Performance Analysis of Remanufacturing System Considering Inspection & Grading Policies, Sourcing Policies and Resource Policies Under Multiple Quality Scenarios: Towards Environmental Sustainability
محورهای موضوعی : Strategic Management
Magdalene Andrew-Munot
1
,
Shirley Jonathan Tanjong
2
1 - Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Sarawak, Malaysia
2 - Department of Mechanical and Manufacturing Engineering, Faculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), 94300 Kota Samarahan, Sarawak, Malaysia
کلید واژه: Simulation, Remanufacturing, Inspection, Used-Products, Grading,
چکیده مقاله :
The aim of this study was to investigate the effect three factors (inspection & grading, sourcing policies and resource policies) on the cycle-time performance of a remanufacturing system under three different quality scenarios. The objectives were to analyse (i) the main effect of factors on the remanufacturing cycle-time under the given three quality scenarios, (ii) the interaction effect between these factors on the remanufacturing cycle-time under the given three quality scenarios; and (iii) the factors and corresponding levels that lead to shortest remanufacturing cycle-time. Simulation technique was used to model and simulate the remanufacturing system. Design of experiment method was used to design a mixed two-level and three-level full factorial for running the simulation experiments. Analysis of variance (ANOVA) was used to analyse the output results from the simulation experiments. The ANOVA results show all three factors have significant effect on the remanufacturing cycle-time, regardless of the quality scenarios. The ANOVA results also suggest that sourcing policies has the most predominant effect when the quality scenario is average. Despite the different quality scenarios, the interaction between sourcing policies and resource policies have significant effects on the remanufacturing cycle-time, with predominant effect when the quality scenario is average. The implications for remanufacturing industry are there must be (i) inspection & grading policies, (ii) sourcing policies and (iii) resource policies, as these factors affect the remanuafacturing cycle-time. This work is novel because it considers three factors simultaneously and carries out the research by using simulation, design of experiment and ANOVA.
Andrew-Munot, M., Yassin, A., Shazali, S. T., Sawawi, M., Tanjong, S. J., & Razali, N. (2018). Analysis of production planning activities in remanufacturing system. Journal of Mechanical Engineering and Sciences, 12(2), 3548-3565.
Aydin, R., Kwong, C. K., Geda, M. W., & Okudan Kremer, G. E. (2018). Determining the optimal quantity and quality levels of used product returns for remanufacturing under multi-period and uncertain quality of returns. The International Journal of Advanced Manufacturing Technology, 94, 4401-4414.
Butzer, S., Kemp, D., Steinhilper, R., & Schötz, S. (2016). Identification of approaches for remanufacturing 4.0. IEEE European Technology and Engineering Management Summit (E-TEMS), 1-6.
Caterpillar, (2019), 2019 Annual Report, [Online] Available: https://reports.caterpillar.com/ar/2019_Caterpillar_Annual_Report.pdf (February 10, 2020)
Chen, W., Wang, Y., Zhang, P., & Chen, X. (2018). Effects of an Inaccurate Sorting Procedure on Optimal Procurement and Production Decisions in a Remanufacturing System. Engineering Management Journal, 30(2), 117-127.
Devoto, C., Fernández, E., & Piñeyro, P. (2020). The economic lot-sizing problem with remanufacturing and inspection for grading heterogeneous returns. Journal of Remanufacturing, 1-17.
Fuji Xerox Australia, (2020), Eco Manufacturing Centre and Product Stewardship Program Information, [Online] Available: https://www.fujixerox.com.au/en/Sustainability/Eco-Manufacturing-Centre (March 15, 2020)
Farahani, S., Otieno, W., & Omwando, T. (2020). The optimal disposition policy for remanufacturing systems with variable quality returns. Computers & Industrial Engineering, 140, 106-218.
Gaspari, L., Colucci, L., Butzer, S., Colledani, M., & Steinhilper, R. (2017). Modularization in material flow simulation for managing production releases in remanufacturing. Journal of Remanufacturing, 7(2-3), 139-157.
GA, U. (2015). Transforming our world: the 2030 Agenda for Sustainable Development. Division for Sustainable Development Goals: New York, NY, USA.
Graham, I., Goodall, P., Peng, Y., Palmer, C., West, A., Conway, P., Mascolo, J. E., & Dettmer, F. U. (2015). Performance measurement and KPIs for remanufacturing. Journal of Remanufacturing, 5-10.
Golinska-Dawson, P, Kosacka, M, & Nowak, A. (2015). Automotive Parts Remanufacturing–Experience of Polish Small Companies. CMUJ NS Special Issue on Logistics and Supply Chain, 14, 415-430.
Gunal M.M. (2019) Simulation and the Fourth Industrial Revolution. In: Gunal M. (eds) Simulation for Industry 4.0. Springer Series in Advanced Manufacturing. (pp.1-17). Springer, Cham.
Gunal, M. M., & Karatas, M. (2019). Industry 4.0, Digitisation in Manufacturing, and Simulation: A Review of the Literature. In Gunal M. (eds) Simulation for Industry 4.0. Springer Series in Advanced Manufacturing. (pp.19-37). Springer, Cham.
HP, (2020), Remanufactured Hardware, [Online] Available: https://www8.hp.com/us/en/hp-information/environment/refurbished-products.html (March 22, 2020)
Haziri, L. L., & Sundin, E. (2019). Supporting design for remanufacturing-A framework for implementing information feedback from remanufacturing to product design.Journal of Remanufacturing, 1-20.
Iwao, M. & Kusukawa, M. (2012). Optimal production planning for remanufacturing with uncertainty in quality of returns and classification error in quality grading. Proceedings of the Asia Pacific Industrial Engineering & Management Systems Conference Osaka
Jin, X., Ni., J, & Koren, Y. (2011). Optimal control of reassembly with variable quality returns in a product remanufacturing system. CIRP Annals, 60,25-28.
Kang, T. (2013). Balancing Acquisition and Sorting Policies Of Remanufacturing. https://rc.library.uta.edu/uta-ir/handle/10106/23941 (February 21, 2020).
Karamouzian, A., Naini, S.G.J. & Mazdeh, M.M. (2014). Management of returned products to a remanufacturing facility considering arrival uncertainty and priority processing. International Journal of Operational Research, 20, 331-340.
Karamouzian, A., Teimoury, E., Modarres, M. (2011). A model for admission control of returned products in a remanufacturing facility using queuing theory. The International Journal of Advanced Manufacturing Technology, 54, 403-412.
Kelton, W., Sadowski, R., & Zupick, N. (2015). Simulation with Arena. 6th ed. Singapore
Lage Junior, M., & Godinho Filho, M. (2016). Production planning and control for remanufacturing: exploring characteristics and difficulties with case studies. Production Planning and Control, 27(3), 212-225.
Lari, O, & Singh, H. (2015). Basics of Modelling and Simulation. S. K. Kataria & Sons
Liao, H., Deng, Q., & Shen, N. (2019). Optimal remanufacture-up-to strategy with uncertainties in acquisition quality, quantity, and market demand. Journal of Cleaner Production, 206, 987-1003.
Li, X., Li, Y., & Cai, X. (2016). On Core Sorting in RMTS and RMTO Systems: A Newsvendor Framework. Decision Sciences, 47, 60-93.
Lund, R. T., & Hauser, W. M. (2010). Remanufacturing-an American perspective.
Mashhadi, A. R., Esmaeilian, B., & Behdad, S. (2015). Uncertainty Management in Remanufacturing Decisions: A Consideration of Uncertainties in Market Demand, Quantity, and Quality of Returns. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, 1(2).
Mashhadi, A. R., & Behdad, S. (2017). Optimal sorting policies in remanufacturing systems: Application of product life-cycle data in quality grading and end-of-use recovery. Journal of Manufacturing Systems, 43(1), 15-24.
Matsumoto, M., & Ijomah, W. (2013). Remanufacturing. In Handbook of sustainable engineering (pp. 389-408). Springer Netherlands.
Matsumoto, M., Yang, S., Martinsen, K., & Kainuma, Y. (2016). Trends and research challenges in remanufacturing. International Journal of Precision Engineering and Manufacturing-Green Technology, 3, 129-142.
Mezghani M, & Loukil T. (2012). Remanufacturing planning with imprecise quality inputs through the goal programming and the satisfaction functions. International Journal of Multicriteria Decision Making, 2, 379-390.
Mutha, A., Bansal, S., & Guide, V. D. R. (2016). Managing demand uncertainty through core acquisition in remanufacturing. Production and Operations Management, 25, 1449-1464.
Oh, Y., & Behdad, S. (2017). Simultaneous reassembly and procurement planning in assemble-to-order remanufacturing systems. International Journal of Production Economics, 184, 168-178.
Priyono, A., Ijomah, W., & Bititci, U. (2016) Disassembly for remanufacturing: A systematic literature review, new model development and future research needs. Journal of Industrial Engineering and Management, 9, 899-932.
Rockwell Automation (2020) Arena simulation software. 16 ed.
Sarda, A., & Digalwar, A. K. (2018). Performance analysis of vehicle assembly line using discrete event simulation modelling. International Journal of Business Excellence, 14(2), 240-255.
Savaliya, R., & Abdul-Kader, W. (2020). Performance evaluation of the remanufacturing system prone to random failure and repair. International Journal of Sustainable Engineering, 13(1), 33-44.
Sturrock, D. T. (2019). Traditional Simulation Applications in Industry 4.0. In In: Gunal M. (eds) Simulation for Industry 4.0. Springer Series in Advanced Manufacturing. (pp.39-54). Springer, Cham
Sundin, E., (2019), The role of remanufacturing in a circular economy: Operations, Engineering and Logistics (pp. 31-60). John Wiley & Sons.
Swanberg, L. (2018), Engines Revived, [Online] https://www.volvotrucks.com/en-lb/news/magazine-online/2018/may/remanufacturing-engines.html# (May 5, 2020)
Tao, Z., Zhou, S. X., & Tang, C. S. (2012). Managing a Remanufacturing System with Random Yield: Properties, Observations, and Heuristics. Production and Operations Management, 21, 797-813.
Teunter, R. H., & Flapper, S. D. P. (2011). Optimal core acquisition and remanufacturing policies under uncertain core quality fractions. European Journal of Operational Research, 210, 241-248.
Yang, C. H., Wang, J., & Ji, P. (2015). Optimal acquisition policy in remanufacturing under general core quality distributions. International Journal of Production Research, 53, 1425-1438.
Yang, C. H., Bao, X. Y., Song, C., & Liu, H. B. (2016A). Optimal acquisition policy in remanufacturing systems with quantity discount and carbon tax scheme. Tehnicki vjesnik, 23, 1073-1081.
Yang, C. H., Liu, H. B., Ji, P., & Ma, X. (2016B). Optimal acquisition and remanufacturing policies for multi-product remanufacturing systems. Journal of Cleaner Production, 135, 1571-1579.
Yang, C. H., Ma, X., & Talluri, S. (2019). Optimal acquisition decision in a remanufacturing system with partial random yield information. International Journal of Production Research, 57(6), 1624-1644.
Yanıkoğlu, İ., & Denizel, M. (2020). The value of quality grading in remanufacturing under quality level uncertainty. International Journal of Production Research, 1-21.
Zhang, R., Ong, S. K., & Nee, A. Y. C. (2015). A simulation-based genetic algorithm approach for remanufacturing process planning and scheduling. Applied Soft Computing, 37, 521-532.
Zhou, J., Deng, Q., & Li, T. (2018). Optimal acquisition and remanufacturing policies considering the effect of quality uncertainty on carbon emissions. Journal of Cleaner Production, 186, 180-190.
Zheng, Y., Zhang, C., & Su, C. (2019). Simulation on Remanufacturing Cost by Considering Quality Grade of Returns and Buffer Capacity. Journal of Shanghai Jiaotong University (Science), 24(4), 471-476.
Zikopoulos, C. (2012). Remanufacturing lot-sizing under alternative perceptions of returned units' quality. International Journal of Business Science & Applied Management, 7,12-22.
Zikopoulos, C. (2017) Remanufacturing lotsizing with stochastic lead-time resulting from stochastic quality of returns. International Journal of Production Research, 55, 1565-1587
