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Optimal lot-sizing policy for a failure prone production system with investment in process quality improvement and lead time variance reduction
Author(s) -
Sourav Sarkar,
Bibhas C. Giri
Publication year - 2022
Publication title -
journal of industrial and management optimization
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.325
H-Index - 32
eISSN - 1553-166X
pISSN - 1547-5816
DOI - 10.3934/jimo.2021048
Subject(s) - production (economics) , investment (military) , lead time , variance (accounting) , reduction (mathematics) , computer science , quality (philosophy) , variance reduction , process (computing) , economic production quantity , mathematical optimization , operations research , sizing , economics , operations management , mathematics , microeconomics , art , philosophy , geometry , accounting , epistemology , politics , political science , law , visual arts , operating system
To survive in today's competitive market, it is not enough to produce low-cost products but also quality-related issues and lead time needs to be considered in the decision-making process. This paper extends the previous research by developing a stochastic economic manufacturing quantity (EMQ) model for a production system which is subject to process shifts from an in-control state to an out-of-control state at any random time. Moreover, we consider the option of investment to increase the process quality and decrease the lead-time variability. Closed-form solutions of the proposed models are obtained by applying the classical optimization technique. Some lemmas and theorems are developed to determine the optimal solution of the decision variables. Numerical results are obtained for each of these models and compared with those of the basic EMQ model without any investment. From the numerical analysis, it has been observed that our proposed model can significantly reduce the cost of the system compared to the basic model.

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