Overall Equipment Effectiveness Analysis Using Discrete Event Simulation at Table Tennis Table Manufacturer

Main Article Content

Yuniaristanto Yuniaristanto
Iqbal Wahyu Saputra
Muhammad Hisjam

Keywords

Performance, Overall Equipment Effectiveness, Discrete Event Simulation, STELLA Architect

Abstract

To measure the performance of the production process, an efficiency calculation is performed using the Overall Equipment Effectiveness (OEE) method. OEE can measure various production losses and identify potential developments that can be carried out in a production process. This research is expected to be an input to improve production efficiency. The results of overall equipment effectiveness are then performed using Discrete Event Simulation, which built using STELLA Architect. The result shows that their overall equipment effectiveness scores are below the company goals, and performance rate is their lowest score. These simulation results are expected to be a basis for improvements in the production division, especially at Table Tennis Table Manufacturer.

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References

[1]          J. Fleischer, U. Weismann, and S. Niggeschmidt, “Calculation and optimisation model for costs and effects of availability relevant service elements,” Proc. LCE, pp. 675–680, 2006.

[2]          S. H. Huang et al., “Manufacturing productivity improvement using effectiveness metrics and simulation analysis,” Int. J. Prod. Res., vol. 41, no. 3, pp. 513–527, 2003. https://doi.org/10.1080/0020754021000042391.

[3]          J. A. Garza‐Reyes, S. Eldridge, K. D. Barber, and H. Soriano‐Meier, “Overall equipment effectiveness (OEE) and process capability (PC) measures,” Int. J. Qual. Reliab. Manag., 2010. https://doi.org/10.1108/02656711011009308.

[4]          R. M. Nachiappan and N. Anantharaman, “Evaluation of overall line effectiveness (OLE) in a continuous product line manufacturing system,” J. Manuf. Technol. Manag., 2006. https://doi.org/10.1108/17410380610688278.

[5]          J. Kumar, V. K. Soni, and G. Agnihotri, “Impact of TPM implementation on Indian manufacturing industry,” Int. J. Product. Perform. Manag., 2014. https://doi.org/10.1108/IJPPM-06-2012-0051.

[6]          S. Nakajima, “Introduction to TPM: total productive maintenance.(Translation),” Product. Press. Inc., 1988, p. 129, 1988.

[7]          P. Jonsson and M. Lesshammar, “Evaluation and improvement of manufacturing performance measurement systems‐the role of OEE,” Int. J. Oper. Prod. Manag., 1999. https://doi.org/10.1108/01443579910244223.

[8]          P. Muchiri and L. Pintelon, “Performance measurement using overall equipment effectiveness (OEE): literature review and practical application discussion,” Int. J. Prod. Res., vol. 46, no. 13, pp. 3517–3535, 2008. https://doi.org/10.1080/00207540601142645.

[9]          T. Wireman, Total productive maintenance. Industrial Press Inc., 2004.

[10]        O. T. R. Almeanazel, “Total productive maintenance review and overall equipment effectiveness measurement,” Jordan J. Mech. Ind. Eng., vol. 4, no. 4, 2010.

[11]        J. A. Garza-Reyes, “From measuring overall equipment effectiveness (OEE) to overall resource effectiveness (ORE),” J. Qual. Maint. Eng., 2015. https://doi.org/10.1108/JQME-03-2014-0014.

[12]        P. Gupta and S. Vardhan, “Optimizing OEE, productivity and production cost for improving sales volume in an automobile industry through TPM: a case study,” Int. J. Prod. Res., vol. 54, no. 10, pp. 2976–2988, 2016. https://doi.org/10.1080/00207543.2016.1145817.

[13]        A. Shahin and N. G. Isfahani, “Estimating overall equipment effectiveness for continuous production lines: with a case study in Esfahan Steel Company,” Int. J. Serv. Oper. Manag., vol. 21, no. 4, pp. 466–478, 2015. https://doi.org/10.1504/IJSOM.2015.070252.

[14]        R. RANJAN and A. MISHRA, “Evaluation and Optimization of Overall Equipment Effectiveness on a Pasting Machine in a Battery Manufacturing Industry.,” Int. J. Performability Eng., vol. 12, no. 6, 2016.

[15]        J. Fattah, L. Ezzine, and A. Lachhab, “Evaluating the performance of a production line by the overall equipment effectiveness: An approach based on best maintenance practices,” in International Journal of Engineering Research in Africa, 2017, vol. 30, pp. 181–189. https://doi.org/10.4028/www.scientific.net/JERA.30.181.

[16]        R. Sharma, “Overall equipment effectiveness measurement of TPM manager model machines in flexible manufacturing environment: a case study of automobile sector,” Int. J. Product. Qual. Manag., vol. 26, no. 2, pp. 206–222, 2019. https://doi.org/10.1504/IJPQM.2019.10018982.

[17]        P. K. Yadav, S. Gupta, and D. Kumar, “Machine performance index (MPI): A method to evaluate the performance of mining dumper,” J. Mines, Met. Fuels, vol. 67, no. 6, pp. 320–325, 2019.

[18]        M. Majid, U. Aickelin, and P.-O. Siebers, “Human Behaviour Modelling for Discrete Event and Agent Based Simulation: A Case Study,” Available SSRN 2831301, 2007.

[19]        L. M. Leemis and S. K. Park, Discrete-event simulation: A first course. Pearson Prentice Hall Upper Saddle River, NJ, 2006.

[20]        R. Wild, Operations management. Cengage Learning EMEA, 2002.

[21]        S. Robinson, R. Brooks, K. Kotiadis, and D.-J. Van Der Zee, Conceptual modeling for discrete-event simulation. CRC Press, 2010.

[22]        J. B. Jun, S. H. Jacobson, and J. R. Swisher, “Application of discrete-event simulation in health care clinics: A survey,” J. Oper. Res. Soc., vol. 50, no. 2, pp. 109–123, 1999. https://doi.org/10.1057/palgrave.jors.2600669.

[23]        A. Mousavi and H. R. A. Siervo, “Automatic translation of plant data into management performance metrics: a case for real-time and predictive production control,” Int. J. Prod. Res., vol. 55, no. 17, pp. 4862–4877, 2017. https://doi.org/10.1080/00207543.2016.1265682.

[24]        E. Alzubi, A. M. Atieh, K. Abu Shgair, J. Damiani, S. Sunna, and A. Madi, “Hybrid Integrations of Value Stream Mapping, Theory of Constraints and Simulation: Application to Wooden Furniture Industry,” Processes, vol. 7, no. 11, p. 816, 2019. https://doi.org/10.3390/pr7110816.

[25]        P. Barosz, G. Gołda, and A. Kampa, “Efficiency Analysis of Manufacturing Line with Industrial Robots and Human Operators,” Appl. Sci., vol. 10, no. 8, p. 2862, 2020. https://doi.org/10.3390/app10082862.

[26]        S. C. Brailsford and N. A. Hilton, “A comparison of discrete event simulation and system dynamics for modelling health care systems,” 2001.

[27]        M. Raunak, L. Osterweil, A. Wise, L. Clarke, and P. Henneman, “Simulating patient flow through an emergency department using process-driven discrete event simulation,” in 2009 ICSE Workshop on Software Engineering in Health Care, 2009, pp. 73–83. https://doi.org/10.1109/SEHC.2009.5069608.

[28]        B. W. Niebel and A. Freivalds, Niebel’s methods, standards, & work design. McGraw-Hill Companies, 2008.