20diverse%20industries&f=false
  • 29.Laney, D. B. (2002). Improved control charts for attributes. Quality Engineering, 14(4), 531-537. Retrieved from: https://doi.org/10.1081/QEN-120003555
  • 30.Lightfoot, P., & Kauffman, R. G. (2003). Controlling warehouse performance with statistical process methods. Journal of Public Procurement, 3(1), 29. Retrieved from: https://www.researchgate.net/profile/Ralph_Kauffman2/publication/265748593_CONTROLLING_WAREHOUSE_PERFORMANCE_WITH_STATISTICAL_PROCESS_METHODS/links/55d9743d08aeb38e8a87d30f/CONTROLLING-WAREHOUSE-PERFORMANCE-WITH-STATISTICAL-PROCESS-METHODS.pdf
  • 31.McLachlan, G., & Peel, D. (2006). Finite mixture models. John Wiley & Sons: NY, USA. Retrieved from: https://books.google.com.eg/books?hl=en&lr=&id=c2_fAox0DQoC&oi=fnd&pg =PR7&dq=Finite+Mixture+ Models+2000&ots=ItWC1V88iC&sig=jesok4wEt6IwQr40nfyOmkVlV1c&redir_esc=y#v=onepage&q=Finite%20Mixture%20Models%202000&f=false
  • 32.Melchior, P., & Goulding, A. D. (2018). Filling the gaps: Gaussian mixture models from noisy, truncated or incomplete samples. Astronomy and computing, 25, 183-194. Retrieved from: https://doi.org/10.1016/j.ascom.2018.09.013 Montgomery, D. (2013). Introduction to statistical quality control. Wiley Global Education: Arizona State University
  • 33.Moraru, L., Moldovanu, S., Dimitrievici, L., Dey, N., Ashour, A., & Shi, F. et al. (2019). Gaussian mixture model for texture characterization with application to brain DTI images. Journal Of Advanced Research, 16, 15-23. Retrieved from: https://doi.org/10.1016/j.jare.2019.01.001
  • 34.Muller, M. (2019). Essentials of inventory management. HarperCollins Leadership: Australia. Retrieved from: https://books.google.com.eg/books?hl=en&lr=&id=R_JWDwAAQBAJ&oi=fnd&pg=PP1&dq=Essentials+of+invent ory+management&ots=7yVfMc0H3E&sig=QYB7pGA61aw9NgYFF-GgxpA3xvA&redir_esc=y#v=onepage&q=Essentials%20of%20inventory%20management&f=false
  • 35.National Research Council. (2000). Surviving supply chain integration: Strategies for small manufacturers. National Academies Press: Washington, DC. Retrieved from: https://books.google.com.eg/books?hl= en&lr=&id=GupuAgAAQBAJ&oi=fnd&pg=PR16&dq=Surviving+supply+chain+integration:+strategies+for+small+manufacturers+2000&ots=3wi6TDgUOH&sig=OTh8J3MMZ3HWuvxVXAdEvcMROho&redir_esc=y#v=onepage&q=Surviving%20supply%20chain%20integration%3A%20strategies%20for%20small%20manufacturers%202000&f=false
  • 36.Oliveira, P. M., Novais, P., & Reis, L. P. (Eds.). (2019). Progress in Artificial Intelligence: 19th EPIA Conference on Artificial Intelligence, EPIA 2019, Vila Real, Portugal, September 3–6, 2019, Proceedings, 2(11805). Springer Nature. Retrieved from: https://books.google.com.eg/books?hl=en&lr=&id=mButDwAAQBAJ&oi=fnd&pg=PR5&dq=Progress+in+Artificial+Intelligence+2019+Oliveira&ots=avq0XX4N2m&sig=KPJsiEkL2MD3RTrBpeT7iKoLOBw&redir_esc=y#v=onepage&q=Progress%20in%20Artificial%20Intelligence%202019%20Oliveira&f=false
  • 37.Pfohl, H. C., Cullmann, O., & Stolzle, W. (1999). Inventory management with statistical process control: simulation and evaluation. Journal of Business Logistics, 20(1), 101-120. Retrieved from: https://search.proquest.com/openview/54aca944437505ae5a3757380de04aea/1?pq-origsite=gscholar&cbl=36584
  • 38.Pyzdek, T., & Keller, P. (2009). The six sigma handbook. McGraw-Hill Professional: NY, USA.
  • 39.Rachmania, I. N., Basri, M. H. (2013). Pharmaceutical inventory management issues in hospital supply chains. Management, 3(1):1-5. doi: http://DOI: 10.5923/j.mm.20130301.01
  • 40.Reynolds, D. A., & Rose, R. C. (1995). Robust text-independent speaker identification using Gaussian mixture speaker models. IEEE transactions on speech and audio processing, 3(1), 72-83. doi: http://doi.10.1109/89.365379
  • 41.Ryan, T. (2013). Statistical methods for quality improvement. Wiley: Hoboken, NJ, USA.
  • 42.Ryan, Th. P. (2000). Statistical Methods for Quality Improvement, (2nd ed.). Wiley Series in probability and statistics, John Wiley & Sons: NY, USA.
  • 43.Schlegelmilch, B. B. (1998). Marketing ethics: An international perspective. Cengage Learning EMEA,Berkshire House: London, UK.
  • 44.Sokal, R. R. (1995). The principles and practice of statistics in biological research. Biometry, (3rd ed, pp. 451-554). Freeman, New York, USA.
  • 45.Teasdale, A., Elder, D., & Nims, R. W. (2017). ICH Quality Guidelines. John Wiley & Sons, Inc., Hoboken, NJ, USA.
  • 46.Thompson, J. (2011). Empirical model building. John Wiley & Sons:NJ, USA. Tomassone, R., Dervin, C., & Masson, J. P. (1993). Biométrie. Modélisation de phénomènes biologiques (pp. 553-p). Elsevier Mason SAS: Paris, France.
  • 47.Wilkinson, L, (1999), The Grammar of Graphics. Springer Verlag: NY, USA. World Health Organization (WHO). (2007). Quality assurance of pharmaceuticals: A compendium of guidelines and related materials. Good manufacturing practices and inspection (Vol. 2). World Health Organization.
  • 48.World Health Organization (WHO). (2011). Laboratory quality management system: handbook. World Health Organization. Retrieved from: https://apps.who.int/iris/bitstream/handle/10665/44665/9789244548271_rus.pdf
APA Eissa M, Rashed E (2020). Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. , 388 - 408.
Chicago Eissa Mostafa Essam Ahmed Mostafa,Rashed Engy Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. (2020): 388 - 408.
MLA Eissa Mostafa Essam Ahmed Mostafa,Rashed Engy Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. , 2020, ss.388 - 408.
AMA Eissa M,Rashed E Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. . 2020; 388 - 408.
Vancouver Eissa M,Rashed E Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. . 2020; 388 - 408.
IEEE Eissa M,Rashed E "Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility." , ss.388 - 408, 2020.
ISNAD Eissa, Mostafa Essam Ahmed Mostafa - Rashed, Engy. "Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility". (2020), 388-408.
APA Eissa M, Rashed E (2020). Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. Journal of the Turkish Operations Management (JTOM), 4(1), 388 - 408.
Chicago Eissa Mostafa Essam Ahmed Mostafa,Rashed Engy Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. Journal of the Turkish Operations Management (JTOM) 4, no.1 (2020): 388 - 408.
MLA Eissa Mostafa Essam Ahmed Mostafa,Rashed Engy Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. Journal of the Turkish Operations Management (JTOM), vol.4, no.1, 2020, ss.388 - 408.
AMA Eissa M,Rashed E Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. Journal of the Turkish Operations Management (JTOM). 2020; 4(1): 388 - 408.
Vancouver Eissa M,Rashed E Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility. Journal of the Turkish Operations Management (JTOM). 2020; 4(1): 388 - 408.
IEEE Eissa M,Rashed E "Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility." Journal of the Turkish Operations Management (JTOM), 4, ss.388 - 408, 2020.
ISNAD Eissa, Mostafa Essam Ahmed Mostafa - Rashed, Engy. "Application of statistical process optimization tools in inventory management of goods quality: Suppliers evaluation in healthcare facility". Journal of the Turkish Operations Management (JTOM) 4/1 (2020), 388-408.