Article: Forecast-corrected production-inventory control policy in unreliable manufacturing systems Journal: European Journal of Industrial Engineering (EJIE) 2017 Vol.11 No.5 pp.569 - 587 Abstract: In traditional research on production-inventory control problems with failure-prone manufacturing systems, a stationary demand process is an essential assumption. However, such a situation may not be true. This study extends the hedging-point-based production-inventory control problem into the case with non-stationary demand. The demand forecasting process is simulated and categorised into two different cases. First of all, a two-level control policy is proposed to solve the problem with a Markov modulated Poisson demand process which is often used in qualitative forecasting. Then the quantitative forecasting process using time series methods is modelled and a forecast-corrected control policy is proposed accordingly. The impact of forecasting on the system performance is then investigated. An integrated simulation and experimental design method was adopted to solve the modified optimal control problem. The results show that the proposed control policy can outperform the traditional stationary policy when the forecasting error is limited to a certain level. [Received 29 August 2014; Revised 13 July 2015; Revised 12 April 2016; Revised 20 September 2016; Revised 21 September 2016; Accepted 30 March 2017] Inderscience Publishers - linking academia, business and industry through research

Title: Forecast-corrected production-inventory control policy in unreliable manufacturing systems

Authors: Nan Li; Felix T.S. Chan; S.H. Chung

Addresses: Department of Industrial and System Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong ' Department of Industrial and System Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong ' Department of Industrial and System Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong

Abstract: In traditional research on production-inventory control problems with failure-prone manufacturing systems, a stationary demand process is an essential assumption. However, such a situation may not be true. This study extends the hedging-point-based production-inventory control problem into the case with non-stationary demand. The demand forecasting process is simulated and categorised into two different cases. First of all, a two-level control policy is proposed to solve the problem with a Markov modulated Poisson demand process which is often used in qualitative forecasting. Then the quantitative forecasting process using time series methods is modelled and a forecast-corrected control policy is proposed accordingly. The impact of forecasting on the system performance is then investigated. An integrated simulation and experimental design method was adopted to solve the modified optimal control problem. The results show that the proposed control policy can outperform the traditional stationary policy when the forecasting error is limited to a certain level. [Received 29 August 2014; Revised 13 July 2015; Revised 12 April 2016; Revised 20 September 2016; Revised 21 September 2016; Accepted 30 March 2017]

Keywords: supply chain; production control; inventory control; forecasting; simulation; optimisation.

DOI: 10.1504/EJIE.2017.087677

European Journal of Industrial Engineering, 2017 Vol.11 No.5, pp.569 - 587

Published online: 30 Oct 2017 *

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Title: Forecast-corrected production-inventory control policy in unreliable manufacturing systems

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