• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.19 no.37
• /
• pp.31-40
• /
• 1996

The amount of safety stock is decided from various information such as the forecasted demand, the lead time, the size of the order quantity and the desired service level. There are two cases to consider the problem of setting safety stock when both the demand in a period and the lead time are characterized as random variables: the first case is the parameters of the demand and lead time distributions are known, the second case is they are unknown and must be estimated. The objective of this study is to present the procedure for setting safety stocks in the case the parameters of the demand and lead time distributions are unknown and must be estimated. In this study, a simple exponential smoothing model is used. to generate the estimates of demand in each period and a discrete distribution of the lead time is developed from historical data, and the optimal service level is used which determined to consider both of a backorder and lost sale.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.28 no.2
• /
• pp.146-151
• /
• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.28 no.4
• /
• pp.79-84
• /
• 2005

Some distributions have been used for diagnosing the lead time demand distribution in inventory system. In this paper, we describe the negative binomial distribution as a suitable demand distribution for a specific retail inventory management application. We here assume that customer order sizes are described by the Poisson distribution with the random parameter following a gamma distribution. This implies in turn that the negative binomial distribution is obtained by mixing the mean of the Poisson distribution with a gamma distribution. The purpose of this paper is to give an interpretation of the negative binomial demand process by considering the sources of variability in the unknown Poisson parameter. Such variability comes from the unknown demand rate and the unknown lead time interval.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.34 no.4
• /
• pp.91-112
• /
• 2009

The bullwhip effect means the phenomenon of increasing demand variation as moving UP to the upstream in the supply chain. Therefore, it is recognized that the bullwhip effect is problematic for effective supply chain operations. In this paper, we exactly quantifies the bullwhip effect for the case of stochastic lead time and seasonal demand in two-echelon supply chain where retailer employs a base-stock policy considering SARMA demand processes and stochastic lead time. We also investigate the behavior of the proposed measurement for the bullwhip effect with autoregressive and moving average coefficient, stochastic lead time, and seasonal factor.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.10 no.16
• /
• pp.143-147
• /
• 1987

Safety stocks constitute one of the major means of dealing with the uncertainties associated with variation in demand and lead time. Adeguate safety facilitate production activities and help to assure customers if good service on the other hand, carrying safety storks ties up working capital on goods that sit idle. The major problem of safety stocks management thus of consists of trying to achieve an optimal balance between the other carrying cost and the costs of stock shortage. Therefore, this study aims to find safety stock level of the fixed reorder quantity system and the fixed reorder cycle system of minimizing total cost when both demand and lead time are variable. (The distribution of demand and lead time is a mere assumption that follows the normal distribution) The results can be summarized as follows. i) Safety factor on the safety stock is determined by carrying cost and the costs of stock shortage: An optimal safety stick=the costs of stork shortage($C_s$) (the carrying cost($C_h$)+the costs of stock storage($C_s$). ii) The safety stock level of the fixed reorder quantity system is ($a{\;}_p\sqrt{L}{\sigma}$) under uncertainties. iii) The safety stock level of the fixed reorder cycle system is ($a{\;}_p\sqrt{R+L{\sigma}}$) under uncertain demand and constant lead time. ($a{\;}_p\sqrt{L{\sigma}_d{\;^2+{\mu}^2L{\sigma}^2}$) under demand and lead time uncertainties.

• Proceedings of the Safety Management and Science Conference
• /
• 2011.11a
• /
• pp.557-561
• /
• 2011

The study proposes three types of production lead time according to the production or demand pattern. First of all, it discusses the difference of three lead times. While pitch time and cycle time are used in push system with process stock and mass conveyor production, the tact time is used in pull system like as JIT based lean production system.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.44 no.4
• /
• pp.220-226
• /
• 2021

In supply chain, there are a variety of different uncertainties including demand, service time, lead time, and so forth. The uncertainty of demand has been commonly studied by researchers or practitioners in the field of supply chain. However, the uncertainty of upstream supply chain has also increased. A problem of uncertainty in the upstream supply chain is the fluctuation of the lead time. The stochastic lead time sometimes causes to happen so called the order crossover which is not the same sequences of the order placed and the order arrived. When the order crossover happens, ordinary inventory policies have difficult to find the optimal inventory solutions. In this research, we investigate the lead time distribution in case of the order crossover and explore the resolutions of the inventory solution with the order crossover.

• Journal of the Korean Operations Research and Management Science Society
• /
• v.17 no.2
• /
• pp.91-106
• /
• 1992

It an inventory control system, the demand over time are often assumed to be independently identically distributed (i. i. d.). However, the demands may well be correlated over time in many situations. The estimation of reorder points is not simple for correlated demands with variable lead time. In this paper, a general class of autoregressive and moving average processes is considered for modeling the demands of an inventory item. The first four moments of the lead-time demand (L) are derived and used to approximate the distribution of L. The reorder points at given service level are then estimated by the three approximation methods : normal approximation, Charlier series and Pearson system. Numerical investigation shows that the Pearson system and the Charlier series performs extremely well for various situations whereas the normal approximation show consistent underestimation and sensitive to the distribution of lead time. The same conclusion can be reached when the parameters are estimated from the sample based on the simulation study.

• Journal of the Semiconductor & Display Technology
• /
• v.22 no.2
• /
• pp.104-111
• /
• 2023

The semiconductor industry, which relies on global supply chains, has recently been facing longer lead time for material procurement due to supply chain uncertainties. Moreover, since increasing customer satisfaction and reducing inventory costs are in a trade-off relationship, it is challenging to determine the appropriate safety stock level under demand and lead time uncertainties. In this paper, we propose a framework for determining safety stock levels by utilizing the optimization method to determine the optimal safety stock level. Additionally, we employ a linear regression method to analyze customer satisfaction scores and inventory costs based on variations in lead time and demand. To verify the effectiveness of the proposed framework, we compared safety stock levels obtained by the regression equations with those of the conventional method. The numerical experiments demonstrated that the proposed method successfully reduces inventory costs while maintaining the same level of customer satisfaction when lead time increases.

• Korean Management Science Review
• /
• v.13 no.1
• /
• pp.47-55
• /
• 1996

Rapid globalization of production and marketing functions makes choice of international transportation mode of great importance. In this paper, transportation mode is characterized by two factors, mean and variability of transportation lead time. We developed a simple mathematical model to estimate the relative impact of mean lead time, lead time variance and demand variance on the required average inventory level under specified service rates.