IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i16p3179-d258951.html
   My bibliography  Save this article

Economic Analysis of an Integrated Production–Inventory System under Stochastic Production Capacity and Energy Consumption

Author

Listed:
  • Iqra Asghar

    (Department of Industrial and Management Engineering, Hanyang University, Ansan Gyeonggi-do 15588, Korea
    These authors contributed equally to this work.)

  • Biswajit Sarkar

    (Department of Industrial and Management Engineering, Hanyang University, Ansan Gyeonggi-do 15588, Korea
    These authors contributed equally to this work.)

  • Sung-jun Kim

    (Department of Industrial and Management Engineering, Hanyang University, Ansan Gyeonggi-do 15588, Korea)

Abstract

Expensive power cost is a significant concern in today’s manufacturing world. Reduction in energy consumption is an ultimate measure towards achieving manufacturing efficiency and emissions control. In the existing literature of scheduling problems, the consumption of energy is considered uncertain under the dimensions of uncertain demand and supply. In reality, it is a random parameter that also depends on production capacity, manufacturing technology, and operational condition of the manufacturing system. As the unit production cost varies with production rate and reliability of the manufacturing system, the energy consumption of the system also varies accordingly. Therefore, this study investigated an unreliable manufacturing system under stochastic production capacities and energy consumption. A stochastic production–inventory policy is developed to optimize production quantity, production rate, and manufacturing reliability under variable energy consumption costs. As energy consumption varies in different operational states of manufacturing, we consider three specific states of power consumption, namely working, idle, and repair time, for an integrated production–maintenance model. The considered production system is subjected to stochastic failure and repair time, where productivity and manufacturing reliability is improved through additional technology investment. The robustness of the model is shown through numerical example, comparative study, and sensitivity analysis of model parameters. Several graphical illustrations are also provided to obtain meaningful managerial insights.

Suggested Citation

  • Iqra Asghar & Biswajit Sarkar & Sung-jun Kim, 2019. "Economic Analysis of an Integrated Production–Inventory System under Stochastic Production Capacity and Energy Consumption," Energies, MDPI, vol. 12(16), pages 1-27, August.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3179-:d:258951
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/16/3179/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/16/3179/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Mitali Sarkar & Biswajit Sarkar & Muhammad Waqas Iqbal, 2018. "Effect of Energy and Failure Rate in a Multi-Item Smart Production System," Energies, MDPI, vol. 11(11), pages 1-21, October.
    2. Ozgul Calicioglu & Alessandro Flammini & Stefania Bracco & Lorenzo Bellù & Ralph Sims, 2019. "The Future Challenges of Food and Agriculture: An Integrated Analysis of Trends and Solutions," Sustainability, MDPI, vol. 11(1), pages 1-21, January.
    3. Glock, C. H., 2010. "Batch sizing with controllable production rates," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 57823, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    4. Bazan, Ehab & Jaber, Mohamad Y. & Zanoni, Simone, 2017. "Carbon emissions and energy effects on a two-level manufacturer-retailer closed-loop supply chain model with remanufacturing subject to different coordination mechanisms," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 394-408.
    5. Biswajit Sarkar & Shib Sankar Sana & Kripasindhu Chaudhuri, 2010. "Optimal reliability, production lot size and safety stock in an imperfect production system," International Journal of Mathematics in Operational Research, Inderscience Enterprises Ltd, vol. 2(4), pages 467-490.
    6. Liu, Ying & Dong, Haibo & Lohse, Niels & Petrovic, Sanja, 2016. "A multi-objective genetic algorithm for optimisation of energy consumption and shop floor production performance," International Journal of Production Economics, Elsevier, vol. 179(C), pages 259-272.
    7. Marchi, B. & Zanoni, S. & Zavanella, L.E. & Jaber, M.Y., 2019. "Supply chain models with greenhouse gases emissions, energy usage, imperfect process under different coordination decisions," International Journal of Production Economics, Elsevier, vol. 211(C), pages 145-153.
    8. Sarkar, Biswajit & Guchhait, Rekha & Sarkar, Mitali & Cárdenas-Barrón, Leopoldo Eduardo, 2019. "How does an industry manage the optimum cash flow within a smart production system with the carbon footprint and carbon emission under logistics framework?," International Journal of Production Economics, Elsevier, vol. 213(C), pages 243-257.
    9. Dellino, Gabriella & Kleijnen, Jack P.C. & Meloni, Carlo, 2010. "Robust optimization in simulation: Taguchi and Response Surface Methodology," International Journal of Production Economics, Elsevier, vol. 125(1), pages 52-59, May.
    10. Seokgi Lee & Vittaldas V. Prabhu, 2015. "Energy-aware feedback control for production scheduling and capacity control," International Journal of Production Research, Taylor & Francis Journals, vol. 53(23), pages 7158-7170, December.
    11. Eva González-Romera & Mercedes Ruiz-Cortés & María-Isabel Milanés-Montero & Fermín Barrero-González & Enrique Romero-Cadaval & Rui Amaral Lopes & João Martins, 2019. "Advantages of Minimizing Energy Exchange Instead of Energy Cost in Prosumer Microgrids," Energies, MDPI, vol. 12(4), pages 1-18, February.
    12. Dionysios Pramangioulis & Konstantinos Atsonios & Nikos Nikolopoulos & Dimitrios Rakopoulos & Panagiotis Grammelis & Emmanuel Kakaras, 2019. "A Methodology for Determination and Definition of Key Performance Indicators for Smart Grids Development in Island Energy Systems," Energies, MDPI, vol. 12(2), pages 1-22, January.
    13. Biel, K. & Glock, C. H., 2016. "Systematic literature review of decision support models for energy-efficient production planning," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 83071, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    14. Rapine, Christophe & Penz, Bernard & Gicquel, Céline & Akbalik, Ayse, 2018. "Capacity acquisition for the single-item lot sizing problem under energy constraints," Omega, Elsevier, vol. 81(C), pages 112-122.
    15. Glock, C. H., 2011. "Batch sizing with controllable production rates in a multi-stage production system," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 57822, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Suchitra Pattnaik & Mitali Madhusmita Nayak & Stefano Abbate & Piera Centobelli, 2021. "Recent Trends in Sustainable Inventory Models: A Literature Review," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    2. Jia-Liang Pan & Chui-Yu Chiu & Kun-Shan Wu & Chih-Te Yang & Yen-Wen Wang, 2021. "Optimal Pricing, Advertising, Production, Inventory and Investing Policies in a Multi-Stage Sustainable Supply Chain," Energies, MDPI, vol. 14(22), pages 1-20, November.
    3. Asif Iqbal Malik & Byung Soo Kim, 2020. "A Constrained Production System Involving Production Flexibility and Carbon Emissions," Mathematics, MDPI, vol. 8(2), pages 1-21, February.
    4. Xue Lin & Lixia Sun & Ping Ju & Hongyu Li, 2019. "Stochastic Control for Intra-Region Probability Maximization of Multi-Machine Power Systems Based on the Quasi-Generalized Hamiltonian Theory," Energies, MDPI, vol. 13(1), pages 1-16, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Asif Iqbal Malik & Byung Soo Kim, 2020. "A Constrained Production System Involving Production Flexibility and Carbon Emissions," Mathematics, MDPI, vol. 8(2), pages 1-21, February.
    2. Hajo Terbrack & Thorsten Claus & Frank Herrmann, 2021. "Energy-Oriented Production Planning in Industry: A Systematic Literature Review and Classification Scheme," Sustainability, MDPI, vol. 13(23), pages 1-32, December.
    3. Wakhid Ahmad Jauhari & I Nyoman Pujawan & Mokh Suef, 2023. "Sustainable inventory management with hybrid production system and investment to reduce defects," Annals of Operations Research, Springer, vol. 324(1), pages 543-572, May.
    4. Xia, Jing & Niu, Wenju, 2021. "Carbon-reducing contract design for a supply chain with environmental responsibility under asymmetric information," Omega, Elsevier, vol. 102(C).
    5. Lucio Enrico Zavanella & Beatrice Marchi & Simone Zanoni & Ivan Ferretti, 2019. "Energy considerations for the economic production quantity and the joint economic lot sizing," Journal of Business Economics, Springer, vol. 89(7), pages 845-865, September.
    6. Suzanne, Elodie & Absi, Nabil & Borodin, Valeria, 2020. "Towards circular economy in production planning: Challenges and opportunities," European Journal of Operational Research, Elsevier, vol. 287(1), pages 168-190.
    7. Golpîra, Hêriş, 2020. "Smart Energy-Aware Manufacturing Plant Scheduling under Uncertainty: A Risk-Based Multi-Objective Robust Optimization Approach," Energy, Elsevier, vol. 209(C).
    8. Wichmann, Matthias Gerhard & Johannes, Christoph & Spengler, Thomas Stefan, 2019. "Energy-oriented Lot-Sizing and Scheduling considering energy storages," International Journal of Production Economics, Elsevier, vol. 216(C), pages 204-214.
    9. Mitali Sarkar & Li Pan & Bikash Koli Dey & Biswajit Sarkar, 2020. "Does the Autonomation Policy Really Help in a Smart Production System for Controlling Defective Production?," Mathematics, MDPI, vol. 8(7), pages 1-21, July.
    10. AlDurgam, Mohammad & Adegbola, Kehinde & Glock, Christoph H., 2017. "A single-vendor single-manufacturer integrated inventory model with stochastic demand and variable production rate," International Journal of Production Economics, Elsevier, vol. 191(C), pages 335-350.
    11. Dhahri, Akrem & Gharbi, Ali & Ouhimmou, Mustapha, 2022. "Integrated production-delivery control policy for an unreliable manufacturing system and multiple retailers," International Journal of Production Economics, Elsevier, vol. 245(C).
    12. Mitali Sarkar & Byung Do Chung, 2021. "Effect of Renewable Energy to Reduce Carbon Emissions under a Flexible Production System: A Step Toward Sustainability," Energies, MDPI, vol. 14(1), pages 1-14, January.
    13. Asif Iqbal Malik & Biswajit Sarkar, 2020. "Coordination Supply Chain Management Under Flexible Manufacturing, Stochastic Leadtime Demand, and Mixture of Inventory," Mathematics, MDPI, vol. 8(6), pages 1-32, June.
    14. Zanoni, Simone & Bettoni, Laura & Glock, Christoph H., 2014. "Energy implications in a two-stage production system with controllable production rates," International Journal of Production Economics, Elsevier, vol. 149(C), pages 164-171.
    15. Suchitra Pattnaik & Mitali Madhusmita Nayak & Stefano Abbate & Piera Centobelli, 2021. "Recent Trends in Sustainable Inventory Models: A Literature Review," Sustainability, MDPI, vol. 13(21), pages 1-20, October.
    16. Zhou, Xiaoyang & Wei, Xiaoya & Lin, Jun & Tian, Xin & Lev, Benjamin & Wang, Shouyang, 2021. "Supply chain management under carbon taxes: A review and bibliometric analysis," Omega, Elsevier, vol. 98(C).
    17. Beatrice Marchi & Simone Zanoni & Ivan Ferretti & Lucio E. Zavanella, 2018. "Stimulating Investments in Energy Efficiency Through Supply Chain Integration," Energies, MDPI, vol. 11(4), pages 1-13, April.
    18. Beatrice Marchi & Simone Zanoni, 2017. "Supply Chain Management for Improved Energy Efficiency: Review and Opportunities," Energies, MDPI, vol. 10(10), pages 1-29, October.
    19. Glock, Christoph H., 2012. "Lead time reduction strategies in a single-vendor–single-buyer integrated inventory model with lot size-dependent lead times and stochastic demand," International Journal of Production Economics, Elsevier, vol. 136(1), pages 37-44.
    20. Mitali Sarkar & Biswajit Sarkar, 2019. "Optimization of Safety Stock under Controllable Production Rate and Energy Consumption in an Automated Smart Production Management," Energies, MDPI, vol. 12(11), pages 1-16, May.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:12:y:2019:i:16:p:3179-:d:258951. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.