Article Sidebar

Download
PDF
Statistic
Read Counter : 563 Download : 476

Downloads

Download data is not yet available.

Main Article Content

Abstract

The global demand for effective utilization of both humans and machinery is increasing due to wastage incurred during product manufacturing. Excessive waste generation has made entrepreneurs find it difficult to breakeven. The development of dynamic error-proof Overall Equipment Effectiveness (OEE) model for optimizing a complex production process is targeted at minimizing/eradicating operational wastes/losses. In this study, the error-proof sigma metric was integrated into the extended traditional OEE factors (availability, performance, quality) to include losses due to waste and man-machine relationships. Error-proof sigma statistics enabled continuous corrective measures on unsatisfactory or low-level OEE resulted from process output variations (quantity delivered or expected), which were mapped into sigma statistical standards (one- to six-sigma).  Application of the model in a processing company showed that errors of the process were reduced by 78% and 42% respectively for traditional OEE and the new Error-Proof OEE (OEE-EP).  The results revealed that the OEE-EP model is better than the other existing schemes in terms of losses elimination in the production process.

Keywords

OEE dynamism Sigma metric process integration productivity

Article Details

Creative Commons License

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

Author Biographies

Buliaminu Kareem, Federal University of Technology Akure

Professor, Industrial and Production Engineering

Adefowope S. Alabi, Federal University of Technology Akure

Research fellow, Dept. of Industrial and Production Engineering

T I. Ogedengbe, The Federal University of Technology Akure

Associate Professor, Mechanical Engineering Dept.

B. O. Akinnuli, The Federal University of Technology, Akure

Associate Professor, Dept. of Industrial and Production Engineering

O. A. Aderoba, Elizade University, Ilara Mokin

Lecturer I, Mechanical and Mechatronics Engineering dept.
How to Cite
Kareem, B., Alabi, A. S., Ogedengbe, T. I., Akinnuli, B. O., & Aderoba, O. A. (2020). Development of OEE Error-Proof (OEE-EP) Model for Production Process Improvement. The Journal of Engineering Research [TJER], 17(2), 59–74. Retrieved from https://journals.squ.edu.om/index.php/tjer/article/view/3187
Download Citation
Endnote/Zotero/Mendeley (RIS)
BibTeX

References

  1. Adams JA (2014), Human factors engineering. New York: McMillan Publishing.
  2. AFSC-Air Force Systems Command, (2010),Air Force Systems Command Design Handbook, Human Factors Engineering. United Kingdom: McMillan Publishing.
  3. Alexander DC (2012), The practice and management of industrial ergonomics. New York: Englewood Cliffs, NJ: Prentice-Hall.
  4. Almeanazel OTR (2010), Total productive maintenance review and overall equipment effectiveness measurement. Jordan Journal of Mechanical and Industrial Engineering (JJMIE) 4(4): 517 – 522
  5. Braglia M, Frosolini M, Zammori F (2008), Overall equipment effectiveness of a manufacturing line (OEEML): An integrated approach to assess systems performance. Journal of Manufacturing Technology Management 20(1) 8-29
  6. Bruce CH (2006), Best Practices in Maintenance, http://www.tpmonline.com/articles_on_total_ productivemaintenance/management.htm, accessed 26:09:2011.
  7. Butlewski, M., Dahlke, G., Drzewiecka-Dahlke M, G-orny A, Pacholski L, (2018), Implementation of TPM methodology in worker fatigue management - a macroergonomic approach. Adv. Intell. Syst. Comput. 605:32-41.
  8. Dilworth JB (2013), Production and operations management. New York: McGraw-Hill.
  9. Domingo R, Aguado S (2015), Overall environmental equipment effectiveness as a metric of a lean and green manufacturing system, Sustainability 7(7): 9031-9047.
  10. Garza‐Reyes JA, Eldridge S, Barber KD, Soriano‐Meier H (2010), Overall equipment effectiveness (OEE) and process capability (PC) measures: A relationship analysis. International Journal of Quality & Reliability Management 27(1): 48-62.
  11. Gharbi A, Kennen JP (2000), Production and preventive maintenance rates control for a manufacturing system: An experimental design approach, International Journals of Production Economics 65: 275-287.
  12. Ghazali A, Adegbola AA. Olaiya KA, Yusuff ON, Kareem B (2013): Evaluation of workers’ perception on safety in selected industries within Ibadan metropolis. SEEM Research and Development Journal 2(1): 82-88.
  13. Godfrey P (2002), How the return on investment and cash flow can be improved by using the overall equipment effectiveness measure. Manufacturing Engineer 81(2): 109-112.
  14. Hansen RC (2002), Overall equipment effectiveness: a powerful production/maintenance tool for increased profits. New York: Industrial Press Inc.
  15. Hayes AF (2018), Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: The Guilford Press.
  16. Hedman R, Subramaniyan M, Almström P (2016), Analysis of critical factors for automatic measurement of OEE. Procedia CIRP 57: 128-133
  17. Joshi S, Gupta R (2004), Scheduling of Routine Maintenance Using Production Schedule and Equipment Failure History. International Journal of Computer and Industrial Engineering 10(1) 11-20.
  18. Lennon P (2016), Root-cause analysis underscores the importance of understanding, addressing and communicating cold chain equipment failures to improve equipment performance. Technical report, Los Angeles, USA.
  19. Kadiri M. A. (2000), “Scheduling of preventive maintenance in a manufacturing company: A computer model approach”, Unpublished M.S. Thesis, Dept. of Ind. and Prod. Eng., University of Ibadan, NG.
  20. Kareem B, Jewo AO (2015), Development of a model for failure prediction on critical equipment in the petrochemical industry. Engineering Failure Analysis 56: 338–347.
  21. Künsch HR, Stefanski LA, Carroll RJ (2012), Conditionally unbiased bounded-influence estimation in general regression models, with applications to generalized linear models. Journal of the American Statistical Association 84 (406): 23-37
  22. Ljungberg O (1998), Measurement of overall equipment effectiveness as a basis for TPM activities. International Journal of Operations & Production Management 18(5): 495-507.
  23. Madhavan E, Paul R, Rajmohan M (2011), Study on the influence of human factors Euro Journals, 23: 179-192.
  24. Marselli M (2004), Lean manufacturing and six-sigma, Wire Journal International, http://www.aemconsulting. com/pdf/lean.pdf. accessed 12-10-2018.
  25. Martand T (2014), Industrial engineering and production management. New Delhi: S.Chand & Company Ltd.
  26. Meyer FE, Stewart JR (2018), Motion and time study for lean manufacturing, 3rd edition, JS-89867 US, https://rzo0o4khw01.storage.googleapis.com/MDEzMDDMxNjcwOQ==01.pdf accessed 19-05-2018.
  27. Michael JK (2015), Six sigma green belt training manual, Michael JK (UK Based), Lagos, NG.
  28. Muñoz-Villamizar A, Santos J, Montoya-Torres J, Jaca C (2018), Using OEE to evaluate the effectiveness of urban freight transportation systems: A case study. International Journal of Production Economics 197: 232-242.
  29. Muraa MD (2016), Worker skills and equipment optimization in assembly line balancing by a Genetic Approach. Technical report, Dept. of Civil and Ind. Eng., Univ. of Pisa, Italy.
  31. Mwanza BG (2017), An assessment of the effectiveness of equipment maintenance, practices in public hospitals. Technical report, Univ. of Johannesburg, South Africa.
  32. Pampanelli AB, Found P, Bernardes AM (2014), A lean & green model for a production cell. Journal of Cleaner Production 85: 19-30
  33. Peng L, Huang Y (2012), Survival analysis with quartile regression models. Journal of the American Statistical Association 103 (482): 637-649.
  34. Prinz C (2017): Implementation of a learning environment for an Industrie 4.0 assistance system to improve the overall equipment effectiveness. Technical report, A Ruhr-Universität Bochum, Chair of Production Systems, Bochum, Germany.
  35. Shah R, Ward PT (2003), Lean manufacturing: context, practice bundles, and performance. Journal of Operations Management 21(2): 129-149.
  36. Swamidassa PM, Kothab S (1998), Explaining manufacturing technology use, firm size and performance using a multidimensional view of technology. Journal of Operations Management 17(1): 23-37.
  37. Wilson L (2010), How to implement lean manufacturing. New York: McGraw-Hill Inc.
  38. Zuashkiani A, Rahmandad H, Jardine AKS (2011), Mapping the dynamics of overall equipment effectiveness to enhance asset management practices. Journal of Quality in Maintenance Engineering 17(1): 74-92