Research article Special Issues

Sustainable green production model considering variable demand, partial outsourcing, and rework

  • Received: 05 March 2022 Revised: 01 May 2022 Accepted: 31 May 2022 Published: 22 June 2022
  • Social activities, economic benefits, and environmental friendly approach are very much essential for a sustainable production system. This is widely observed during the Covid-19 pandemic situation. The demand for essential goods in the business sector is always changing due to different unavoidable situations. The proposed study introduces a variable demand for controlling the fluctuating demand. However, a reworking of produced imperfect products makes the production model more profitable. Partial outsourcing of the good quality products has made the production system more popular and profitable. Separate holding cost for the reworked and produced products are very helpful idea for the proposed model. Moreover, consumption of energy during various purpose are considered. Separate green investment make the model more sustainable and eco-friendly. The main focus of the model is to find the maximum profit through considering optimum value of lot size quantity, average selling price, and green investment. The classical optimization technique is utilized here for optimizing the solution theoretically. The use of concave 3D graphs, different examples, and sensitivity analyses are considered here. Furthermore, managerial insights from this study can be used for industry improvement.

    Citation: Raj Kumar Bachar, Shaktipada Bhuniya, Santanu Kumar Ghosh, Biswajit Sarkar. Sustainable green production model considering variable demand, partial outsourcing, and rework[J]. AIMS Environmental Science, 2022, 9(3): 325-353. doi: 10.3934/environsci.2022022

    Related Papers:

  • Social activities, economic benefits, and environmental friendly approach are very much essential for a sustainable production system. This is widely observed during the Covid-19 pandemic situation. The demand for essential goods in the business sector is always changing due to different unavoidable situations. The proposed study introduces a variable demand for controlling the fluctuating demand. However, a reworking of produced imperfect products makes the production model more profitable. Partial outsourcing of the good quality products has made the production system more popular and profitable. Separate holding cost for the reworked and produced products are very helpful idea for the proposed model. Moreover, consumption of energy during various purpose are considered. Separate green investment make the model more sustainable and eco-friendly. The main focus of the model is to find the maximum profit through considering optimum value of lot size quantity, average selling price, and green investment. The classical optimization technique is utilized here for optimizing the solution theoretically. The use of concave 3D graphs, different examples, and sensitivity analyses are considered here. Furthermore, managerial insights from this study can be used for industry improvement.



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    [1] Sarkar B, Bhuniya S (2022) A sustainable flexible manufacturing-remanufacturing model with improved service and green investment under variable demand. Expert Systems With Applications 202: 117154. https://doi.org/10.1016/j.eswa.2022.117154 doi: 10.1016/j.eswa.2022.117154
    [2] Bhuniya S, Pareek S, Sarkar B, et al. (2021) A smart production process for the optimum energy consumption with maintenance policy under a supply chain management. Processes 9: 19. https://doi.org/10.3390/pr9010019 doi: 10.3390/pr9010019
    [3] Kumar R, Chandrawat RK, Sarkar B, et al. (2021) An advanced optimization technique for smart production using $\alpha$-cut based quadrilateral fuzzy number. International Journal of Fuzzy Systems 23: 107-127. https://doi.org/10.1007/s40815-020-01002-9 doi: 10.1007/s40815-020-01002-9
    [4] Dey BK, Bhuniya S, Sarkar B (2021) Involvement of controllable lead time and variable demand for a smart manufacturing system under a supply chain management. Expert Systems with Applications 184: 115464. https://doi.org/10.1016/j.eswa.2021.115464 doi: 10.1016/j.eswa.2021.115464
    [5] Sepehri A, Mishra U, Sarkar B (2021) A sustainable production-inventory model with imperfect quality under preservation technology and quality improvement investment. Journal of Cleaner Production 310: 127332. https://doi.org/10.1016/j.jclepro.2021.127332 doi: 10.1016/j.jclepro.2021.127332
    [6] Ahmed W, Moazzam M, Sarkar B, et al. (2021) Synergic effect of reworking for imperfect quality items with the integration of multi-period delay-in-payment and partial backordering in global supply chains. Engineering 7: 260-271. https://doi.org/10.1016/j.eng.2020.07.022 doi: 10.1016/j.eng.2020.07.022
    [7] Vandana, Singh SR, Yadav D, et al. (2021) Impact of energy and carbon emission of a supply chain management with two-level trade-credit policy. Energies 14: 1569. https://doi.org/10.3390/en14061569 doi: 10.3390/en14061569
    [8] Sepehri A, Mishra U, Tseng ML, et al. (2021) Joint pricing and inventory model for deteriorating items with maximum lifetime and controllable carbon emissions under permissible delay in payments. Mathematics 9: 470. https://doi.org/10.3390/math9050470 doi: 10.3390/math9050470
    [9] Chen TH (2017) Optimizing pricing, replenishment and rework decision for imperfect and deteriorating items in a manufacturer-retailer channel. International Journal of Production Economics 183: 539-550. https://doi.org/10.1016/j.ijpe.2016.08.015 doi: 10.1016/j.ijpe.2016.08.015
    [10] Bhuniya S, Sarkar B, Pareek S (2019) Multi-product production system with the reduced failure rate and the optimum energy consumption under variable demand. Mathematics 7: 465. https://doi.org/10.3390/math7050465 doi: 10.3390/math7050465
    [11] Dey O, Giri BC (2019) A new approach to deal with learning in inspection in an integrated vendor-buyer model with imperfect production process. Computers & Industrial Engineering 131: 515-523. https://doi.org/10.1016/j.cie.2018.12.028 doi: 10.1016/j.cie.2018.12.028
    [12] Malik AI, Sarkar B (2020) Disruption management in a constrained multi-product imperfect production system. Journal of manufacturing systems 56: 227-240. https://doi.org/10.1016/j.jmsy.2020.05.015 doi: 10.1016/j.jmsy.2020.05.015
    [13] Chiu YS, Liu CJ, Hwang MH (2017) Optimal batch size considering partial outsourcing plan and rework. Jordan Journal of Mechanical and Industrial Engineering 11: 195-200.
    [14] Yadav D, Kumari R, Kumar N, et al. (2021) Reduction of waste and carbon emission through the selection of items with cross-price elasticity of demand to form a sustainable supply chain with preservation technology. Journal of Cleaner Production 297: 126298. https://doi.org/10.1016/j.jclepro.2021.126298 doi: 10.1016/j.jclepro.2021.126298
    [15] Taleizadeh AA, C$\acute{a}$rdenas-Barr$\acute{a}$n LE, Mohammadi B (2014) A deterministic multi product single machine EPQ model with backordering, scraped products, rework and interruption in manufacturing process. International Journal of Production Economics 150: 9-27. https://doi.org/10.1016/j.ijpe.2013.11.023 doi: 10.1016/j.ijpe.2013.11.023
    [16] Chiu YS, Wu MF, Chiu SW, et al. (2015) A simplified approach to the multi-item economic production quantity model with scrap, rework, and multi-delivery. Journal of applied research and technology 13: 472-476. https://doi.org/10.1016/j.jart.2015.09.004 doi: 10.1016/j.jart.2015.09.004
    [17] Chiu SW, Wu CS, Tseng CT (2019) Incorporating an expedited rate, rework, and a multi-shipment policy into a multi-item stock refilling system. Operations Research Perspectives 6: 100115. https://doi.org/10.1016/j.orp.2019.100115 doi: 10.1016/j.orp.2019.100115
    [18] Nia AR, Far MH, Niaki ST (2015) A hybrid genetic and imperialist competitive algorithm for green vendor managed inventory of multi-item multi-constraint EOQ model under shortage. Applied Soft Computing 30: 353-364. https://doi.org/10.1016/j.asoc.2015.02.004 doi: 10.1016/j.asoc.2015.02.004
    [19] Manna AK, Das B, Dey JK, et al. (2017) Two layers green supply chain imperfect production inventory model under bi-level credit period. Tékhne 15: 124-142. https://doi.org/10.1016/j.tekhne.2017.10.001 doi: 10.1016/j.tekhne.2017.10.001
    [20] Raza SA, Rathinam S, Turiac M, et al. (2018) An integrated revenue management framework for a firm's greening, pricing and inventory decisions. International Journal of Production Economics 195: 373-390. https://doi.org/10.1016/j.ijpe.2016.11.014 doi: 10.1016/j.ijpe.2016.11.014
    [21] Mishra U, Wu JZ, Tsao YC, et al. (2020) Sustainable inventory system with controllable non-instantaneous deterioration and environmental emission rates. Journal of Cleaner Production 244: 118807. https://doi.org/10.1016/j.jclepro.2019.118807 doi: 10.1016/j.jclepro.2019.118807
    [22] Dev NK, Shankar R, Swami S (2020) Diffusion of green products in industry 4.0: Reverse logistics issues during design of inventory and production planning system. International Journal of Production Economics 223: 107519. https://doi.org/10.1016/j.ijpe.2019.107519 doi: 10.1016/j.ijpe.2019.107519
    [23] Mishra U, Wu JZ, Sarkar B (2021) Optimum sustainable inventory management with backorder and deterioration under controllable carbon emissions. Journal of Cleaner Production 279: 123699. https://doi.org/10.1016/j.jclepro.2020.123699 doi: 10.1016/j.jclepro.2020.123699
    [24] Alfares HK, Ghaithan AM (2016) Inventory and pricing model with price-dependent demand, time-varying holding cost, and quantity discounts. Computers & Industrial Engineering 94: 170-177. https://doi.org/10.1016/j.cie.2016.02.009 doi: 10.1016/j.cie.2016.02.009
    [25] Feng L, Chan YL, C$\acute{a}$rdenas-Barr$\acute{a}$n LE (2017) Pricing and lot-sizing policies for perishable goods when demand depends on selling price, displayed stocks, and expiration date. International Journal of Production Economics 185: 11-20. https://doi.org/10.1016/j.ejor.2018.04.029 doi: 10.1016/j.ejor.2018.04.029
    [26] Maiti T, Giri BC (2017) Two-period pricing and decision strategies in a two-echelon supply chain under price-dependent demand. Applied Mathematical Modelling 42: 655-674. https://doi.org/10.1016/j.apm.2016.10.051 doi: 10.1016/j.apm.2016.10.051
    [27] Li R, Teng JT (2018) Pricing and lot-sizing decisions for perishable goods when demand depends on selling price, reference price, product freshness, and displayed stocks. European Journal of Operational Research 270: 1099-1108. https://doi.org/10.1016/j.ejor.2018.04.029 doi: 10.1016/j.ejor.2018.04.029
    [28] Mishra U, Wu JZ, Tseng ML (2019) Effects of a hybrid-price-stock dependent demand on the optimal solutions of a deteriorating inventory system and trade credit policy on re-manufactured product. Journal of Cleaner Production 241: 118282. https://doi.org/10.1016/j.jclepro.2019.118282 doi: 10.1016/j.jclepro.2019.118282
    [29] Khan MA, Shaikh AA, Konstantaras I, et al. (2020) Inventory models for perishable items with advanced payment, linearly time-dependent holding cost and demand dependent on advertisement and selling price. International Journal of Production Economics 230: 107804. https://doi.org/10.1016/j.ijpe.2020.107804 doi: 10.1016/j.ijpe.2020.107804
    [30] Chu C, Chu F, Zhong J, et al. (2013) A polynomial algorithm for a lot-sizing problem with backlogging, outsourcing and limited inventory. Computers & Industrial Engineering 64: 200-210. https://doi.org/10.1016/j.cie.2012.08.007 doi: 10.1016/j.cie.2012.08.007
    [31] Chen K, Xiao T (2015) Outsourcing strategy and production disruption of supply chain with demand and capacity allocation uncertainties. International Journal of Production Economics 170: 243-257. https://doi.org/10.1016/j.ijpe.2015.09.028 doi: 10.1016/j.ijpe.2015.09.028
    [32] Li J, Su Q, Ma L (2017) Production and transportation outsourcing decisions in the supply chain under single and multiple carbon policies. Journal of Cleaner Production 141: 1109-1122. https://doi.org/10.1016/j.jclepro.2016.09.157 doi: 10.1016/j.jclepro.2016.09.157
    [33] Abriyantoro D, Dong J, Hicks C, et al. (2019) A stochastic optimisation model for biomass outsourcing in the cement manufacturing industry with production planning constraints. Energy 169: 515-526. https://doi.org/10.1016/j.energy.2018.11.114 doi: 10.1016/j.energy.2018.11.114
    [34] Heydari J, Govindan K, Nasab HR, et al. (2020) Coordination by quantity flexibility contract in a two-echelon supply chain system: effect of outsourcing decisions. International Journal of Production Economics 225: 107586. https://doi.org/10.1016/j.ijpe.2019.107586 doi: 10.1016/j.ijpe.2019.107586
    [35] Omair M, Noor S, Tayyab M, et al. (2021) The selection of the sustainable suppliers by the development of a decision support framework based on analytical hierarchical process and fuzzy inference system. International Journal of Fuzzy Systems 23: 1986-2003. https://doi.org/10.1007/s40815-021-01073-2 doi: 10.1007/s40815-021-01073-2
    [36] Zhalechian M, Tavakkoli-Moghaddam R, Zahiri B, et al. (2016) Sustainable design of a closed-loop location-routing-inventory supply chain network under mixed uncertainty. Transportation Research Part E: Logistics and Transportation Review 89: 182-214. https://doi.org/10.1016/j.tre.2016.02.011 doi: 10.1016/j.tre.2016.02.011
    [37] Tiwari S, Daryanto Y, Wee HM (2018) Sustainable inventory management with deteriorating and imperfect quality items considering carbon emission. Journal of Cleaner Production 192: 281-292. https://doi.org/10.1016/j.jclepro.2018.04.261 doi: 10.1016/j.jclepro.2018.04.261
    [38] Lu CJ, Yang CT, Yen HF (2020) Stackelberg game approach for sustainable production-inventory model with collaborative investment in technology for reducing carbon emissions. Journal of Cleaner Production 270: 121963. https://doi.org/10.1016/j.jclepro.2020.121963 doi: 10.1016/j.jclepro.2020.121963
    [39] Ullah M, Asghar I, Zahid M, et al. (2021) Ramification of remanufacturing in a sustainable three-echelon closed-loop supply chain management for returnable products. Journal of Cleaner Production 290: 125609. https://doi.org/10.1016/j.jclepro.2020.125609 doi: 10.1016/j.jclepro.2020.125609
    [40] Guchhait R, Dey BK, Bhuniya S, et al. (2020) Investment for process quality improvement and setup cost reduction in an imperfect production process with warranty policy and shortages. RAIRO-Operations Research 54: 251-266. https://doi.org/10.1051/ro/2018101 doi: 10.1051/ro/2018101
    [41] Garai A, Chowdhury S, Sarkar B, et al. (2021) Cost-effective subsidy policy for growers and biofuels-plants in closed-loop supply chain of herbs and herbal medicines: An interactive bi-objective optimization in T-environment. Applied Soft Computing 100: 106949. https://doi.org/10.1016/j.asoc.2020.106949 doi: 10.1016/j.asoc.2020.106949
    [42] Habib MS, Asghar O, Hussain A, et al. (2021) A robust possibilistic programming approach toward animal fat-based biodiesel supply chain network design under uncertain environment. Journal of Cleaner Production 278: 122403. https://doi.org/10.1016/j.jclepro.2020.122403 doi: 10.1016/j.jclepro.2020.122403
    [43] Samanta S, Dubey VK, Sarkar B (2021) Measure of influences in social networks. Applied Soft Computing 99: 106858. https://doi.org/10.1016/j.asoc.2020.106858 doi: 10.1016/j.asoc.2020.106858
    [44] Sardar SK, Sarkar B, Kim B (2021) Integrating machine learning, radio frequency identification, and consignment policy for reducing unreliability in smart supply chain management. Processes 9: 247. https://doi.org/10.3390/pr9020247 doi: 10.3390/pr9020247
    [45] Bhuniya S, Pareek S, Sarkar B (2021) A supply chain model with service level constraints and strategies under uncertainty. Alexandria Engineering Journal 60: 6035-6052. https://doi.org/10.1016/j.aej.2021.03.039 doi: 10.1016/j.aej.2021.03.039
    [46] Mahapatra AS, Soni NH, Mahapatra MS, et al. (2021) A continuous review production-inventory system with a variable preparation time in a fuzzy random environment. Mathematics 9: 747. https://doi.org/10.3390/math9070747 doi: 10.3390/math9070747
    [47] Tayyab M, Sarkar B (2021) An interactive fuzzy programming approach for a sustainable supplier selection under textile supply chain management. Computers & Industrial Engineering 155: 107164. https://doi.org/10.1016/j.cie.2021.107164 doi: 10.1016/j.cie.2021.107164
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