Production planning decision of a dairy under supply disruption and demand uncertainty. (30th December 2020)

• Record Type: Journal Article
• Authors: Jena, Dayanidhi; Ray, Pritee
• Is Part Of: Journal of modelling in management. Volume 17:Number 1(2022)
• Page Start: 256
• Page End: 271
• Publication Date: 2020-12-30
• Subjects: Decision-making -- Optimization -- Planning -- Production -- Nonlinear programing -- Supply chain management -- Demand uncertainty -- Mixed-integer nonlinear programing -- Production planning -- Supply disruption -- Dairy industry; Industrial management -- Mathematical models -- Periodicals; Industrial management -- Computer simulation -- Periodicals; Business -- Mathematical models -- Periodicals; Business -- Computer simulation -- Periodicals; 658.4033
• DOI: 10.1108/JM2-01-2020-0028
• Languages: English
• ISSNs: 1746-5664

Abstract

Abstract : Purpose: The purpose of this paper is to develop a model for the production planning decision of a dairy plant in a multi-product setting under supply disruption risk and demand uncertainty while determining the optimal product-mix and material planning requirement. Design/methodology/approach: A mixed-integer nonlinear programming model is proposed to determine the optimal product-mix that maximizes the expected profit of a dairy. The data are collected through visits to the dairy site, conducting brainstorming sessions with the plant manager and marketing head at the corporate office. Disruption data are collected from the India Meteorological Department, Odisha. Findings: From the analysis, it is recommended that the dairy should not produce curd during the planning period. Moreover, turnover from toned, double toned and baby food is maximum than that of the curd and these products are produced in the planning period. The expected profit increases from its present value when an optimal product-mix is followed. Sensitivity analysis is performed to analyze the effect of demand uncertainty, supply disruption and production quota. The expected profit decreases as the supply failure probability increases. Research limitations/implications: The model is implemented in a dairy plant under Orissa State Cooperative Milk Producers Federation, Odisha, India. The proposed methodology has not been validated, theoretically. The concerned dairy is based on the Indian context, but the authors believe that the study is highly relevant to other dairies as well. Practical implications: This study provides a methodology for dairy plant managers to plan production effectively under supply disruption risk with demand uncertainty. It also suggests material requirement planning at different factories of the dairy plant. Originality/value: This paper develops a mathematical model for the production planning decision of a dairy plant that determines the optimal product-mix, which maximizes the expected profit of a dairy under disruption risk and demand uncertainty (in the Indian context).