Abstract
A sustainable manufacturing system design can be defined as a process aimed at minimising the negative aspect of both economic and ecological costs. This may be partially achieved through the implementation of lean manufacturing methods in order to reduce production wastes, increase efficiency of manufacturing systems and minimise operational costs. Nevertheless, the concept of lean methods does not include environmental considerations in terms of such as energy consumption and CO2 (carbon dioxide) emissions, which are also important factors today for developing a sustainable manufacturing system. This paper addresses these issues involved in modelling a sustainable manufacturing system allowing an evaluation in energy consumption and CO2 emissions against the total cost using the multi-objective approach. In this work, a multi-objective mathematical model was developed based on a manufacturing system incorporating its economic and ecological parameters towards a minimisation of the total cost, the total energy consumption and CO2 emissions associated with relevant machines, air-conditioning units and lighting bulbs involved in each manufacturing process and material flow. The model was coded using LINGO11 to help gain optimal solutions using the ε-constraint approach and the LP-metrics approach, respectively. The best solution among obtained optimal results was revealed using the max-min approach. Applicability of the proposed method was also examined using collected data from a real case study. The study concluded that the multi-objective mathematical model was useful as an aid for optimizing the manufacturing system design under the economic and ecological constraints.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Lind S, Krassi B, Johansson B, Viitaniemi J, Heilala J, Stahre J, …, & Berlin C (2008) SIMTER: a production simulation tool for joint assessment of ergonomics, level of automation and environmental impacts. In The 18th International Conference on Flexible Automation and Intelligent Manufacturing
Taghdisian H, Pishvaie MR, Farhadi F (2015) Multi-objective optimization approach for green design of methanol plant based on CO 2-efficeincy indicator. J Clean Prod 103:640–650. https://doi.org/10.1016/j.jclepro.2014.05.032
Wang Q, Lassalle S, Mileham AR, Owen GW (2009) Analysis of a linear walking worker line using a combination of computer simulation and mathematical modeling approaches. J Manuf Syst 28(2–3):64–70. https://doi.org/10.1016/j.jmsy.2009.12.001
Heilala J, Vatanen S, Tonteri H, Montonen J, Lind S, Johansson B, Stahre J (2008) Simulation-based sustainable manufacturing system design, Proceedings of the 2008 Winter Simulation Conference. pp 1922-1930
Nujoom R, Wang Q, Bennett N (2016a) An integrated method for sustainable manufacturing systems design, Proceedings of the 3rd International Conferences in MATEC, vol. 70, Istanbul, Turkey, pp 1-5
Pagell M, Yang CL, Krumwiede DW, Sheu C (2004) Does the competitive environment influence the efficacy of investment in environmental management? J Supply Chain Manag 40(3):30–39. https://doi.org/10.1111/j.1745-493X.2004.tb00172.x
Rodger JA, George JA (2017) Triple bottom line accounting for optimizing natural gas sustainability: a statistical linear programming fuzzy ILOWA optimized sustainment model approach to reducing supply chain global cybersecurity vulnerability through information and communications technology. J Clean Prod 142:1931–1949
Jayal AD, Badurdeen F, Dillon JrOW, Jawahir IS (2010) Sustainable manufacturing modeling and optimization challenges at the product, pro-cess and system levels. CIRP J Manuf Sci Technol 2(3):144–152. https://doi.org/10.1016/j.cirpj.2010.03.006
Nishant R, Teo TSH, Goh M (2014) Energy efficiency benefits: is technophilic optimizm justified? IEEE Trans Eng Manag 61(3):476–487. https://doi.org/10.1109/TEM.2014.2314703
Jawahir IS, Jayal AD (2011) Product and process innovation for modeling of sustainable machining processes. In: Seliger G, Khraisheh MMK, Jawahir IS (eds) Adv. Sustain. Manuf. Springer, Berlin, pp 301–307
Pusavec F, Krajnik P, Kopac J (2010) Transitioning to sustainable production—part I: application on machining technologies. J Clean Prod 18(2):174–184. https://doi.org/10.1016/j.jclepro.2009.08.010
Pishvaee MS, Razmi J (2012) Environmental supply chain network design using multi-objective fuzzy mathematical programming. Appl Math Model 36(8):3433–3446. https://doi.org/10.1016/j.apm.2011.10.007
Gielen D, Moriguchi Y (2002) CO2 in the iron and steel industry: an analysis of Japanese emission reduction potentials. Energy Policy 30:349–363
Hidalgo I, Szabo L, Ciscar C, Soria A (2005) Technological prospects and CO2 emission trading analyses in the iron and steel industry, a global model. Energy 30(5):583–610. https://doi.org/10.1016/j.energy.2004.05.022
Koç E, Kaplan E (2007) An investigation on energy consumption in yarn production with special reference to ring spinning. J Fibr Texti Eas Eur 4:18–24
Wang C, Larsson M, Ryman C, Grip CE, Wikström JO, Johnsson A, Engdahl J (2008) A model on CO2 emission reduction in integrated steelmaking by optimization methods. Int J Energy Res 32(12):1092–1106. https://doi.org/10.1002/er.1447
Li C, Zhang X, Zhang S, Suzuki K (2009) Environmentally conscious design of chemical processes and products, multi-optimization method. Chem Eng Res Des 87(2):233–243. https://doi.org/10.1016/j.cherd.2008.07.017
Mohammed A, Wang Q, Alyahya S, Bennett N (2016) Design and optimization of an RFID-enabled automated warehousing system under uncertainties: a multi-criterion fuzzy programming approach. Int J Adv Manuf Technol
Jamshidi R, Ghomi SF, Karimi B (2012) Multi-objective green supply chain optimization with a new hybrid memetic algorithm using the Taguchi method. Scientia Iranica 19(6):1876–1886. https://doi.org/10.1016/j.scient.2012.07.002
Alçada-Almeida L, Coutinho-Rodrigues J, Current J (2009) A multi-objective modeling approach to locating incinerators. Socio Econ Plan Sci 43(2):111–120. https://doi.org/10.1016/j.seps.2008.02.008
Wang F, Lai X, Shi N (2011) A multi-objective optimization for green supply chain network design. Decis Support Syst 51(2):262–269. https://doi.org/10.1016/j.dss.2010.11.020
Abdallah T, Diabat A, Simchi-Levi D (2010) A carbon sensitive supply chain network problem with green procurement, Proceedings of the 40th International Conference In Computers And Industrial Engineering (CIE), 1–6. IEEE
Shaw K, Shankar R, Yadav SS, Thakur LS (2012) Supplier selection using fuzzy AHP and fuzzy multi-objective linear programming for developing low carbon supply chain. Expert Syst Appl 39(9):8182–8192. https://doi.org/10.1016/j.eswa.2012.01.149
Zhou CC, Yin GF, Hu XB (2009) Multi-objective optimization of material selection for sustainable products: artificial neural networks and genetic algorithm approach. Mater Des 30(4):1209–1215. https://doi.org/10.1016/j.matdes.2008.06.006
Hamdy M, Hasan A, Siren K (2011) Applying a multi-objective optimization approach for design of low-emission cost-effective dwellings. Build Environ 46(1):109–123. https://doi.org/10.1016/j.buildenv.2010.07.006
Pinto-Varela T, Barbosa-Póvoa APF, Novais AQ (2011) Bi-objective optimization approach to the design and planning of supply chains: economic versus environmental performances. Comput Chem Eng 35(8):1454–1468. https://doi.org/10.1016/j.compchemeng.2011.03.009
Fesanghary M, Asadi S, Geem ZW (2012) Design of low-emission and energy-efficient residential buildings using a multi-objective optimization algorithm. Build Environ 49:245–250. https://doi.org/10.1016/j.buildenv.2011.09.030
Sharafi M, ELMekkawy TY (2014) Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach. Renew Energy 68:67–79. https://doi.org/10.1016/j.renene.2014.01.011
Sahar V, Arijit B, Byrne PJ (2014) A case analysis of a sustainable food supply chain distribution system—a multi-objective approach. Int J Prod Econ 152:71–87
Bortolini M, Faccio M, Ferrari M, Gamberi M, Pilati F (2016) Fresh food sustainable distribution: cost, delivery time and carbon footprint three-objective optimization. J Food Eng 174:56–67. https://doi.org/10.1016/j.jfoodeng.2015.11.014
Paksoy T, Pehlivan NY, Özceylan E (2012) Fuzzy multi objective optimization of green supply chain network with risk management of included environmental hazards. Hum Ecol Risk Assess 18(5):1121–1152
Harris I, Mumford CL, Naim MM (2014) A hybrid multi-objective approach to capacitated facility location with flexible store allocation for green logistics modeling. Transport Res E Log 66:1–22. https://doi.org/10.1016/j.tre.2014.01.010
EPA (2008) The lean and environment toolkit. U.S. Environmental Protection Agency, http://www.epa.gov/lean/toolkit/index.htm. Accessed June 26
Nujoom R, Mohammed A, Wang Q, Bennett N (2016b) The multi-objective optimization model for a sustainable manufacturing system design. In Renewable Energy Research and Applications (ICRERA), 2016 I.E. international conference on 1134-1140
Nurjanni KP, Carvalho MS, da Costa LAAF (2014) Green supply chain design with multi-objective optimization, Proceedings of the 2014 International Conference on Industrial Engineering and Operations Management Bali, Indonesia, pp 7–9
Amin SH, Zhang G (2013) A multi-objective facility location model for closed-loop supply chain network under uncertain demand and return. Appl Math Model 37(6):416
Mohammed A, Wang Q (2016) The fuzzy multi-objective distribution planner for a green meat supply chain. Int J Prod Econ
Lai YL, Hwang CL (1992) Fuzzy mathematical programming, 1st edn. Springer, Berlin. https://doi.org/10.1007/978-3-642-48753-8
Wang Q, Chatwin CR (2005) Key issues and developments in modelling and simulation-based methodologies for manufacturing systems analysis, design and performance evaluation. Int J Adv Manuf Technol 25(11–12):1254–1265. https://doi.org/10.1007/s00170-003-1957-7
Acknowledgements
The authors would like to express their gratitude to the Ministry of Education in Saudi Arabia for the financial support in this study. Also, the authors would like to thank the anonymous referees whose thorough reviews and insightful comments made a valuable contribution to this article.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Nujoom, R., Wang, Q. & Mohammed, A. Optimisation of a sustainable manufacturing system design using the multi-objective approach. Int J Adv Manuf Technol 96, 2539–2558 (2018). https://doi.org/10.1007/s00170-018-1649-y
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s00170-018-1649-y