A producer-retailer incorporated multi-item EPQ problem with delayed differentiation, the expedited rate for common parts, multi-delivery and scrap

Chiu, Y.; Chiu, T.; Pai, F.; Wu, H.

Abstract: Transnational producers facing the present-day competitive global supply-chain environments need to pursue the most appropriate manufacturing scheme, quality screening task, and stock shipping plan to satisfy customer’s timely multi-item requirements under minimum overall product fabrication-delivery expenses. This study develops a producer-retailer incorporated multi-item two-stage economic production quantity- (EPQ-) based system with delayed differentiation, expedited-rate for common parts, multiple deliveries plan, and random scrap. It aims to assist current manufacturing firms in achieving the aforementioned operating goals. Mathematical methods help us build an analytical model to explicitly portray the studied problem’s features and derive its overall system expenses. Hessian matrix equations and optimization approaches help us prove convexity and derive the cost-minimized fabrication- delivery decision. This study gives a simulated example to illustrate the research outcome’s applicability and the proposed model’s capabilities numerically. Consequently, diverse crucial information becomes obtainable to the manufacturers to facilitate various operating decision makings as follows: (i) the cost-minimized fabrication-delivery policy; (ii) the behavior of system’s overall expenses and operating policy regarding mean scrap rate, and different relationships between common part’s values and completion-rate; (iii) the system’s detailed cost components; (iv) the system’s overall expenses, utilization, and common part’s uptime concerning different common part’s expedited rates; and (v) the collective effects of critical system features on the overall expenses, uptime, and optimal cycle length, etc.

How to cite this paper

 Chiu, Y., Chiu, T., Pai, F & Wu, H. (2021). A producer-retailer incorporated multi-item EPQ problem with delayed differentiation, the expedited rate for common parts, multi-delivery and scrap.International Journal of Industrial Engineering Computations , 12(4), 427-440.

References

Aouam, T., & Kumar, K. (2019). On the effect of overtime and subcontracting on supply chain safety stocks. Omega, 89, 1-20
Arslan, H., Ayhan, H., & Olsen, T.L. (2001). Analytic models for when and how to expedite in make-to-order systems. IIE Transaction, 33(11), 1019-1029
Ayed, S., Sofiene, D., & Nidhal, R. (2011). Joint optimisation of maintenance and production policies considering random demand and variable production rate. International Journal of Production Research, 50(23), 6870-6885.
Cavusoglu, H., Cavusoglu, H., & Raghunathan, S. (2012). Value of and interaction between production postponement and information sharing strategies for supply chain firms. Production and Operations Management, 21(3), 470-488.
Chiu, Y-S.P., Hsieh, Y-T., Kuo, J-S., & Chiu, S.W. (2016). A delayed differentiation multi-product FPR model with scrap and a multi-delivery policy – I: Using single-machine production scheme. International Journal for Engineering Modelling, 29(1-4), 37-52.
Chiu, Y-S.P., Chiu, V., Lin, H-D., Chiu, T. (2019). An EMQ-based system considering machine malfunction, allowable backlogging level, repairable items, and discontinuous issuing policy. Journal of Engineering Research, 7(4), 276-298.
Chiu, S.W., You, L-W., Yeh, T-M., Chiu, T. (2020a). The collective influence of component commonality, adjustable-rate, postponement, and rework on multi-item manufacturing decision. Mathematics. 8(9), Art. No. 1570, 1-18
Chiu, Y-S.P., Chiu, V., Yeh, T-M., Wu, H-Y. (2020b). Incorporating outsourcing strategy and quality assurance into a multiproduct manufacturer–retailer coordination replenishing decision. Mathematics, 8(12), Art. No. 02212, 1-19.
Chiu, Y-S.P., Wu, C-S., Wu, H.Y., Chiu, S.W. (2021). Studying the effect of stochastic breakdowns, overtime, and rework on inventory replenishment decision. Alexandria Engineering Journal, 60(1), 1627-1637
Farsijani, H., Nikabadi, M.S., & Ayough, A. (2012). A simulated annealing approach to optimize multi-products EPQ model with discrete delivery orders, imperfect production processes and service level constraint. World Applied Sciences Journal, 16(8), 1142-1157.
Gera, A.E. (2021). The reliability of a system involving change points. International Journal of Mathematical, Engineering and Management Sciences, 6(1), 296-308.
Gilotra, M., Pareek, S., Mittal, M., & Dhaka, V. (2020). Effect of carbon emission and human errors on a two-echelon supply chain under permissible delay in payments. International Journal of Mathematical, Engineering and Management Sciences, 5(2), 225-236.
Gupta, D., & Benjaafar, S. (2004). Make-to-order, make-to-stock, or delay product differentiation? A common framework for modeling and analysis, IIE Transactions, 36(6), 529-546.
Jabbarzadeh, A., Haughton, M., & Pourmehdi, F. (2019). A robust optimization model for efficient and green supply chain planning with postponement strategy. International Journal of Production Economics, 214, 266-283.
Jeunet, J., & Bou Orm, M. (2020). Optimizing temporary work and overtime in the time cost quality trade-off Problem. European Journal of Operational Research, 284, 743-761
Kauppila, O., Valikangas, K., & Majava, J. (2020). Improving supply chain transparency between a manufacturer and suppliers: A triadic case study. Management and Production Engineering Review, 11(3), 84-91.
Köksal, G., Taşeli, A., Dolgun, L.E., & Batmaz, I. (2013). The effect of inspection error on quality and producer losses: The case of nominal-the-best type quality characteristic and rework. European Journal of Industrial Engineering, 7(4), 497-528.
Larkin, E.V., & Privalov, A.N. (2019). Engineering method of fault-tolerant system simulations. Journal of Applied Engineering Science, 17(3), 295-303.
Lesmono, D., Limansyah, T., & Loedy, N. (2020). A joint return policy for a multi-item perishable inventory model with deterministic demands, return and all-units discount. International Journal of Mathematical, Engineering and Management Sciences, 5(3), 416-431.
Lin, H-D., Chen, Y-R., Chiu, V., & Chiu, Y-S.P. (2019). A decision model for a quality-assured EPQ-based intra-supply chain system considering overtime option. Journal of Applied Engineering Science, 17(3), 362-371.
López-Ruíz, S., & Carmona-Benítez, R.B. (2019). The design of a liquefied natural gas (LNG) distribution network of a company operating in Mexico. Journal of Applied Research and Technology, 17(4), 213-249.
Marchi, B., Zanoni, S., Jaber, M.Y. (2019). Economic production quantity model with learning in production, quality, reliability and energy efficiency. Computers & Industrial Engineering, 129, 502-511.
Mokao, R. (2020). Multi criteria decision making model for producing multiple products at the same time. Management and Production Engineering Review, 11(3), 92-105.
Nahmias, S. (2009). Production & Operations Analysis. McGraw-Hill Inc. New York.
Ortiz-Servin, J.J., Castillo, A., & Talavera, F. (2019). A new methodology to optimize operation cycles in a bwr using heuristic techniques. Journal of Applied Research and Technology, 17(3), 155-162.
Palyanitsina, A., & Sukhikh, A. (2020). Peculiarities of assessing the reservoir propties of clayish reservoirs depending on the water of reservoir pressure maintenance system properties. Journal of Applied Engineering Science, 18(1), 10-14.
Pawar, P.J., & Nandurkar, K.N. (2018). Optimization of single supplier multi buyer multi product supply chain system. Procedia Manufacturing, 26, 21-28.
Pramono, S.N.W., Ulkhaq, M.M., Rachmadina, D.P., Trianto, R., Rachmadani, A.P., Wijayanti, W.R., & Dewi, W.R. (2018). The use of quality management techniques: The application of the new seven tools. International Journal of Applied Science and Engineering, 15(2), 105-112.
Rardin R.L. (1998). Optimization in Operations Research. Prentice-Hall; New Jersey, USA.
Rout, C., Chakraborty, D., & Goswami, A. (2020). An EPQ model for deteriorating items with imperfect production, two Types of inspection errors and rework under complete backordering. International Game Theory Review, 22(2), Art. No. 2040011.
Ruidas, S. Seikh, M.R., & Nayak, P.K. (2020). An EPQ model with stock and selling price dependent demand and variable production rate in interval environment. International Journal of Systems Assurance Engineering and Management, 11(2), 385-399.
Taft, E.W. (1918). The most economical production lot. Iron Age, 101, 1410–1412.
Tantiwattanakul, P., & Dumrongsiri, A. (2019). Supply chain coordination using wholesale prices with multiple products, multiple periods, and multiple retailers: Bi-level optimization approach. Computers & Industrial Engineering, 131, 391-407.
Tian, Q., Guo, W. (2019). Reconfiguration of manufacturing supply chains considering outsourcing decisions and supply chain risks. Journal of Manufacturing Systems, 52(Part B), 217-226
Trisna, T., Marimin, M., Arkeman, Y., & Sunarti, T.C. (2020). Fuzzy multi-objective optimization for wheat flour supply chain considering raw material substitution. International Journal of Industrial Engineering and Management, 11(3), 180-191.