Assessment of Optimal Production Through Assembly Line-Balancing and Product-Mix Flexibility

  • Authors

    • Waqas Saleem
    • Hassan Ijaz
    • Ahmed Alzahrani
    • Saeed Rubaiee
    • Muhammad A Khan
    2018-11-27
    https://doi.org/10.14419/ijet.v7i4.16.21775
  • Operational flexibility, Productivity, Production simulation, Line balancing

  • Timely accomplishment of production targets is a challenging task in low volume–high variety environment. Assessment of the manufacturing flexibility of a production system assists in achieving the desired objectives. In this research, the operational flexibility of a production system is investigated which operates under the low-volume high-variety production scenario. Prospective dimensions of the production flexibility are studied to analyze its interface with the integrated functional units. It was analyzed that with a low-volume operational flexibility (OF) varies rationally despite high job varieties. Line-balancing and queuing techniques are applied to ascertain the optimum productivity. A sensitivity analysis is also performed to evaluate the critical parameters that affect the OF and productivity level. OF index of the production system was estimated by means of the optimized production parameters. A comparative analysis is performed to evaluate the flexibility in conventional and flexible production cells. Analytical and computational results show a close approximation and validate the implemented schemes.

     

  • References

    1. [1] Gerwin, D., 1993, Manufacturing Flexibility: a strategic perspective, Management Science, Vol. 39(4), 395-410

      [2] Hayes, R.H. and Wheelwright, S.C., Restoring Our Competitive Edge Competing through Manufacturing, John Wiley (1984)

      [3] Sethi, A.K., Sethi, S.P., 1990, Flexibility in manufacturing: a survey, International Journal of Flexible Manufacturing Systems, Vol. 2, Issue 4, pp 289–328

      [4] Beach, R., Muhlemann, A.P., Price D.H.R., Paterson, Sharp J.A., 2000, A review of manufacturing flexibility, European Journal of Operational Research

      [5] Leary, K., Benito, E., 2002. The integration of manufacturing and marketing/sales decisions: impact on organizational performance, Journal of Operation Management, Vol. 20, pp. 221-240

      [6] Chang, S.C., Lin, N.P. and Sheu, C., 2002, Conceptualizing manufacturing flexibility: an operational approach and a comparative evaluation. International Journal of Production Research, 40(10), 2187-2206.

      [7] Koste, L.L. and Malhotra, M.K., 1999, A theoretical framework for analyzing the dimensions of manufacturing flexibility. Journal of Operations Management, 18, 75-93.

      [8] Matthias A., 2000. An exact method for cost oriented assembly line balancing, International Journal of Production Economics, Vol. 64, pp 187-195

      [9] Hafsa, A., Mouhssine, C., Driss, A., Said, B., 2017, Optimization tolerancing of surface in flexible parts and assembly: Influence Coefficient Method with shape defects, International Journal of Engineering & Technology, 7 (1), pp 90-94

      [10] Kara, S., Kayis, B. and Kane, S., 2002. The role of human factors in flexibility management: a survey, Human Factors and Ergonomics in Manufacturing, Vol. 12, 1, pp. 75-119

      [11] Calvo, R., Domingo, R., Sebastian, M.A., 2007, Operational flexibility quantification in a make -to-order assembly system, International Journal of Flexible Manufacturing Systems, Vol. 19,3, pp 247–263

      [12] Malasamy, G.V., Nadarajah, D., Mehmood, S.A., 2018, Effects of Knowledge Acquisition, Information Capability and Relationship Quality on Product Innovation Flexibility Among Manufacturing Firms in Malaysia, International Journal of Engineering & Technology, 7 (2.34), pp 29-33

      [13] Seamus M.M., Surendra M.G., 2007, A balancing method and genetic algorithm for disassembly line balancing, European Journal of Operational Research Vol.179, pp.692–708

      [14] Alper H, Gokalp Y, 2012. A genetic algorithm based approach for simultaneously balancing and sequencing of mixed-model U-lines with parallel workstations and zoning constraints, Computers & Industrial Engineering, Vol.62, pp.206–215

      [15] Simaria, A.S., Vilarinho, P.M., 2009, 2-ANTBAL: An ant colony optimisation algorithm for balancing two-sided assembly lines, Computers & Industrial Engineering, Vol.56, pp.489–506

      [16] Mahesh, R., Murali, J.G., Arulmurugan, R., 2018, Overview Role of Simulation Package in Virtual Manufacturing and for CNC Machinery, International Journal of Engineering & Technology, 7 (2.8), pp 702-705

  • Downloads

  • How to Cite

    Saleem, W., Ijaz, H., Alzahrani, A., Rubaiee, S., & A Khan, M. (2018). Assessment of Optimal Production Through Assembly Line-Balancing and Product-Mix Flexibility. International Journal of Engineering & Technology, 7(4.16), 32-36. https://doi.org/10.14419/ijet.v7i4.16.21775