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Modelling and simulation of energy consumption of ceramic production chains with mixed flows using hybrid Petri nets

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  • Hongcheng Li
  • Haidong Yang
  • Bixia Yang
  • Chengjiu Zhu
  • Sihua Yin

Abstract

Ceramic production chain consisting of discrete flow and continuous flow energy-intensive processes consumes substantial amounts of energy. This study aims to evaluate energy consumption performance and energy-saving potentials of the ceramic production chain. According to the energy consumption characteristics of manufacturing processes and process interaction constraints in a ceramic production chain, an approach integrating the first-order hybrid Petri net (FOHPN) model, an objective linear programming model and a sensitivity analysis is proposed. The FOHPN model will simulate the energy consumption patterns of the ceramic production chain. Meanwhile, multi-objective linear programming model and sensitivity analysis will suggest the optimal specific energy consumption (SEC) of the production chain and identify the influences of input parameters (i.e. production rate of a process) on the SEC in the optimal production scheme. Finally, a real case study from bathroom ceramic plant validates the approach. It provides a tool for modelling and simulation of energy consumption of ceramic production chains with mixed flows and helps operators to perform energy-saving actions in the ceramic enterprise.

Suggested Citation

  • Hongcheng Li & Haidong Yang & Bixia Yang & Chengjiu Zhu & Sihua Yin, 2018. "Modelling and simulation of energy consumption of ceramic production chains with mixed flows using hybrid Petri nets," International Journal of Production Research, Taylor & Francis Journals, vol. 56(8), pages 3007-3024, April.
    • Handle: RePEc:taf:tprsxx:v:56:y:2018:i:8:p:3007-3024
    DOI: 10.1080/00207543.2017.1391415
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    Cited by:

    1. Miguel Castro Oliveira & Muriel Iten & Pedro L. Cruz & Helena Monteiro, 2020. "Review on Energy Efficiency Progresses, Technologies and Strategies in the Ceramic Sector Focusing on Waste Heat Recovery," Energies, MDPI, vol. 13(22), pages 1-24, November.
    2. Ma, Shuaiyin & Ding, Wei & Liu, Yang & Ren, Shan & Yang, Haidong, 2022. "Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries," Applied Energy, Elsevier, vol. 326(C).
    3. Li, Hongcheng & Yang, Dan & Cao, Huajun & Ge, Weiwei & Chen, Erheng & Wen, Xuanhao & Li, Chongbo, 2022. "Data-driven hybrid petri-net based energy consumption behaviour modelling for digital twin of energy-efficient manufacturing system," Energy, Elsevier, vol. 239(PC).
    4. El-Kadi Hellel & Samir Hamaci & Rezki Ziani, 2019. "Performance-related dependability evaluation of multi-source renewable energy systems using deterministic and stochastic Petri nets," Energy & Environment, , vol. 30(5), pages 800-820, August.
    5. Ma, Shuaiyin & Zhang, Yingfeng & Lv, Jingxiang & Ge, Yuntian & Yang, Haidong & Li, Lin, 2020. "Big data driven predictive production planning for energy-intensive manufacturing industries," Energy, Elsevier, vol. 211(C).

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