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Sustainability Economic Production Quantity with Warm-Up Function for a Defective Production System

Author

Listed:
  • Erfan Nobil

    (Tecnologico de Monterrey, School of Engineering and Sciences, E. Garza Sada 2501 Sur, Monterrey 64849, Mexico)

  • Leopoldo Eduardo Cárdenas-Barrón

    (Tecnologico de Monterrey, School of Engineering and Sciences, E. Garza Sada 2501 Sur, Monterrey 64849, Mexico)

  • Imelda de Jesús Loera-Hernández

    (Tecnologico de Monterrey, School of Engineering and Sciences, E. Garza Sada 2501 Sur, Monterrey 64849, Mexico)

  • Neale R. Smith

    (Tecnologico de Monterrey, School of Engineering and Sciences, E. Garza Sada 2501 Sur, Monterrey 64849, Mexico)

  • Gerardo Treviño-Garza

    (Tecnologico de Monterrey, School of Engineering and Sciences, E. Garza Sada 2501 Sur, Monterrey 64849, Mexico)

  • Armando Céspedes-Mota

    (Tecnologico de Monterrey, School of Engineering and Sciences, E. Garza Sada 2501 Sur, Monterrey 64849, Mexico)

  • Amir Hossein Nobil

    (Tecnologico de Monterrey, School of Engineering and Sciences, E. Garza Sada 2501 Sur, Monterrey 64849, Mexico)

Abstract

Inventory management seeks to improve manufacturing by contracting inventory costs in a similar fashion to raise efficiency and profit. One approach is to develop inventory management models according to actual production systems. Furthermore, governmental policies in many countries impose many regulations on firms to fulfill the growing demand for a reduction in carbon emissions. Warm-up is a familiar concept in industrial applications. It allows the manufacturing system to work at a higher level of productivity and efficiency, as well as decreasing the number of defective items and maintenance costs. Along with fewer poor-quality items, the system has less waste as scrap items entering the environment and also requires less energy and workload to focus on reworking. The economic production quantity (EPQ) problems with a warm-up as an input parameter have been studied in a few works recently. This paper proposes a production-inventory model which considers the warm-up period as a decision variable and investigates its impact on the total cost. Furthermore, the defective rate is a decreasing linear function related to the warm-up period’s length. The production-inventory model takes into account the carbon emission tax policy. The main aim of this research is to jointly optimize both the length of the warm-up period and the production cycle in order to minimize the total cost of the production-inventory system and, therefore, reduce emitted carbon emissions. The comparison of tax prices and the effect of the proper warm-up period on the amount of carbon emissions are discussed in the sensitivity analysis.

Suggested Citation

  • Erfan Nobil & Leopoldo Eduardo Cárdenas-Barrón & Imelda de Jesús Loera-Hernández & Neale R. Smith & Gerardo Treviño-Garza & Armando Céspedes-Mota & Amir Hossein Nobil, 2023. "Sustainability Economic Production Quantity with Warm-Up Function for a Defective Production System," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
  • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:1397-:d:1032451
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    References listed on IDEAS

    as
    1. Hua, Guowei & Cheng, T.C.E. & Wang, Shouyang, 2011. "Managing carbon footprints in inventory management," International Journal of Production Economics, Elsevier, vol. 132(2), pages 178-185, August.
    2. Glock, C. H. & Jaber, M. Y. & Searcy, C., 2012. "Sustainability strategies in an EPQ model with price- and quality-sensitive demand," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 59335, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Stefano Carattini & Maria Carvalho & Sam Fankhauser, 2018. "Overcoming public resistance to carbon taxes," Wiley Interdisciplinary Reviews: Climate Change, John Wiley & Sons, vol. 9(5), September.
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    6. Amir Hossein Nobil & Sunil Tiwari & Fatemeh Tajik, 2019. "Economic production quantity model considering warm-up period in a cleaner production environment," International Journal of Production Research, Taylor & Francis Journals, vol. 57(14), pages 4547-4560, July.
    7. S. Ganesan & R. Uthayakumar, 2021. "EPQ models with bivariate random imperfect proportions and learning-dependent production and demand rates," Journal of Management Analytics, Taylor & Francis Journals, vol. 8(1), pages 134-170, January.
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