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An Investigation into Minimising Total Energy Consumption, Total Energy Cost and Total Tardiness Based on a Rolling Blackout Policy in a Job Shop

Conference paper
Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, volume 397)

Abstract

Manufacturing enterprises nowadays face the challenge of increasing energy price and emission reduction requirements. An approach to reduce energy cost and become environmental friendly is to incorporate energy consumption into consideration while making the scheduling plans. The research presented by this paper is set in a classical job shop circumstance, the model for the triple objectives problem that minimise total electricity cost, total electricity consumption and total tardiness when the Rolling Blackout policy is applied. A case study based on a 3*3 job shop is presented to show how scheduling plans affect electricity consumption and its related cost, and to prove the feasibility of the model.

Keywords

Energy efficient production planning sustainable manufacturing job shop scheduling 

References

  1. 1.
    Tang, D., Li, L., Du, K.: On the Developmental Path of Chinese Manufac-turing Industry Based on Resource Restraint. Jiangsu Social Sciences 4, 51–58 (2006)Google Scholar
  2. 2.
    Mouzon, G., Yildirim, M.B.: A framework to minimize total energy con-sumption and total tardiness on a single machine. In: Proceedings of 4th Annual GRASP Symposium, vol. 1(2), pp. 105–116 (2008)Google Scholar
  3. 3.
    Dahmus, J.B., Gutowski, T.G.: An environmental analysis of machining. In: Proceedings of ASME International Mechanical Engineering Congress and RD&D Expo 2004, pp. 1–10 (2004)Google Scholar
  4. 4.
    Munoz, A.A., Sheng, P.: An analytical approach for determining the envi-ronmental impact of machining processes. Journal of Materials Processing Technology 53, 736–758 (1995)CrossRefGoogle Scholar
  5. 5.
    Kordonowy, D.: A power assessment of machining tools. Massachusetts Institue of Technology (2003)Google Scholar
  6. 6.
    Mouzon, G., Yildirim, M.B., Twomey, J.: Operational methods for mini-mization of energy consumption of manufacturing equipment. Interna-tional Journal of Production Research 45(18-19), 4247–4271 (2007)CrossRefzbMATHGoogle Scholar
  7. 7.
    Mouzon, G.: Operational methods and models for minimization of energy consumption in a manufacturing environment. Wichita State University (2008)Google Scholar
  8. 8.
    He, Y., Liu, B., Zhang, X., Gao, H., Liu, X.: A modeling method of task-oriented energy consumption for machining manufacturing system. Journal of Cleaner Production 23(1), 167–174 (2012)CrossRefGoogle Scholar
  9. 9.
    Herrmann, C., Thiede, S.: Process chain simulation to foster energy effi-ciency in manufacturing. CIRP Journal of Manufacturing Science and Technology 1, 221–229 (2009)CrossRefGoogle Scholar
  10. 10.
    Özgüven, C., Özbakır, L., Yavuz, Y.: Mathematical models for job-shop scheduling problems with routing and process plan flexibility. Applied Mathematical Modelling 34(6), 1539–1548 (2010)MathSciNetCrossRefzbMATHGoogle Scholar
  11. 11.
    Antonio, J., Petrovic, V.S.: A new dispatching rule based genetic algorithm for the multi-objective job shop problem. Journal of Heuristics, 771–793 (2010)Google Scholar
  12. 12.
    Dietmair, A., Verl, A.: Energy Consumption Forecasting and Optimisation for Tool Machines. Energy, 63–67 (2009)Google Scholar
  13. 13.
    Diaz, N., et al.: Machine Tool Design and Operation Strategies for Green Manufacturing. In: Proceedings of 4th CIRP Internatinal Conference on High Performance Cutting, pp. 1–6 (2010)Google Scholar
  14. 14.
    Avram, I.O.: Machine Tool Use Phase: Modeling and Analysis with Environmental Considerations,” ÉCOLE POLYTECHNIQUE FÉDÉRALE DE LAUSANNE (2010)Google Scholar
  15. 15.
    Vázquez-Rodríguez, J.A., Petrovic, S.: A new dispatching rule based genetic algorithm for the multi-objective job shop problem. Journal of Heuristics 16(6), 771–793 (2009)CrossRefzbMATHGoogle Scholar
  16. 16.
    Liu, M., Wu, C.: Intelligent Optimization Scheduling Algorithms for Manufacturing Process and Their Applications, p. 334. National Defense Industry Press (2008)Google Scholar
  17. 17.
    Lv, J.X., Tang, R.Z., Jia, S.: Research on energy consumption modeling of CNC machine tool for non-cutting operations, no. 51175464 (2012)Google Scholar
  18. 18.
    Deb, K., Pratap, A., Agarwal, S., Meyarivan, T.: A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II 6(2), 182–197 (2002)Google Scholar

Copyright information

© IFIP International Federation for Information Processing 2013

Authors and Affiliations

  1. 1.Department of Mechanical, Material and Manufacturing EngineeringUniversity of NottinghamNottinghamUnited Kingdom
  2. 2.Department of Computer ScienceUniversity of NottinghamNottinghamUnited Kingdom
  3. 3.Division of EngineeringUniversity of Nottingham Ningbo ChinaNingboChina

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