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Facing energy-aware scheduling: a multi-objective extension of a scheduling support system for improving energy efficiency in a moulding industry

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Abstract

Nowadays most industries do not integrate product, process and energy data. Costs due to energy consumption are often considered externalities and energy efficiency is not deemed a relevant performance criterion. In energy-intensive processes, as injection moulding, the specific energy consumption, embedded inside the same products, depends on the machine–product combinations. Multi-objective scheduling, including the energy data acquired from shop floor and allocation criteria, is a valuable approach to improve energy efficiency. This paper presents the extension of a commercial detailed scheduling support system developed within a regional Italian project aiming at providing tools to manufacturing industry for improving energy efficiency. The project designed a monitoring system developed by instrumenting injection moulding presses to acquire the energy consumption for each product–machine combination. The commercial scheduling system was extended by implementing a multi-objective metaheuristic scheduling approach. The experimental assessment of the proposed approach involved a major producer of plastic dispensers. The extended algorithm simultaneously optimizes the total weighted tardiness, the total setup and the energy consumption costs. The obtained results, produced for a real test case and a set of random generated instances, show the effectiveness of the proposed approach.

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References

  • Bruzzone AAG, Anghinolfi D, Paolucci M, Tonelli F (2012) Energy-aware scheduling for improving manufacturing process sustainability: a mathematical model for flexible flow shops. CIRP Ann Manuf Technol 61(1):459–462

    Article  Google Scholar 

  • Dai M, Tang D, Giret A, Salido MA, Li WD (2013) Energy-efficient scheduling for a flexible flow shop using an improved genetic-simulated annealing algorithm. Robot Comput Integr Manuf 29:418–429

    Article  Google Scholar 

  • Despeisse M, Ball PD, Evans S, Levers A (2012) Industrial ecology at factory level—a conceptual model. J Clean Prod 31:30–39

    Article  Google Scholar 

  • Fang K, Uhan N, Zhao F, Sutherland JW (2011) A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction. J Manuf Syst 30:234–240

    Article  Google Scholar 

  • Hall NG, Posner ME (2001) Generating experimental date for computational testing with machine scheduling applications. Oper Res 49:854–865

    Article  MathSciNet  MATH  Google Scholar 

  • Hoogeveen H (2005) Multicriteria scheduling. Eur J Oper Res 167:592–623

    Article  MathSciNet  MATH  Google Scholar 

  • Jovane F, Yoshikawa H, Alting L, Bor CR et al (2008) The incoming global technological and industrial revolution towards competitive sustainable manufacturing. CIRP Ann Manuf Technol 57(2):641–659

    Article  Google Scholar 

  • Kostka G, Moslener U, Andreas J (2013) Barriers to increasing energy efficiency: evidence from small- and medium-sized enterprises in China. J Clean Prod 57:59–68

    Article  Google Scholar 

  • Kuster T, Lutzenberger M, Freund D, Albayrak S (2013) Distributed evolutionary optimisation for electricity price responsive manufacturing using multi-agent system technology. Int J Adv Intell Syst 6(1–2):27–40

    Google Scholar 

  • Langer T, Schlegel A, Stoldt J, Putz M (2014) A model-based approach to energy-saving manufacturing control strategies. Procedia CIRP 15:123–128

    Article  Google Scholar 

  • Lawler EL (1997) A pseudopolynomial algorithm for sequencing jobs to minimize total tardiness. Ann Discret Math 1:331–342

    Article  MathSciNet  Google Scholar 

  • Le CV, Pang CK (2013) Fast reactive scheduling to minimize tardiness penalty and energy cost under power consumption uncertainties. Comput Ind Eng 66:406–417

    Article  Google Scholar 

  • Liu Y, Dong H, Lohse N, Petrovic S, Gindy N (2013) An investigation into minimising total energy consumption and total weighted tardiness in job shops. J Clean Prod 65:87–96

    Article  Google Scholar 

  • Lu N, Gong G, Yang Y, Lu J (2012) Multi-objective process parameter optimization for energy saving in injection moulding process. J Zhejiang Univ Sci A 13(5):382–394

  • Luo H, Du B, Huang GQ, Chen H, Li X (2013) Hybrid flow shop scheduling considering machine electricity consumption cost. Int J Prod Econ 146:423–439

    Article  Google Scholar 

  • Mattis J, Sheng P, DiScipio W, Leong K (1996) A framework for analysing energy efficient injection-molding die casting. In: IEEE International conference on electronics and the environment. Dallas, TX, pp 207–212

  • Michaloski JL, Shao G, Arinez J, Lyons K, Leong S, Riddick F (2011) Analysis of sustainable manufacturing using simulation for integration of production and building service. In: SimAUD 2011 symposium on simulation for architecture and urban design, pp 93–101

  • Mitra S, Grossmann IE, Pinto JM, Arora N (2012) Optimal production planning under time-sensitive electricity prices for continuous power-intensive processes. Comput Chem Eng 38:171–184

    Article  Google Scholar 

  • Moon JY, Shin K, Park J (2013) Optimization of production scheduling with time-dependent and machine-dependent electricity cost for industrial energy efficiency. Int J Adv Manuf Technol 68(1–4):523–535

    Article  Google Scholar 

  • Mouzon G, Yildirim MB, Twomey J (2007) Operational methods for minimization of energy consumption of manufacturing equipment. Int J Prod Res 45:4247–4271

    Article  MATH  Google Scholar 

  • Mukherjee K (2008) Energy use efficiency in U.S. manufacturing: a nonparametric analysis. Energy Econ 30:76–96

    Article  Google Scholar 

  • Nilakantan JM, Huang GQ, Ponnambalam SG (2015) An investigation on minimizing cycle time and total energy consumption in robotic assembly line systems. J Clean Prod 90:311–325

    Article  Google Scholar 

  • Pinedo ML (2012) Scheduling—theory, algorithms, and systems, 4th edn. Springer, New York

    MATH  Google Scholar 

  • Seow Y, Rahimifard S (2011) A framework for modelling energy consumption within manufacturing systems. CIRP J Manuf Sci Technol 4(3):258–264

    Article  Google Scholar 

  • Shrouf F, Ordieres-Meré J, García-Sánchez A, Ortega-Mier M (2014) Optimizing the production scheduling of a single machine to minimize total energy consumption costs. J Clean Prod 67:197–207

    Article  Google Scholar 

  • Soroush HM (2010) Solving a stochastic single machine problem with initial idle time and quadratic objective. Comput Oper Res 37:1328–1347

    Article  MathSciNet  MATH  Google Scholar 

  • Sutherland JW, Rivera JL, Brown KL, Law M et al (2008), Challenges for the manufacturing enterprise to achieve sustainable development. In: Mitsuishi M, Ueda K, Kimura F (eds) Manufacturing systems and technologies for the new frontier. 41st CIRP conference on manufacturing systems, pp 15–18

  • Taticchi P, Tonelli F, Pasqualino R (2013) Performance measurement of sustainable supply chains: a literature review and a research agenda. Int J Product Perform Manag 62(8):782–804

  • Thiriez A, Dahmus J, Gutowski T (2006) Electrical energy requirements for manufacturing processes. In: 13th CIRP international conference on life cycle engineering (LCE), Leuven, Belgium pp 623-628

  • Thollander P, Rohdin P, Moshfegh B, Karlsson M, Sderstrm M, Trygg L (2013) Energy in Swedish industry 2020—current status, policy instruments, and policy implications. J Clean Prod 51:109–117

    Article  Google Scholar 

  • Tonelli F, Evans S, Taticchi P (2013) Industrial sustainability: challenges, perspectives, actions. Int J Bus Innov Res 7(2):143–163

    Article  Google Scholar 

  • United Nations (1998) Kyoto protocol to the United Nations framework convention on climate change. UN Treaty Database. http://unfccc.int/resource/docs/convkp/kpeng.pdf

  • Weinert N, Chiotellis S, Seliger G (2011) Methodology for planning and operating energy-efficient production systems. CIRP Ann Manuf Technol 60:41–44

    Article  Google Scholar 

  • Yan H, Fei L, Hua-jun C, Cong-bo L (2005) A bi-objective model for job-shop scheduling problem to minimize both energy consumption and makespan. J Cent South Univ Technol 12(2):167–171

    Article  Google Scholar 

  • Yi Q, Li C, Tang Y, Member S (2012) A new operational framework to job shop scheduling for reducing carbon emissions. In: 8th IEEE international conference on automation science and engineering, pp 58–63

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Authors and Affiliations

  1. Department of Informatics, Bioengineering, Robotics, and Systems Engineering, University of Genova, Genova, Italy

    Massimo Paolucci & Davide Anghinolfi

  2. Department of Mechanical Engineering, Energy, Management and Transports, University of Genova, Genova, Italy

    Flavio Tonelli

Authors
  1. Massimo Paolucci
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  2. Davide Anghinolfi
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  3. Flavio Tonelli
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Corresponding author

Correspondence to Massimo Paolucci.

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Conflict of interest

M. Paolucci, D. Anghinolfi and F. Tonelli state that there are no conflicts of interest.

Additional information

Communicated by V. Loia.

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Paolucci, M., Anghinolfi, D. & Tonelli, F. Facing energy-aware scheduling: a multi-objective extension of a scheduling support system for improving energy efficiency in a moulding industry. Soft Comput 21, 3687–3698 (2017). https://doi.org/10.1007/s00500-015-1987-8

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  • DOI: https://doi.org/10.1007/s00500-015-1987-8

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