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Methodology – A Review of Intelligent Manufacturing: Scope, Strategy and Simulation

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Recent Advances in Intelligent Manufacturing (ICSEE 2018, IMIOT 2018)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 923))

Abstract

This paper presents a critical review of some existing modelling, control and optimization techniques for energy saving, carbon emission reduction in manufacturing processes. The study on various production issues reveals different levels of intelligent manufacturing approaches. Then methods and strategies to tackle the sustainability issues in manufacturing are summarized. Modelling tools such as discrete (dynamic) event system (DES/DEDS) and agent-based modelling/simulation (ABS) approaches are reviewed from the production planning and control prospective. These approaches will provide some guidelines for the development of advanced factory modelling, resource flow analysis and assisting the identification of improvement potentials, in order to achieve more sustainable manufacturing.

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References

  1. Mařík, V., Schirrmann, A., Trentesaux, D., Vrba, P. (eds.): HoloMAS 2015. LNCS (LNAI), vol. 9266. Springer, Cham (2015). https://doi.org/10.1007/978-3-319-22867-9

    Book  Google Scholar 

  2. Trentesaux, D., Prabhu, V.: Sustainability in manufacturing operations scheduling: stakes, approaches and trends. In: Grabot, B., Vallespir, B., Gomes, S., Bouras, A., Kiritsis, D. (eds.) APMS 2014. IAICT, vol. 439, pp. 106–113. Springer, Heidelberg (2014). https://doi.org/10.1007/978-3-662-44736-9_13

    Chapter  Google Scholar 

  3. Duflou, J.R., et al.: Towards energy and resource efficient manufacturing: a processes and systems approach. CIRP Ann. 61, 587–609 (2012)

    Article  Google Scholar 

  4. Roghanian, P., Rasli, A., Gheysari, H.: Productivity through effectiveness and efficiency in the banking industry. Procedia Soc. Behav. Sci. 40, 550–556 (2012)

    Article  Google Scholar 

  5. Brandimarte, P., Villa, A.: Modeling Manufacturing Systems: From Aggregate Planning to Real-Time Control. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-662-03853-6

    Book  Google Scholar 

  6. Abele, E., Anderl, R., Birkhofer, H.: Environmentally-Friendly Product Development. Springer, London (2005). https://doi.org/10.1007/b138604

    Book  Google Scholar 

  7. Kellens, K., Dewulf, W., Overcash, M., Hauschild, M.Z., Duflou, J.R.: Methodology for systematic analysis and improvement of manufacturing unit process life-cycle inventory (UPLCI)—CO2PE! initiative (cooperative effort on process emissions in manufacturing). Part 1: Methodology description. Int. J. Life Cycle Assess. 17, 69–78 (2012)

    Article  Google Scholar 

  8. Zein, A.: Transition Towards Energy Efficient Machine Tools. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-32247-1

    Book  Google Scholar 

  9. Duflou, J.R., Kellens, K., Dewulf, W.: Environmental performance of sheet metal working processes. In: Key Engineering Materials, pp. 21–26. Trans Tech Publ. (2011)

    Google Scholar 

  10. Dotchev, K., Yusoff, W.: Recycling of polyamide 12 based powders in the laser sintering process. Rapid Prototyp. J. 15, 192–203 (2009)

    Article  Google Scholar 

  11. Diaz, N., Helu, M., Jarvis, A., Tonissen, S., Dornfeld, D., Schlosser, R.: Strategies for minimum energy operation for precision machining (2009)

    Google Scholar 

  12. Saidur, R., Rahim, N.A., Hasanuzzaman, M.: A review on compressed-air energy use and energy savings. Renew. Sustain. Energy Rev. 14, 1135–1153 (2010)

    Article  Google Scholar 

  13. Bittencourt, J.L., Bonefeld, R., Scholze, S., Stokic, D., Uddin, M.K., Lastra, J.L.M.: Energy efficiency improvement through context sensitive self-learning of machine availability. In: 2011 9th IEEE International Conference on Industrial Informatics, pp. 93–98 (2011)

    Google Scholar 

  14. Mori, M., Fujishima, M., Inamasu, Y., Oda, Y.: A study on energy efficiency improvement for machine tools. CIRP Ann. 60, 145–148 (2011)

    Article  Google Scholar 

  15. Li, Y., Liu, H., Li, J., Tao, J.: Process parameters optimization for energy saving in paper machine dryer section. Dry. Technol. 29, 910–917 (2011)

    Article  Google Scholar 

  16. Afshar, P., Brown, M., Maciejowski, J., Wang, H.: Data-based robust multiobjective optimization of interconnected processes: energy efficiency case study in papermaking. IEEE Trans. Neural Netw. 22, 2324–2338 (2011)

    Article  Google Scholar 

  17. Zhang, L., Wu, L., Zhang, X., Ju, G.: Comparison and optimization of mid-low temperature cogeneration systems for flue gas in iron and steel plants. J. Iron. Steel Res. Int. 20, 33–40 (2013)

    Article  Google Scholar 

  18. Bejan, A.: Fundamentals of exergy analysis, entropy generation minimization, and the generation of flow architecture. Int. J. Energy Res. 26, 1–43 (2002)

    Google Scholar 

  19. Wang, Z., Zheng, D., Jin, H.: Energy integration of acetylene and power polygeneration by flowrate-exergy diagram. Appl. Energy 86, 372–379 (2009)

    Article  Google Scholar 

  20. Thekdi, A., Nimbalkar, S.U.: Industrial Waste Heat Recovery - Potential Applications, Available Technologies and Crosscutting R&D Opportunities. Oak Ridge National Laboratory (ORNL), Oak Ridge, TN, USA (2015)

    Google Scholar 

  21. Karellas, S., Leontaritis, A.-D., Panousis, G., Bellos, E., Kakaras, E.: Energetic and exergetic analysis of waste heat recovery systems in the cement industry. Energy 58, 147–156 (2013)

    Article  Google Scholar 

  22. Logožar, K., Radonjič, G., Bastič, M.: Incorporation of reverse logistics model into in-plant recycling process: a case of aluminium industry. Resour. Conserv. Recycl. 49, 49–67 (2006)

    Article  Google Scholar 

  23. Herrmann, C., Thiede, S.: Process chain simulation to foster energy efficiency in manufacturing. CIRP J. Manuf. Sci. Technol. 1, 221–229 (2009)

    Article  Google Scholar 

  24. Jia, Z., Zhang, L., Arinez, J., Xiao, G.: Performance analysis for serial production lines with Bernoulli Machines and Real-time WIP-based Machine switch-on/off control. Int. J. Prod. Res. 54, 6285–6301 (2016)

    Article  Google Scholar 

  25. Herrmann, C., Thiede, S., Kara, S., Hesselbach, J.: Energy oriented simulation of manufacturing systems – concept and application. CIRP Ann. 60, 45–48 (2011)

    Article  Google Scholar 

  26. Reich-Weiser, C., Vijayaraghavan, A., Dornfeld, D.: Appropriate use of green manufacturing frameworks (2010)

    Google Scholar 

  27. Diaz, N., Helu, M., Jayanathan, S., Chen, Y., Horvath, A., Dornfeld, D.: Environmental analysis of milling machine tool use in various manufacturing environments. In: Proceedings of the 2010 IEEE International Symposium on Sustainable Systems and Technology, pp. 1–6 (2010)

    Google Scholar 

  28. Grau, R., Espuña, A., Puigjaner, L.: Environmental considerations in batch production scheduling (1995)

    Google Scholar 

  29. Giret, A., Trentesaux, D., Prabhu, V.: Sustainability in manufacturing operations scheduling: a state of the art review. J. Manuf. Syst. 37, 126–140 (2015)

    Article  Google Scholar 

  30. Zheng, H., Wang, L.: Reduction of carbon emissions and project makespan by a Pareto-based estimation of distribution algorithm. Int. J. Prod. Econ. 164, 421–432 (2015)

    Article  Google Scholar 

  31. Mouzon, G., Yildirim, M.B.: A framework to minimise total energy consumption and total tardiness on a single machine. Int. J. Sustain. Eng. 1, 105–116 (2008)

    Article  Google Scholar 

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

    Article  Google Scholar 

  33. Liu, C., Yang, J., Lian, J., Li, W., Evans, S., Yin, Y.: Sustainable performance oriented operational decision-making of single machine systems with deterministic product arrival time. J. Clean. Prod. 85, 318–330 (2014)

    Article  Google Scholar 

  34. Yildirim, M.B., Mouzon, G.: Single-machine sustainable production planning to minimize total energy consumption and total completion time using a multiple objective genetic algorithm. IEEE Trans. Eng. Manag. 59, 585–597 (2012)

    Article  Google Scholar 

  35. Escamilla, J., Salido, M.A., Giret, A., Barber, F.: A metaheuristic technique for energy-efficiency in job-shop scheduling. Knowl. Eng. Rev. 31, 475–485 (2016)

    Article  Google Scholar 

  36. Li, X., Li, W., Cai, X., He, F.: A honey-bee mating optimization approach of collaborative process planning and scheduling for sustainable manufacturing. In: Proceedings of the 2013 IEEE 17th International Conference on Computer Supported Cooperative Work in Design (CSCWD), pp. 465–470 (2013)

    Google Scholar 

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

    Article  Google Scholar 

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

    Article  Google Scholar 

  39. Vergnano, A., et al.: Embedding detailed robot energy optimization into high-level scheduling. In: 2010 IEEE International Conference on Automation Science and Engineering, pp. 386–392 (2010)

    Google Scholar 

  40. Adonyi, R., Biros, G., Holczinger, T., Friedler, F.: Effective scheduling of a large-scale paint production system. J. Clean. Prod. 16, 225–232 (2008)

    Article  Google Scholar 

  41. Wang, X., Ding, H., Qiu, M., Dong, J.: A low-carbon production scheduling system considering renewable energy. In: Proceedings of 2011 IEEE International Conference on Service Operations, Logistics and Informatics, pp. 101–106 (2011)

    Google Scholar 

  42. Liu, C.-H.: Approximate trade-off between minimisation of total weighted tardiness and minimisation of carbon dioxide (CO2) emissions in bi-criteria batch scheduling problem. Int. J. Comput. Integr. Manuf. 27, 759–771 (2014)

    Article  Google Scholar 

  43. Seleim, Azab, A., AlGeddawy, T.: Simulation methods for changeable manufacturing. Procedia CIRP 3, 179–184 (2012)

    Google Scholar 

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

    Article  Google Scholar 

  45. Robinson, S.: Simulation: The Practice of Model Development and Use. Wiley, Chichester, Hoboken (2004)

    Google Scholar 

  46. Costa, B., Dias, L.S., Oliveira, J.A., Pereira, G.: Simulation as a tool for planning a material delivery system to manufacturing lines. In: 2008 IEEE International Engineering Management Conference, pp. 1–5 (2008)

    Google Scholar 

  47. Lee, S., et al.: Steel-yard planning support system: Optimizing the steel-yard planning and performance evaluation with simulation. In: 2012 12th International Conference on Control, Automation and Systems, pp. 605–609 (2012)

    Google Scholar 

  48. Gebus, S., Soulas, A., Juuso, E.: Short term scheduling in electronics manufacturing using discrete-event simulation. Proc. SIMS–Scand. Simul. Soc. 2013, 1–7 (2013)

    Google Scholar 

  49. Franke, C., Basdere, B., Ciupek, M., Seliger, S.: Remanufacturing of mobile phones—capacity, program and facility adaptation planning. Omega 34, 562–570 (2006)

    Article  Google Scholar 

  50. Gregg, M.L., Van Andel, S.M., Saylor, S.E.: Lean+ manufacturing process analysis simulation (LPAS+). In: Proceedings of the Winter Simulation Conference. Winter Simulation Conference, Phoenix, Arizona, pp. 2171–2180 (2011)

    Google Scholar 

  51. Van Dyke Parunak, H., Savit, R., Riolo, Rick L.: Agent-Based Modeling vs. Equation-Based Modeling: A Case Study and Users’ Guide. In: Sichman, J.S., Conte, R., Gilbert, N. (eds.) MABS 1998. LNCS (LNAI), vol. 1534, pp. 10–25. Springer, Heidelberg (1998). https://doi.org/10.1007/10692956_2

    Chapter  Google Scholar 

  52. Jeon, S.M., Kim, G.: A survey of simulation modeling techniques in production planning and control (PPC). Prod. Plan. Control. 27, 360–377 (2016)

    Article  Google Scholar 

  53. Monostori, L., Váncza, J., Kumara, S.R.T.: Agent-based systems for manufacturing. CIRP Ann. 55, 697–720 (2006)

    Article  Google Scholar 

  54. Yeung, W.L.: Behavioral modeling and verification of multi-agent systems for manufacturing control. Expert Syst. Appl. 38, 13555–13562 (2011)

    Article  Google Scholar 

  55. Li, D., Wang, Y., Xiao, G., Tang, J.: Dynamic parts scheduling in multiple job shop cells considering intercell moves and flexible routes. Comput. Oper. Res. 40, 1207–1223 (2013)

    Article  MathSciNet  Google Scholar 

  56. Kim, T., Choi, B.K.: Production system-based simulation for backward on-line job change scheduling. Simul. Model. Pract. Theory 40, 12–27 (2014)

    Article  Google Scholar 

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Authors and Affiliations

  1. School of Electronic and Electrical Engineering, University of Leeds, Leeds, LS2 9JT, UK

    Peiliang Sun & Kang Li

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  1. Peiliang Sun
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  2. Kang Li
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Correspondence to Peiliang Sun .

Editor information

Editors and Affiliations

  1. Chongqing University, Chongqing, China

    Shilong Wang

  2. Queen’s University Belfast, Belfast, UK

    Mark Price

  3. Chongqing University, Chongqing, China

    Ming K. Lim

  4. Queen’s University Belfast, Belfast, UK

    Yan Jin

  5. Chongqing University, Chongqing, China

    Yuanxin Luo

  6. Chongqing University, Chongqing, China

    Rui Chen

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Sun, P., Li, K. (2018). Methodology – A Review of Intelligent Manufacturing: Scope, Strategy and Simulation. In: Wang, S., Price, M., Lim, M., Jin, Y., Luo, Y., Chen, R. (eds) Recent Advances in Intelligent Manufacturing . ICSEE IMIOT 2018 2018. Communications in Computer and Information Science, vol 923. Springer, Singapore. https://doi.org/10.1007/978-981-13-2396-6_33

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  • DOI: https://doi.org/10.1007/978-981-13-2396-6_33

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  • Publisher Name: Springer, Singapore

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  • Online ISBN: 978-981-13-2396-6

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