The goal of inventory management is to decide the timing and quantity of ordering in response to various kinds of uncertainty. The failure of manufacturing machines, shortage of materials, and overworking may prevent manufacturers from achieving the planned quantity of items. Additionally, some nonconforming items may be included in the replenishment to retailers as a result of imperfect production and inspection by manufacturers and damage during transport. Consequently, the planned quantity of items may not be supplied to retailers. The uncertainty about production should be considered in the decision-making of inventory management. In this article, we consider the impact of nonconforming items on the following traditional inventory systems: continuous review and periodic review. In particular, we investigate how the inclusion of nonconforming items has an influence on inventory policies and operating costs. Then, the difference of influence between both systems is discussed.

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In this paper, we discuss the scheduling problem of lot production lines in the Toyota production system. A lot production line at Toyota produces parts in accordance with its schedule, which is planned in advance using lot sizes predetermined for each part. The lot size of each part produced in practice is the consumption of the part in the subsequent process in the time interval between the starting time of the previous production run of the part and the starting time of the next production run. As the schedule of lot production lines is determined in advance, in order to adapt to fluctuations in parts consumption, the lot size of the part is changed every time the part is produced. In scheduling lot production lines, the consumption of each part in the time interval between a certain production run of the part and the next production run need to be equal to the lot size predetermined for each part as much as possible. The reason is that we must hold the part inventory equal to the part consumption in the maximum time interval. Therefore, we need to develop a schedule to reduce the total amount of the inventory of each part to a minimum. We propose an approximation algorithm and a method for improving the feasible solution computed by the approximation algorithm. We show, by numerical examples, that the methods presented efficiently obtain a good solution.

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This paper proposes a simulation model which recreates the change in price-sales distribution of general-purpose electronic parts (GEPs) due to fluctuations in business. We apply the hedonic approach to extract characteristics such as value drivers from the attributes of the GEPs. Using the concept that if the hedonic function for the characteristics is linear, then the GEPs are decomposed into unit-price and the unit-characteristic, we could interpret the GEPs as a characteristic cluster. Our simulation model is composed of the following three elements. 1) characteristic cluster, 2) random numbers lattice as a virtual market, and 3) the probability of the agreement at each lattice point. According to our simulation results, the cluster size-frequency distribution was approximate to the price-sales distribution observed from the real sales data. Additionally, with the decreased probability of the agreement in the business slowdown period, we found that the behavior of the cluster size-frequency distribution corresponds to the price-sales distribution obtained from the sales data of the real business slowdown period.

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In an attempt to make a model for supply chain management (SCM) system design, this study clarifies how the elements for the realization of a SCM system are related to each other. This study aims to propose a modeling method for SCM system design. The proposed model is multistage-structured so that the framework is formed by the elements necessary for designing the SCM system. The quantitative relations between elements in the framework, which depend on the production-sales system and target of a group company, are determined by the present authors' survey of companies. The results of a survey of Japanese companies in China are used to construct a quantitative model.

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