Utilizing simulation to evaluate production line performance under varying demand conditions

McDonald, T.; Akenb, E.; Ellib, K.

Abstract: Determining how a new production cell will function is problematic and can lead to disastrous results if done incorrectly. Discrete-event simulation can provide information on how a line will function before, during, and after the line is in operation. A simulation model can also provide a visual animation of the line to see how product will flow through the line. This paper discusses the development and analysis of a simulation model of a new manufacturing line. The manufacturing cell is a new motor assembly cell. An analysis of the capability of the line for varying demand levels was conducted for the two main motor types produced on the line. An ARENA® simulation model was developed, verified, and validated to determine the daily production and potential problem areas for the various demand levels. The results show that at all but one demand level, the line is capable of producing to within one unit of customer demand if the required number of workers is present. At the highest demand level, the simulation results suggest that the line is not capable of meeting demand. Additional analysis indicates that multiple workstations could prove problematic with minor fluctuations in demand. Problematic workstations were identified for each assembly area and for the line as a whole.

How to cite this paper

        APA: McDonald, T., Akenb, E & Ellib, K. (2012). Utilizing simulation to evaluate production line performance under varying demand conditions. International Journal of Industrial Engineering Computations, 3(1), 3-14.
    

        Chicago/Turabian: McDonald, T., Akenb, E & Ellib, K. 2012. "Utilizing simulation to evaluate production line performance under varying demand conditions." International Journal of Industrial Engineering Computations 3, no. 1 (2012): 3-14.
    

        AMA: McDonald, T., Akenb, E & Ellib, K. Utilizing simulation to evaluate production line performance under varying demand conditions. International Journal of Industrial Engineering Computations. 2012;3(1):3-14.
    

References

Aghaie, A., & Popplewell, K. (1997). Simulation for TQM – the unused tool?. The TQM Magazine, 9(2), 111-116.

Benedettini, O., & Tjahjono, B. (2009). Towards an improved tool to facilitate simulation modeling of complex manufacturing systems. International Journal of Advanced Manufacturing Systems, 43, 191-199.

Chan, F.T.S. (1995). Using simulation to predict system performance: A case study of an electro-phoretic deposition plant. Integrated Manufacturing Systems, 6(5), 27-38.

Chan, F.T.S., & Abhary, K. (1996). Design and evaluation of automated cellular manufacturing systems with simulation modelling and AHP approach: a case study. Integrated Manufacturing Systems, 7(6), 39-52.

Chan, F.T.S., & Jian, B. (1999). Simulation-aided design of production and assembly cells in an automotive company. Integrated Manufacturing Systems, 10(5), 276-283.

Doomun, R., & Jungum, N.V. (2008). Business process modeling, simulation, and reengineering: Call centres. Business Process Management Journal, 14(6), 838-848.

Li, L., (2009). Bottleneck detection of complex manufacturing systems using a data-driven method, International Journal of Production Research, 47(24), 6929-6940.

Li, L., Chang, Q., & Ni, J (2009). Data driven bottleneck detection of manufacturing systems. International Journal of Production Research, 47(18), 5019-5036.

Li, J. (2010). Simulation study of coordinating layout change and quality improvement for adapting job shop manufacturing to CONWIP control. International Journal of Production Research, 48(3), 879-900.

McDonald, T., Hafner, A., Van Aken, E.M., & Ellis, K.P. (2002). Analysis of supplier quality and supplier on-time delivery on production line performance, Proceedings of the 2002 Industrial Engineering and Research Conference, Orlando, FL: May 19-22, 2002, Manufacturing Systems Track, CD-ROM.

McDonald, T., Van Aken, E.M., & Rentes, A.F. (2002). Utilizing simulation to enhance value stream mapping: A manufacturing case application. International Journal of Logistics: Research and Applications, 5(2), 213-232.

⭐ Highly Cited Articles

Journals

IJIEC Volumes

🔑 Keywords

✍️ Authors

🌍 Countries