Research article Special Issues

Product outsourcing policy for a sustainable flexible manufacturing system with reworking and green investment


  • Received: 16 July 2022 Revised: 19 September 2022 Accepted: 23 September 2022 Published: 28 October 2022
  • Production of defective products is a very general phenomenon. But backorder and shortages occur due to this defective product, and it hampers the manufacturer's reputation along with customer satisfaction. That is why, these outsourced products supply, a portion of required products for in-line production. This study develops a flexible production model that reworks repairable defective products and outsources products to prevent backlogging. A percentage of total in-line production is defective products, which is random, and those defective products are repairable. A green investment helps the reworking process, which has a direct impact on the market demand for products. A classical optimization solves the profit maximization model, and a numerical method proves the global optimal solutions. Sensitivity analysis, managerial insights, and discussions provide the highlights and decision-making strategies for the applicability of this model.

    Citation: Raj Kumar Bachar, Shaktipada Bhuniya, Santanu Kumar Ghosh, Ali AlArjani, Elawady Attia, Md. Sharif Uddin, Biswajit Sarkar. Product outsourcing policy for a sustainable flexible manufacturing system with reworking and green investment[J]. Mathematical Biosciences and Engineering, 2023, 20(1): 1376-1401. doi: 10.3934/mbe.2023062

    Related Papers:

  • Production of defective products is a very general phenomenon. But backorder and shortages occur due to this defective product, and it hampers the manufacturer's reputation along with customer satisfaction. That is why, these outsourced products supply, a portion of required products for in-line production. This study develops a flexible production model that reworks repairable defective products and outsources products to prevent backlogging. A percentage of total in-line production is defective products, which is random, and those defective products are repairable. A green investment helps the reworking process, which has a direct impact on the market demand for products. A classical optimization solves the profit maximization model, and a numerical method proves the global optimal solutions. Sensitivity analysis, managerial insights, and discussions provide the highlights and decision-making strategies for the applicability of this model.



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    [1] B. Sarkar, S. Bhuniya, A sustainable flexible manufacturing-remanufacturing model with improved service and green investment under variable demand, Expert Syst. Appl., 202 (2022), 117154. https://doi.org/10.1016/j.eswa.2022.117154 doi: 10.1016/j.eswa.2022.117154
    [2] B. Sarkar, M. Ullah, M. Sarkar, Environmental and economic sustainability through innovative green products by remanufacturing, J. Cleaner Prod., 332 (2022), 129813. https://doi.org/10.1016/j.jclepro.2021.129813 doi: 10.1016/j.jclepro.2021.129813
    [3] M. Caterino, M. Fera, R. Macchiaroli, D. T. Pham, Cloud remanufacturing: remanufacturing enhanced through cloud technologies, J. Manuf. Syst., 64 (2022), 133–148. https://doi.org/10.1016/j.jmsy.2022.06.003 doi: 10.1016/j.jmsy.2022.06.003
    [4] X. Xia, M. Li, B. Li, H. Wang, The impact of carbon trade on outsourcing remanufacturing, Int. J. Environ. Res. Public Health, 18 (2021), 10804. https://doi.org/10.3390/ijerph182010804 doi: 10.3390/ijerph182010804
    [5] B. Sarkar, A. Debnath, A. S. Chiu, W. Ahmed, Circular economy-driven two-stage supply chain management for nullifying waste, J. Cleaner Prod., 339 (2022), 130513. https://doi.org/10.1016/j.jclepro.2022.130513 doi: 10.1016/j.jclepro.2022.130513
    [6] Y. S. P. Chiu, C. J. Liu, M. H. Hwang, Optimal batch size considering partial outsourcing plan and rework, Jordan J. Mech. Ind. Eng., 11 (2017), 195–200.
    [7] M. De, B. Das, M. Maiti, Green logistics under imperfect production system: a rough age based multi-objective genetic algorithm approach, Comput. Ind. Eng., 119 (2018), 100–113. https://doi.org/10.1016/j.cie.2018.03.021 doi: 10.1016/j.cie.2018.03.021
    [8] X. Lu, J. Shang, S. Y. Wu, G. G. Hegde, L. Vargas, D. Zhao, Impacts of supplier hubris on inventory decisions and green manufacturing endeavors, Eur. J. Oper. Res., 245 (2015), 121–132. https://doi.org/10.1016/j.ejor.2015.02.051 doi: 10.1016/j.ejor.2015.02.051
    [9] M. AlDurgam, K. Adegbola, C. H. Glock, A single-vendor single-manufacturer integrated inventory model with stochastic demand and variable production rate, Int. J. Prod. Econ., 191 (2017), 335–350. https://doi.org/10.1016/j.ijpe.2017.05.017 doi: 10.1016/j.ijpe.2017.05.017
    [10] M. M. AlDurgam, An integrated inventory and workforce planning Markov decision process model with a variable production rate, IFAC-PapersOnLine, 52 (2019), 2792–2797. https://doi.org/10.1016/j.ifacol.2019.11.631 doi: 10.1016/j.ifacol.2019.11.631
    [11] T. Maiti, B. C. Giri, Two-period pricing and decision strategies in a two-echelon supply chain under price-dependent demand, Appl. Math. Modell., 42 (2017), 655–674. https://doi.org/10.1016/j.apm.2016.10.051 doi: 10.1016/j.apm.2016.10.051
    [12] L. Feng, Y. L. Chan, L. E. C$\acute{a}$rdenas-Barr$\acute{a}$n, Pricing and lot-sizing polices for perishable goods when the demand depends on selling price, displayed stocks, and expiration date, Int. J. Prod. Econ., 185 (2017), 11–20. https://doi.org/10.1016/j.ijpe.2016.12.017 doi: 10.1016/j.ijpe.2016.12.017
    [13] B. C. Giri, C. Mondal, T. Maiti, Analysing a closed-loop supply chain with selling price, warranty period and green sensitive consumer demand under revenue sharing contract, J. Cleaner Prod., 190 (2018), 822–837. https://doi.org/10.1016/j.jclepro.2018.04.092 doi: 10.1016/j.jclepro.2018.04.092
    [14] R. Li, J. T. Teng, Pricing and lot-sizing decisions for perishable goods when demand depends on selling price, reference price, product freshness, and displayed stocks, Eur. J. Oper. Res., 270 (2018), 1099–1108. https://doi.org/10.1016/j.ejor.2018.04.029 doi: 10.1016/j.ejor.2018.04.029
    [15] S. C. Das, A. M. Zidan, A. K. Manna, A. A. Shaikh, A. K. Bhunia, An application of preservation technology in inventory control system with price dependent demand and partial backlogging, Alexandria Eng. J., 59 (2020), 1359–1369. https://doi.org/10.1016/j.aej.2020.03.006 doi: 10.1016/j.aej.2020.03.006
    [16] A. K. Agrawal, S. Yadav, Price and profit structuring for single manufacturer multi-buyer integrated inventory supply chain under price-sensitive demand condition, Comput. Ind. Eng., 139 (2020), 106208. https://doi.org/10.1016/j.cie.2019.106208 doi: 10.1016/j.cie.2019.106208
    [17] S. Ruidas, M. R. Seikh, P. K. Nayak, A production inventory model with interval-valued carbon emission parameters under price-sensitive demand, Comput. Ind. Eng., 154 (2021), 107154. https://doi.org/10.1016/j.cie.2021.107154 doi: 10.1016/j.cie.2021.107154
    [18] A. S. Mahapatra, M. S. Mahapatra, B. Sarkar, S. K. Majumder, Benefit of preservation technology with promotion and time-dependent deterioration under fuzzy learning, Expert Syst. Appl., 201 (2022), 117169. https://doi.org/10.1016/j.eswa.2022.117169 doi: 10.1016/j.eswa.2022.117169
    [19] A. Sarkar, R. Guchhait, B. Sarkar, Application of the artificial neural network with multithreading within an inventory model under uncertainty and inflation, Int. J. Fuzzy Syst., 24 (2022), 2318–2332. https://doi.org/10.1007/s40815-022-01276-1 doi: 10.1007/s40815-022-01276-1
    [20] L. Ameknassi, D. Aït-Kadi, N. Rezg, Integration of logistics outsourcing decisions in a green supply chain design: a stochastic multi-objective multi-period multi-product programming model, Int. J. Prod. Econ., 182 (2016), 165–184. https://doi.org/10.1016/j.ijpe.2016.08.031 doi: 10.1016/j.ijpe.2016.08.031
    [21] J. Li, Q. Su, L. Ma, Production and transportation outsourcing decisions in the supply chain under single and multiple carbon policies, J. Cleaner Prod., 141 (2017), 1109–1122. https://doi.org/10.1016/j.jclepro.2016.09.157 doi: 10.1016/j.jclepro.2016.09.157
    [22] K. Chen, H. Zhao, T. Xiao, Outsourcing contracts and ordering decisions of a supply chain under multi-dimensional uncertainties, Comput. Ind. Eng., 130 (2019), 127–141. https://doi.org/10.1016/j.cie.2019.02.010 doi: 10.1016/j.cie.2019.02.010
    [23] M. J. Cortinhal, M. J. Lopes, M. T. Melo, A multi-stage supply chain network design problem with in-house production and partial product outsourcing, Appl. Math. Modell., 70 (2019), 572–594. https://doi.org/10.1016/j.apm.2019.01.046 doi: 10.1016/j.apm.2019.01.046
    [24] J. Heydari, K. Govindan, H. R. E. Nasab, A. A. Taleizadeh, Coordination by quantity flexibility contract in a two-echelon supply chain system: Effect of outsourcing decisions, Int. J. Prod. Econ., 225 (2020), 107586. https://doi.org/10.1016/j.ijpe.2019.107586 doi: 10.1016/j.ijpe.2019.107586
    [25] Y. Lou, L. Feng, S. He, Z. He, X. Zhao, Logistics service outsourcing choices in a retailer-led supply chain, Transp. Res. Part E Logist. Transp. Rev., 141 (2020), 101944. https://doi.org/10.1016/j.tre.2020.101944 doi: 10.1016/j.tre.2020.101944
    [26] S. H. R. Pasandideh, S. T. A. Niaki, A. H. Nobil, L. E. C$\acute{a}$rdenas-Barr$\acute{a}$n, A multiproduct single machine economic production quantity model for an imperfect production system under warehouse construction cost, Int. J. Prod. Econ., 169 (2015), 203–214. https://doi.org/10.1016/j.ijpe.2015.08.004 doi: 10.1016/j.ijpe.2015.08.004
    [27] I. Khan, B. Sarkar, Transfer of risk in supply chain management with joint pricing and inventory decision considering shortages, Mathematics, 9 (2021), 638. https://doi.org/10.3390/math9060638 doi: 10.3390/math9060638
    [28] A. A. Taleizadeh, M. P. S. Khanbaglo, L. E. C$\acute{a}$rdenas-Barr$\acute{a}$n, An EOQ inventory model with partial backordering and reparation of imperfect products, Int. J. Prod. Econ., 182 (2016), 418–434. https://doi.org/10.1016/j.ijpe.2016.09.013 doi: 10.1016/j.ijpe.2016.09.013
    [29] Y. C. Tsao, Q. Zhang, F. C. Chang, L. Vu-Thuy, An imperfect production model under radio frequency identification adoption and trade credit, Appl. Math. Modell., 42 (2017), 493–508. https://doi.org/10.1016/j.apm.2016.10.009 doi: 10.1016/j.apm.2016.10.009
    [30] M. Y. Jani, M. R. Betheja, U. Chaudhari, B. Sarkar, Optimal investment in preservation technology for variable demand under trade-credit and shortages, Mathematics, 9 (2021), 1301. https://doi.org/10.3390/math9111301 doi: 10.3390/math9111301
    [31] S. Panja, S. K. Mondal, Analyzing a four-layer green supply chain imperfect production inventory model for green products under type-2 fuzzy credit period, Comput. Ind. Eng., 129 (2019), 435–453. https://doi.org/10.1016/j.cie.2019.01.059 doi: 10.1016/j.cie.2019.01.059
    [32] A. I. Malik, B. Sarkar, Disruption management in a constrained multi-product imperfect production system, J. Manuf. Syst., 56 (2020), 227–240. https://doi.org/10.1016/j.jmsy.2020.05.015 doi: 10.1016/j.jmsy.2020.05.015
    [33] C. Rout, A. Paul, R. S. Kumar, D. Chakraborty, A. Goswami, Cooperative sustainable supply chain for deteriorating item and imperfect production under different carbon emission regulations, J. Cleaner Prod., 272 (2020), 122170. https://doi.org/10.1016/j.jclepro.2020.122170 doi: 10.1016/j.jclepro.2020.122170
    [34] T. H. Chen, Optimizing pricing, replenishment and rework decision for imperfect and deteriorating items in a manufacturer-retailer channel, Int. J. Prod. Econ., 183 (2017), 539–550. https://doi.org/10.1016/j.ijpe.2016.08.015 doi: 10.1016/j.ijpe.2016.08.015
    [35] Y. S. Chiu, M. F. Wu, S. W. Chiu, H. H. Chang, A simplified approach to the multi-item economic production quantity model with scrap, rework, and multi-delivery, J. Appl. Res. Technol., 13 (2015), 472–476. https://doi.org/10.1016/j.jart.2015.09.004 doi: 10.1016/j.jart.2015.09.004
    [36] A. R. Nia, M. H. Far, S. T. A. Niaki, A hybrid genetic and imperialist competitive algorithm for green vendor managed inventory of multi-item multi-constraint EOQ model under shortage, Appl. Soft Comput., 30 (2015), 353–364. https://doi.org/10.1016/j.asoc.2015.02.004 doi: 10.1016/j.asoc.2015.02.004
    [37] M. Tayyab, M. S. Habib, M. S. S. Jajja, B. Sarkar, Economic assessment of a serial production system with random imperfection and shortages: a step towards sustainability, Comput. Ind. Eng., 177 (2022), 108398. https://doi.org/10.1016/j.cie.2022.108398 doi: 10.1016/j.cie.2022.108398
    [38] L. Moussawi-Haidar, M. Salameh, W. Nasr, Production lot sizing with quality screening and rework, Appl. Math. Modell., 40 (2016), 3242–3256. https://doi.org/10.1016/j.apm.2015.09.095 \newpage doi: 10.1016/j.apm.2015.09.095
    [39] S. Pal, G. S. Mahapatra, A manufacturing-oriented supply chain model for imperfect quality with inspection errors, stochastic demand under rework and shortages, Comput. Ind. Eng., 106 (2017), 299–314. https://doi.org/10.1016/j.cie.2017.02.003 doi: 10.1016/j.cie.2017.02.003
    [40] D. Sonntag, G. P. Kiesmüller, Disposal versus rework–inventory control in a production system with random yield, Eur. J. Oper. Res., 267 (2018), 138–149. https://doi.org/10.1016/j.ejor.2017.11.019 doi: 10.1016/j.ejor.2017.11.019
    [41] M. Al-Salamah, Economic production quantity in an imperfect manufacturing process with synchronous and asynchronous flexible rework rates, Oper. Res. Perspect., 6 (2019), 100103. https://doi.org/10.1016/j.orp.2019.100103 doi: 10.1016/j.orp.2019.100103
    [42] F. Lin, T. Jia, R. Y. Fung, P. Wu, Impacts of inspection rate on integrated inventory models with defective items considering capacity utilization: rework-versus delivery-priority, Comput. Ind. Eng., 156 (2021), 107245. https://doi.org/10.1016/j.cie.2021.107245 doi: 10.1016/j.cie.2021.107245
    [43] B. Sarkar, J. Joo, Y. Kim, H. Park, M. Sarkar, Controlling defective items in a complex multi-phase manufacturing system, RAIRO-Oper. Res., 56 (2022), 871–889. https://doi.org/10.1051/ro/2022019 doi: 10.1051/ro/2022019
    [44] A. Sepehri, U. Mishra, M. L. Tseng, B. Sarkar, Joint pricing and inventory model for deteriorating items with maximum lifetime and controllable carbon emissions under permissible delay in payments, Mathematics, 9 (2021), 470. https://doi.org/10.3390/math9050470 doi: 10.3390/math9050470
    [45] S. Kumar, M. Sigroha, K. Kumar, B. Sarkar, Manufacturing/remanufacturing based supply chain management under advertisements and carbon emission process, RAIRO-Oper. Res., 56 (2022), 831–851. https://doi.org/10.1051/ro/2021189 doi: 10.1051/ro/2021189
    [46] A. Garai, B. Sarkar, Economically independent reverse logistics of customer-centric closed-loop supply chain for herbal medicines and biofuel, J. Cleaner Prod., 334 (2022), 129977. https://doi.org/10.1016/j.jclepro.2021.129977 doi: 10.1016/j.jclepro.2021.129977
    [47] B. Sarkar, B. Mridha, S. Pareek, A sustainable smart multi-type biofuel manufacturing with the optimum energy utilization under flexible production, J. Cleaner Prod., 332 (2022), 129869. https://doi.org/10.1016/j.jclepro.2021.129869 doi: 10.1016/j.jclepro.2021.129869
    [48] A. S. H. Kugele, W. Ahmed, B. Sarkar, Geometric programming solution of second degree difficulty for carbon ejection controlled reliable smart production system, RAIRO-Oper. Res., 56 (2022), 1013–1029. https://doi.org/10.1051/ro/2022028 doi: 10.1051/ro/2022028
    [49] I. Moon, W. Y. Yun, B. Sarkar, Effects of variable setup cost, reliability, and production costs under controlled carbon emissions in a reliable production system, Eur. J. Ind. Eng., 16 (2022), 371–397. https://doi.org/10.1504/EJIE.2022.123748 doi: 10.1504/EJIE.2022.123748
    [50] B. Sarkar, S. Kar, K. Basu, R. Guchhait, A sustainable managerial decision-making problem for a substitutable product in a dual-channel under carbon tax policy, Comput. Ind. Eng., 172 (2022) 108635. https://doi.org/10.1016/j.cie.2022.108635 doi: 10.1016/j.cie.2022.108635
    [51] M. Rinaldi, M. Caterino, M. Fera, P. Manco, R. Macchiaroli, Technology selection in green supply chains-the effects of additive and traditional manufacturing, J. Cleaner Prod., 282 (2021), 124554. https://doi.org/10.1016/j.jclepro.2020.124554 doi: 10.1016/j.jclepro.2020.124554
    [52] P. Ahi, C. Searcy, A comparative literature analysis of definitions for green and sustainable supply chain management, J. Cleaner Prod., 52 (2013), 329–341. https://doi.org/10.1016/j.jclepro.2013.02.018 doi: 10.1016/j.jclepro.2013.02.018
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