Markovian model with absorbing states for the a priori costing of serial production processes

V. Deibe Blanco, R. Acosta Vega, M. J. Campuzano

This paper summarizes the development of a Markov model that allows the calculation of the efficiency of a serial production line, the equivalent average costs of each stage of the process and the final average cost. This model originates from the need to estimate the a priori cost of a production batch considering that companies experience high rejection costs due to the obtention of non-conforming products. This paper presents three cases associated to the implementation of a Markov chain with absorbing states under three different scenarios: optimistic, intermediate, and pessimistic, based on historical data and significance levels, which are used to construct confidence intervals for every transition probability in each operation (states).

Keywords: Markov chain, serial production system, production costs, confidence intervals.

Scheduled

Methods and Applications of Operations Research
November 10, 2023  4:00 PM
CC4: Room 2

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