A sustainable inventory optimisation considering imperfect production under uncertain environment


Mukherjee A. K., Maity G., Jablonsky J., Roy S. K., Weber G. W.

International Journal of Systems Science: Operations and Logistics, cilt.11, sa.1, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 11 Sayı: 1
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1080/23302674.2024.2379540
  • Dergi Adı: International Journal of Systems Science: Operations and Logistics
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Anahtar Kelimeler: development cost, Economic production quantity, fuzzy-random number, imperfect production, time variant demand and carbon emission
  • Orta Doğu Teknik Üniversitesi Adresli: Evet

Özet

This study enhances economic production quantity model by incorporating repairable defective products within an uncertain environment. To reflect practical scenarios, demand and repair rates are modelled as exponential functions of time. The model considers both defective and used products as repairable, treating repaired items as new products. Additionally, the study addresses pollution by introducing four different carbon emission policies, each leading to the development of distinct models. A unique aspect of this model is the inclusion of development cost and the use of fuzzy-random cost parameters to account for real-life imprecision and market fluctuations. Next, fuzzy-random economic production quantity model is formulated based on these assumptions. Three numerical examples demonstrate the model's utility, revealing that the strictly permitted cap policy results in the shortest production time but higher cost per product. Sensitivity analysis further illustrates the impact of various model parameters. Thus, the main contributions of the study are two-fold: it discusses and validates four carbon taxation policies for different real-world scenarios and provides information related to the sensitivity of different parameters and key values of these parameters at which cost per product minimise.