Optimizing production strategies for deteriorating items in two-level manufacturing

Brijendra Yadav; Chaman Singh; Sanju Kumar; Gurudatt Rao Ambedkar

doi:10.5269/bspm.80497

Brijendra Yadav Department of Mathematics, RLA College, University of Delhi, Delhi https://orcid.org/0009-0003-8235-3714
Prof Chaman Singh Department of Mathematics, Acharya Narendra Dev College, University of Delhi, Delhi https://orcid.org/0000-0002-2107-5584
Sanju Kumar Department of Mathematics, Acharya Narendra Dev College, University of Delhi, Delhi https://orcid.org/0000-0002-1233-4978
Gurudatt Rao Ambedkar Department of Mathematics, Hansraj College, University of Delhi, Delhi https://orcid.org/0000-0003-4758-0914

Abstract

A modern business enterprise should develop a sound operational system of organization to meet the challenges of an ever-changing environment where conditions are somewhat too unpredictable. The need to increase production is determined by the demand for specific goods rising with time, which in many cases is done because of the growth in popularity and the value associated with the product. Thus, the organization faces pressure to increase its manufacturing rates to meet the increased demand. The proposed model optimizes a deteriorating goods inventory system with two different manufacturing rates and exponentially formulable demand. Production initially starts off at a constant rate, how is that production, demand, inherent deterioration and variable manufacturing rates combine to build up the inventory level progressively. The more the demand rate is increased, the more the production rate is increased by the factor known as a so that it is managed according to the market. The feedback system is important to ensure that supply and demand is balanced in a dynamic marketplace. The empirical results only further show that a 10% increase in production costs is equivalent to a 5% increase in total costs, which shows the non-linear relationship between cost input and the overall financial performance. To promote the reliability of the model, a sensitive analysis has been carefully conducted, and thus a robustness check of the model and predictive reliability of its operational results has been verified.

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