Research Article
BibTex RIS Cite
Year 2020, Volume: 3 Issue: 2, 123 - 128, 31.12.2020
https://doi.org/10.46238/jobda.688641

Abstract

References

  • Ahmed Eissa, M. E. (2019). The use failure mode and effects Analysis as Quantitative Risk Analysis Tool. Opinion| J App Sci| Redelve: RD-APS 10009. Bodach, V. (2011). Gráficas circulares. Mankato, Minn.: Capstone Press.
  • Bragg, S. (2018). Inventory management. Centennial, Colorado: AccountingTools, Inc.
  • Broshears, R. E., Akbari, M. A., Chornack, M. P., Mueller, D. K. and Ruddy, B. C. (2005). Inventory of ground-water resources in the Kabul Basin, Afghanistan. U. S. Geological Survey.
  • Crow, L. H. (2006). Useful metrics for managing failure mode corrective action. In RAMS'06. Annual Reliability and Maintainability Symposium, 2006. (pp. 247-252). IEEE.
  • Eissa, M. (2019a). Rare event control charts in drug recall monitoring and trend analysis of data record: A multidimensional study. Global Journal On Quality And Safety In Healthcare, 2(2), 34-9. doi: 10.4103/jqsh.jqsh_3_19
  • Eissa, M. (2019b). A Long-Term Impact Study of Bacterial Outbreak Using Control Chart-Risk Assessment Combination. Worldwide Medicine, 1(4), 117-122. doi: 10.5455/ww.48101
  • Eissa, M. E., Seif, M., and Fares, M. (2015). Assessment of purified water quality in pharmaceutical facility using six sigma tools. International Journal of Pharmaceutical Quality Assurance, 6(02), 54-72
  • Elseviers, M. (2004). STATISTICS CORNER: THE BOX PLOT: An alternative way to present a distribution of observations. EDTNA-ERCA Journal, 30(2), 114-116. doi: 10.1111/j.1755-6686.2004.tb00345.x
  • Glushkovsky, E. A. (1994). ‘On‐line’g‐control chart for attribute data. Quality and Reliability Engineering International, 10(3), 217-227.
  • Iqbal, M., Geer, M., & Dar, P. (2017). Medicines Management in Hospitals: A Supply Chain Perspective. Systematic Reviews In Pharmacy, 8(1), 80-85. doi: 10.5530/srp.2017.1.14
  • Laney, D. B. (2002). Improved control charts for attributes. Quality Engineering, 14(4), 531-537.
  • Lee, H., & Wu, J. (2006). A study on inventory replenishment policies in a two-echelon supply chain system. Computers & Industrial Engineering, 51(2), 257-263. doi: 10.1016/j.cie.2006.01.005
  • McLaughlin, K. M., and Wakefield, D. B. (2015). An Introduction to Data Analysis Using Minitab® 17. University of Connecticut: Pearson Education, Incorporated. Minitab 17. (2014). Getting Started With Minitab 17. USA: Minitab, Inc.
  • Montgomery, D. (2013). Statistical quality control. Hoboken, N.J.: Wiley.
  • Muller, M. (2011). Essentials of inventory management. New York: AMACOM.
  • Van Sciver, G. R. (1990). Quantitative risk analysis in the chemical process industry. Reliability Engineering & System Safety, 29(1), 55-68.
  • WHO Technical Report Series. (2008). WHO Expert Committee on specifications for pharmaceutical preparations. Revista Do Instituto De Medicina Tropical De São Paulo, 50(3), 144-144. doi: 10.1590/s0036-46652008000300013
  • Williamson, D. (1989). The Box Plot: A Simple Visual Method to Interpret Data. Annals Of Internal Medicine, 110(11), 916. doi: 10.7326/0003-4819-110-11-916

INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY

Year 2020, Volume: 3 Issue: 2, 123 - 128, 31.12.2020
https://doi.org/10.46238/jobda.688641

Abstract

Inventory management in the healthcare industry is of prime importance to ensure the appropriate delivery of the medical and health products to the final customer in a reasonable time without shortage or overstocking of the goods. The achievement of this balance, in turn, is dependent on the production of the product in a timely manner through dynamic control of the inventory mobility of the input materials in the warehouse. In the present study, eight raw materials, which are used as excipients in healthcare products, were selected as a focus research group for analysis using statistical process control (SPC: process-behavior (trending/control) charts, Pareto plots, Box plot diagrams and Pie illustrations), namely Macrogolglycerides, MCC, Sodium Benzoic Sulfimide, Carmellose Sodium, Isofol 20, Citric Acid Hydrate, Ace K and Sodium Hydrate. Inventory autonomous management network was integrated with SPC software (Minitab®v17.1.0) using the generated database. A unique and simple index was created to prioritize and evaluate each material quantitatively based on material mass, rejection factor, deliveries intervals and the lag time before disposition. Isofol 20 and MCC contributed by about 70% as a material risk weight (MRW). This index is useful for objective comparative analysis, measurement of the degree of changes quantitatively and decision-making.

References

  • Ahmed Eissa, M. E. (2019). The use failure mode and effects Analysis as Quantitative Risk Analysis Tool. Opinion| J App Sci| Redelve: RD-APS 10009. Bodach, V. (2011). Gráficas circulares. Mankato, Minn.: Capstone Press.
  • Bragg, S. (2018). Inventory management. Centennial, Colorado: AccountingTools, Inc.
  • Broshears, R. E., Akbari, M. A., Chornack, M. P., Mueller, D. K. and Ruddy, B. C. (2005). Inventory of ground-water resources in the Kabul Basin, Afghanistan. U. S. Geological Survey.
  • Crow, L. H. (2006). Useful metrics for managing failure mode corrective action. In RAMS'06. Annual Reliability and Maintainability Symposium, 2006. (pp. 247-252). IEEE.
  • Eissa, M. (2019a). Rare event control charts in drug recall monitoring and trend analysis of data record: A multidimensional study. Global Journal On Quality And Safety In Healthcare, 2(2), 34-9. doi: 10.4103/jqsh.jqsh_3_19
  • Eissa, M. (2019b). A Long-Term Impact Study of Bacterial Outbreak Using Control Chart-Risk Assessment Combination. Worldwide Medicine, 1(4), 117-122. doi: 10.5455/ww.48101
  • Eissa, M. E., Seif, M., and Fares, M. (2015). Assessment of purified water quality in pharmaceutical facility using six sigma tools. International Journal of Pharmaceutical Quality Assurance, 6(02), 54-72
  • Elseviers, M. (2004). STATISTICS CORNER: THE BOX PLOT: An alternative way to present a distribution of observations. EDTNA-ERCA Journal, 30(2), 114-116. doi: 10.1111/j.1755-6686.2004.tb00345.x
  • Glushkovsky, E. A. (1994). ‘On‐line’g‐control chart for attribute data. Quality and Reliability Engineering International, 10(3), 217-227.
  • Iqbal, M., Geer, M., & Dar, P. (2017). Medicines Management in Hospitals: A Supply Chain Perspective. Systematic Reviews In Pharmacy, 8(1), 80-85. doi: 10.5530/srp.2017.1.14
  • Laney, D. B. (2002). Improved control charts for attributes. Quality Engineering, 14(4), 531-537.
  • Lee, H., & Wu, J. (2006). A study on inventory replenishment policies in a two-echelon supply chain system. Computers & Industrial Engineering, 51(2), 257-263. doi: 10.1016/j.cie.2006.01.005
  • McLaughlin, K. M., and Wakefield, D. B. (2015). An Introduction to Data Analysis Using Minitab® 17. University of Connecticut: Pearson Education, Incorporated. Minitab 17. (2014). Getting Started With Minitab 17. USA: Minitab, Inc.
  • Montgomery, D. (2013). Statistical quality control. Hoboken, N.J.: Wiley.
  • Muller, M. (2011). Essentials of inventory management. New York: AMACOM.
  • Van Sciver, G. R. (1990). Quantitative risk analysis in the chemical process industry. Reliability Engineering & System Safety, 29(1), 55-68.
  • WHO Technical Report Series. (2008). WHO Expert Committee on specifications for pharmaceutical preparations. Revista Do Instituto De Medicina Tropical De São Paulo, 50(3), 144-144. doi: 10.1590/s0036-46652008000300013
  • Williamson, D. (1989). The Box Plot: A Simple Visual Method to Interpret Data. Annals Of Internal Medicine, 110(11), 916. doi: 10.7326/0003-4819-110-11-916
There are 18 citations in total.

Details

Primary Language English
Subjects Economics
Journal Section Original Scientific Articles
Authors

Mostafa Eissa 0000-0003-3562-5935

Engy Rashed 0000-0002-6593-378X

Publication Date December 31, 2020
Published in Issue Year 2020 Volume: 3 Issue: 2

Cite

APA Eissa, M., & Rashed, E. (2020). INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY. Journal of Business in The Digital Age, 3(2), 123-128. https://doi.org/10.46238/jobda.688641
AMA Eissa M, Rashed E. INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY. JOBDA. December 2020;3(2):123-128. doi:10.46238/jobda.688641
Chicago Eissa, Mostafa, and Engy Rashed. “INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY”. Journal of Business in The Digital Age 3, no. 2 (December 2020): 123-28. https://doi.org/10.46238/jobda.688641.
EndNote Eissa M, Rashed E (December 1, 2020) INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY. Journal of Business in The Digital Age 3 2 123–128.
IEEE M. Eissa and E. Rashed, “INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY”, JOBDA, vol. 3, no. 2, pp. 123–128, 2020, doi: 10.46238/jobda.688641.
ISNAD Eissa, Mostafa - Rashed, Engy. “INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY”. Journal of Business in The Digital Age 3/2 (December 2020), 123-128. https://doi.org/10.46238/jobda.688641.
JAMA Eissa M, Rashed E. INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY. JOBDA. 2020;3:123–128.
MLA Eissa, Mostafa and Engy Rashed. “INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY”. Journal of Business in The Digital Age, vol. 3, no. 2, 2020, pp. 123-8, doi:10.46238/jobda.688641.
Vancouver Eissa M, Rashed E. INVENTORY DIGITAL MANAGEMENT USING STATISTICAL PROCESS CONTROL ANALYSIS IN HEALTHCARE INDUSTRY. JOBDA. 2020;3(2):123-8.

                                                              Creative Commons License

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.