How does an industry control a decision support system for a long time?

¹ Department of Applied Sciences and Humanities, Parul Institute of Engineering and Technology, Parul University, Vadodara 391760 Gujarat, India
² Government Polytechnic Dahod, Dahod, 389151 Gujarat, India
³ Department of Industrial Engineering, Yonsei University, 50 Yonsei-ro, Sinchon-dong, Seodaemun-gu, Seoul 03722, South Korea
⁴ Department of Computer Science and Engineering, Saveetha School of Engineering, Saveetha Institute of Medical and Technical Sciences, Saveetha University, 162, Poonamallee High Road, Velappanchavadi, Chennai, Tamilnadu 600077, India

^* Corresponding author: bsbiswajitsarkar@gmail.com

Received: 20 June 2020
Accepted: 17 April 2021

Abstract

The inventory system has been affected by many characteristics, among which deterioration of a food product is a critical issue. Chilled foods deteriorate during storage time, and their quality reduces over time. Indian Spiced Pulled Pork Sandwiches are very observable customer goods in India that are, in fact, unpreserved. If chilled foods’ original value reduces over time, consumers are not much likely to buy them. The retail price of chilled food maintained is strictly dependent on its quality. From the vendor’s approach, measuring quality and leftover value should be a severe commercial issue. The model aims to study deterioration together with the quality prediction of Indian Spiced Pulled Pork Sandwiches. This model measures food quality and leftover value. Deterioration rate is considered as a function of two-parameter Weibull distribution, suitable for bacterial inactivation, microbial growth, enzymes, nutrients, and pigments dreadful environments under a non-isothermal atmosphere. The dynamic structure of demand has its importance in business. The price-storage time of product-dependent demand rate is debated in this model as demand rarely remains constant. The objective is to maximize the vendor’s total profit concerning storage time and the product’s selling price. A numerical example supports the model. Sensitivity analysis is carried out to derive insights for decision-makers. The graphical result, in three dimensions, is exhibited with a supervisory decision.