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An industrial facility layout design method considering energy saving based on surplus rectangle fill algorithm

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  • Wang, Ruiqi
  • Zhao, Huan
  • Wu, Yan
  • Wang, Yufei
  • Feng, Xiao
  • Liu, Mengxi

Abstract

The facility layout design within a plant is a key step in the process of chemical engineering design. A good layout can save capital cost, energy and natural resource. The aim of this work is to determine the relative location of facilities in a large-scale industrial plant considering multi-floor structure to make the total cost minimum. The objective function consists of piping investment cost, pump power cost, land cost, and floor construction cost. Surplus rectangle fill algorithm is applied in this work, and it is combined with a genetic algorithm to obtain the optimal solution. Constraints of pump area, joint arrangement of heat exchangers, and the cross-floor facilities are also taken into consideration. In the case study, a plant from a real refinery including 217 facilities is designed with different floor number. The comparison of the three different conditions proves the important role of floor number in the trade-off among investment cost, energy consumption, and land resource. The case illustrates that, the proposed method can generate a reasonable layout design for the industrial facilities and save capital and operating cost effectively. A sensitivity analysis is also done to explore the influence of basic data on the optimal construction structure.

Suggested Citation

  • Wang, Ruiqi & Zhao, Huan & Wu, Yan & Wang, Yufei & Feng, Xiao & Liu, Mengxi, 2018. "An industrial facility layout design method considering energy saving based on surplus rectangle fill algorithm," Energy, Elsevier, vol. 158(C), pages 1038-1051.
    • Handle: RePEc:eee:energy:v:158:y:2018:i:c:p:1038-1051
    DOI: 10.1016/j.energy.2018.06.105
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    References listed on IDEAS

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    1. Ali Derakhshan Asl & Kuan Yew Wong, 2017. "Solving unequal-area static and dynamic facility layout problems using modified particle swarm optimization," Journal of Intelligent Manufacturing, Springer, vol. 28(6), pages 1317-1336, August.
    2. Faina, Loris, 1999. "An application of simulated annealing to the cutting stock problem," European Journal of Operational Research, Elsevier, vol. 114(3), pages 542-556, May.
    3. Stijepovic, Mirko Z. & Linke, Patrick, 2011. "Optimal waste heat recovery and reuse in industrial zones," Energy, Elsevier, vol. 36(7), pages 4019-4031.
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    Cited by:

    1. Siyu Xu & Yufei Wang & Xiao Feng, 2020. "Plant Layout Optimization for Chemical Industry Considering Inner Frame Structure Design," Sustainability, MDPI, vol. 12(6), pages 1-19, March.
    2. Xuemin Liu & Guozhong Huang & Shengnan Ou & Xingyu Xiao & Xuehong Gao & Zhangzhou Meng & Youqiang Pan & Ibrahim M. Hezam, 2023. "Biobjective Optimization Model Considering Risk and Profit for the Multienterprise Layout Design in Village-Level Industrial Parks in China," Sustainability, MDPI, vol. 15(4), pages 1-27, February.
    3. O’Neill, Sam & Wrigley, Paul & Bagdasar, Ovidiu, 2022. "A mixed-integer linear programming formulation for the modular layout of three-dimensional connected systems," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 201(C), pages 739-754.
    4. Zhongwei Zhang & Lihui Wu & Zhaoyun Wu & Wenqiang Zhang & Shun Jia & Tao Peng, 2022. "Energy-Saving Oriented Manufacturing Workshop Facility Layout: A Solution Approach Using Multi-Objective Particle Swarm Optimization," Sustainability, MDPI, vol. 14(5), pages 1-28, February.
    5. Kuldeep Lamba & Ravi Kumar & Shraddha Mishra & Shubhangini Rajput, 2020. "Sustainable dynamic cellular facility layout: a solution approach using simulated annealing-based meta-heuristic," Annals of Operations Research, Springer, vol. 290(1), pages 5-26, July.

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