A STOCHASTIC ANALYSIS APPROACH ON THE COST-TIME PROFILE FOR SELECTING THE BEST FUTURE STATE MA

Seyed Mohammad Seyedhosseini, Ahmad Ebrahimi-Taleghani

Abstract


In the literature on value stream mapping (VSM), the only basis for choosing the best future state map (FSM) among the proposed alternatives is the time factor. As a result, the FSM is selected as the best option because it has the least amount of total production lead time (TPLT). In this paper, the cost factor is considered in the FSM selection process, in addition to the time factor. Thus, for each of the proposed FSMs, the cost-time profile (CTP) is used. Two factors that are of particular importance for the customer and the manufacturer – the TPLT and the direct cost of the product – are reviewed and analysed by calculating the sub-area of the CTP curve, called the cost-time investment (CTI). In addition, variability in the generated data has been studied in each of the CTPs in order to choose the best FSM more precisely and accurately. Based on a proposed step-by-step stochastic analysis method, and also by using non-parametric Kernel estimation methods for estimating the probability density function of CTIs, the process of choosing the best FSM has been carried out, based not only on the minimum expected CTI, but also on the minimum expected variability amount in CTIs among proposed alternatives. By implementing this method during the process of choosing the best FSM, the manufacturing organisations will consider both the cost factor and the variability in the generated data, in addition to the time factor. Accordingly, the decision-making process proceeds more easily and logically than do traditional methods. Finally, to describe the effectiveness and applicability of the proposed method in this paper, it is applied to a case study on an industrial parts manufacturing company in Iran.


Keywords


Value stream mapping, Future state map, Cost-time profile, Cost-time investment, Kernel density estimation

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DOI: https://doi.org/10.7166/26-1-644

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Copyright (c) 2015 The South African Journal of Industrial Engineering


ISSN 2224-7890 (on-line) ; ISSN 1012-277X (print)


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