Simulation-based optimization of a single-stage failure-prone manufacturing system with transportation delay

International Journal of Production Economics

2013

This paper deals with the problem of the joint determination of the optimal lot sizing and optimal production control policy for an unreliable and imperfect manufacturing system, where the quality control of lots produced is performed using an acceptance sampling plan. The proportion of defective items, the time between failures and the time to repair are generally distributed. The incurred total cost includes manufacturing cost, transportation cost, inspection costs, rejection cost of defective items, replacement cost for returned defective items from customers, and holding and backlog costs. The associated cost minimization problem is formulated with a stochastic dynamic programming model where the lot sizing and production rate are considered as decision variables. Given the difficulties in solving such a highly stochastic model analytically or numerically, we adopted a modified hedging point policy (HPP) to control the production rate, as well as an economic lot sizing policy for batch processing control; we also relied on a simulation-based experimental approach to determine a close approximation of the optimal control parameters. It is shown that production should be accelerated at the maximum production rate, not only when building the safety stock, as in the classical HPP, but also after rejecting a lot, in order to recuperate the loss in inventory and to maintain the on-hand safety stock. Numerical experiments and thorough sensitivity analyses are provided to illustrate the effectiveness of the proposed control policy and the robustness of the resolution approach. Some interesting behaviours regarding the impact of different parameters on the optimal decision variables are observed and discussed.

Section: Heuristic Control Policymentioning

confidence: 99%

Joint optimal lot sizing and production control policy in an unreliable and imperfect manufacturing system

International Journal of Production Economics

2013

“…For unreliable batch manufacturing systems with delays which cannot be considered as continuous-flow systems, Bouslah et al (2012) showed that the optimal feedback control policy can be closely approximated by a base-stock policy expressed by a modified HPP. When the batches produced need to be transported for a non-negligible delay to the serviceable stock, the authors assumed that the feedback inventory control is based on the concept of the inventory position which includes the on-hand inventory in the final stock and the total pending quantities in transportation as in Mourani et al (2008) and Li et al (2009). In our study, we define the inventory position y(t) at each time t as the sum of the stock (inventory/backlog) level x(t) and the total amount of batches under sampling, 100% inspection and rectification.…”

Section: Production Control Policymentioning

confidence: 99%

Joint production and quality control of unreliable batch manufacturing systems with rectifying inspection

International Journal of Production Research

2013

Production control policy and economic sampling plan design problems have been studied separately in previous research. This paper considers a joint production control policy and economic single sampling plan design for an unreliable batch manufacturing system. The production is controlled by a modified hedging point policy which consists in building and maintaining a safety stock of finished product to avoid shortages during corrective maintenance. The main objective of this paper is to determine simultaneously the economic production quantity, the optimal safety stock level and the economic sampling plan design which minimize the expected overall cost. A stochastic mathematical model is developed and solved using a simulation optimization approach based on the response surface methodology. Simulation is used to imitate the complex dynamic and stochastic behaviour of processes as in the real-life industrial systems. The obtained results show clearly strong interactions between production quantity, inventory state and sampling plan design which confirm the necessity of jointly considering production and quality control parameters in an integrated model. Moreover, it is shown a significant impact of production system reliability on the economic sampling plan design and therefore on the quality of finished product delivered to consumers. Numerical example and sensitivity analyses are presented for illustrative purposes.

“…In the literature, as in Mourani et al (2008) and Li et al (2009), the production control policies with considerable transportation delay are based on controlling the inventory position which takes into account the on-hand inventory and the total quantity of lots-under-transportation. The relationship between the inventory level ( ) x t , the inventory position ( ) y t and the demand during the transportation delay d   can be written as follows (Mourani et al, 2008):…”

Section: Control Policy Structurementioning

confidence: 99%

“…They derived a heuristic control policy for a job shop problem with delays using theoretical arguments and approximations. Also, Mourani et al (2008) studied a single-stage failure-prone manufacturing system where the produced material flow is added to a finished goods inventory after transportation. Considering that the production is controlled by a HPP, they focused on optimizing the continuous-flow model integrating the transportation delay.…”

mentioning

confidence: 99%

Optimal production control policy in unreliable batch processing manufacturing systems with transportation delay

International Journal of Production Research

et al. 2013

This paper considers the problem of production planning of unreliable batch processing manufacturing systems. The finished goods are produced in lots, and are then transported to a storage area in order to continuously meet a constant demand rate. The main objective of this work is to jointly determine the optimal lot sizing and optimal production control policy that minimize the total expected cost of inventory/backlog and transportation, over an infinite time horizon. The decision variables are the lot sizing and the production rate. The problem is formulated with a stochastic dynamic programming model and the impulse control theory is applied to establish the Hamilton-Jacobi-Bellman (HJB) equations. Based on a numerical resolution of the HJB equations, it is shown that the optimal control policy is governed by a base stock policy for production rate control and economic lot size for batch processing. A thorough analysis and practical issues are addressed with a simulation based approach. Thus, a combined discrete-continuous simulation model is developed to determine the optimal parameters of the proposed policy when the failure and repair times follow general distributions. The results are illustrated with numerical examples and confirmed through sensitivity analysis.