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Technological Updating Decision–Making Model for Eco–Factory Through Dynamic Programming

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Advances in Green Energy Systems and Smart Grid (ICSEE 2018, IMIOT 2018)

Abstract

As the key subject of the green manufacturing system, the construction of eco–factory has become an important content in order to achieve the sustainable development of enterprises. In this paper, a technological updating decision-making model is established based on dynamic programming (DP) for eco–factory. Firstly, the evaluation index system for eco–factory is established. Secondly, the local weight and global weight of each index are calculated based on analytic network process (ANP) and Delphi method. Finally, the decision–making model of eco-factory is established to find the optimal investment plan by using the method of logarithmic fitting and DP. The ANP and Delphi method present a great potential in solving complex and ambiguous problems and the decision-making based on DP can obtain the better ecological benefits through an example of a foundry factory, therefore the feasibility of the proposed method is proved.

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References

  1. Ahn, S.H.: An evaluation of green manufacturing technologies based on research databases. Int. J. Precis. Eng. Manuf.-Green Technol. 1(1), 5–9 (2014)

    Article  MathSciNet  Google Scholar 

  2. Kai, S., Leino, T., Joutsiniemi, A.: Sustainable manufacturing and eco-factories within sustainable industrial areas within fast growing eco-cities sustainable manufacturing and eco-factories within sustainable industrial areas within fast growing eco-cities. In: Flexible Automation and Intelligent Manufacturing, FAIM (2011)

    Google Scholar 

  3. Fantini, P., Palasciano, C., Taisch, M.: Back to intuition: proposal for a performance indicators framework to facilitate eco-factories management and benchmarking. Procedia CIRP 26, 1–6 (2015)

    Article  Google Scholar 

  4. Taisch, M., Stahl, B.: Requirements analysis and definition for eco-factories: the case of EMC2. In: Emmanouilidis, C., Taisch, M., Kiritsis, D. (eds.) APMS 2012. IAICT, vol. 397, pp. 111–118. Springer, Heidelberg (2013). https://doi.org/10.1007/978-3-642-40352-1_15

    Chapter  Google Scholar 

  5. Leong, Y.T., Lee, J.Y., Tan, R.R., et al.: Multi-objective optimization for resource network synthesis in eco-industrial parks using an integrated analytic hierarchy process. J. Clean. Prod. 143, 1268–1283 (2017)

    Article  Google Scholar 

  6. May, G., Stahl, B., Taisch, M.: Energy management in manufacturing: toward eco-factories of the future–a focus group study. Appl. Energy 164, 628–638 (2016)

    Article  Google Scholar 

  7. Reinhard, J., Zah, R., Wohlgemuth, V., et al.: Applying life cycle assessment within discrete event simulation: practical application of the Milan/EcoFactory material flow simulator (2013)

    Google Scholar 

  8. Wen, J.H., Jiang, H.L., Zhang, M., et al.: Application of dynamic programming in resources optimization allocation of factory production line. Key Eng. Mater. 474–476(1), 1632–1637 (2011)

    Article  Google Scholar 

  9. Jia, J., Yang, Y., Yang, T., et al.: Research on dynamic programming of the series manufacturing system reliability allocation. J. Converg. Inf. Technol. 7(7), 17–25 (2012)

    Google Scholar 

  10. Abdul-Zahra, In, Abbas, I.T., Kalaf, B.A., et al.: The role of dynamic programming in the distribution of investment allocations between production lines with an application in the (men’s clothing factory in Najaf holy). Int. J. Pure Appl. Math. 106(2), 365–380 (2016)

    Article  Google Scholar 

  11. Kabak, M., Dağdeviren, M.: A hybrid approach based on ANP and grey relational analysis for machine selection. Tehnicki Vjesnik 24, 109–118 (2017)

    Google Scholar 

  12. Ayağ, Z., Özdemir, R.G.: Evaluating machine tool alternatives through modified TOPSIS and alpha-cut based fuzzy ANP. Int. J. Prod. Econ. 140(2), 630–636 (2012)

    Article  Google Scholar 

  13. Saaty, T.L., Vargas, L.G.: Decision Making with the Analytic Network Process. Springer, Berlin (2013). https://doi.org/10.1007/978-1-4614-7279-7

    Book  Google Scholar 

  14. Li, H., Tao, M., Sun, Z.: Research on the process evaluation of green university based on concordance analysis. In: International Conference on Chinese Control and Decision Conference, pp. 3642–3646. IEEE Press (2009)

    Google Scholar 

  15. Ullah, S.M.S., Muhammad, I., Ko, T.J.: Optimal strategy to deal with decision making problems in machine tools remanufacturing. Int. J. Precis. Eng. Manuf.-Green Technol. 3(1), 19–26 (2016)

    Article  Google Scholar 

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Correspondence to Huajun Cao .

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Chen, E., Cao, H., Wang, K., Jafar, S., He, Q. (2018). Technological Updating Decision–Making Model for Eco–Factory Through Dynamic Programming. In: Li, K., Zhang, J., Chen, M., Yang, Z., Niu, Q. (eds) Advances in Green Energy Systems and Smart Grid. ICSEE IMIOT 2018 2018. Communications in Computer and Information Science, vol 925. Springer, Singapore. https://doi.org/10.1007/978-981-13-2381-2_12

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  • DOI: https://doi.org/10.1007/978-981-13-2381-2_12

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-2380-5

  • Online ISBN: 978-981-13-2381-2

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