Journal of Japan Industrial Management Association
Online ISSN : 2187-9079
Print ISSN : 1342-2618
ISSN-L : 1342-2618
Volume 54 , Issue 1
Showing 1-19 articles out of 19 articles from the selected issue
  • Type: Cover
    2003 Volume 54 Issue 1 Pages Cover1-
    Published: April 15, 2003
    Released: November 01, 2017
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  • Type: Cover
    2003 Volume 54 Issue 1 Pages Cover2-
    Published: April 15, 2003
    Released: November 01, 2017
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  • Type: Index
    2003 Volume 54 Issue 1 Pages Toc1-
    Published: April 15, 2003
    Released: November 01, 2017
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  • Jae Kook LIM, Kap Hwan KIM, Joon Mook LIM, Kazuho YOSHIMOTO, Teruo TAK ...
    Type: Article
    2003 Volume 54 Issue 1 Pages 1-10
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    A routing method is suggested for automated guided vehicles using a reinforcement learning technique. This paper focuses on an algorithm called Qlearning that can acquire optimal routing strategies from delayed rewards, even when the agent has no prior knowledge of the effects of its actions on the environment. In manufacturing shops, there is a high possibility that vehicles on the way to the destination will experience unexpected delays due to interference from other vehicles. Thus, routes of the shortest travel distance are not necessarily the shortest in travel time. This paper discusses how the Q-learning technique can be applied to the routing problem. A numerical experiment was performed to evaluate the performance of the rules obtained from the learning process and the speed of the convergence of an objective value. The performance of the learning-based rules was compared with that of the shortest distance rule.
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  • Heng ZAHNG, Yo ISHIZUKA, Hideaki YAMASHITA
    Type: Article
    2003 Volume 54 Issue 1 Pages 11-18
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    We consider optimal resource allocations, especially buffer space allocation, in job shop production systems that can be modeled by a class of queueing network systems with variable service times, fixed order of services at each server and fixed route of each part. Under a given topology of the production network, processing schedule, service time distributions and total amount of buffer spaces available, the objective is to find an allocation of buffers for the servers that maximizes system throughput. To resolve this type of problem, one needs to perform two major tasks. One is to develop an approximation scheme or model for calculating the performance index (throughput values) since it is generally hard to evaluate them exactly. The other is how to solve the optimal buffer space allocation problem which is NP hard. Our approach is based on the so-called "sample-path optimization" process combined with the "common random number" technique. Under randomly generated service times, the sample-path of departure times of parts from each server, which can be determined by a set of simple recursion formulae (simulation run), is used for estimating the system throughput, and we search for the optimal buffer allocation that maximizes throughput. As a solution method for the approximate buffer space allocation problem, we use a simple genetic algorithm. Numerical experiments shown that our approach is applicable for larger sized problems.
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  • Hiroyuki ARIMITSU, Kenichi NAKASHIMA, Toyokazu NOSE, Sennosuke KURIYAM ...
    Type: Article
    2003 Volume 54 Issue 1 Pages 19-25
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    Many industries have mass-produced and consumed excessive amounts of resources with consideration for only economical efficiency. Most of the products are discarded at the end of their lifetime. Therefore, an important issue is how to deal with used products that have become outdated. With respect to saving resources and environmentally conscious manufacturing, the discarded products should be recovered and their components used to make new products. In a traditional inventory control problem, we focused on inventory on-hand in the system. In a remanufacturing system, however, we should consider all the products which have been bought by customers as the inventory in the factory. This paper proposes a remanufacturing system model with stochastic variability such as customer demand, recovery rate and so on. A product manufactured by this system has its own lifetime and will be taken back from the customers by a specific period. We have utilized the theory of a perishable inventory control to develop a new model of inventory management for remanufacturing systems. In this system, we propose to manage inventory at every point, until products are collected and used in remanufacturing. The numerical examples are given to show the effect of changing the amount of new products and the recovery rates under stochastic demand.
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  • Masatoshi MORI, Masayuki GOTO
    Type: Article
    2003 Volume 54 Issue 1 Pages 26-35
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    This paper focuses on a strategy for determining the price and timing of a new product to be introduced into the market. Every product has its own life cycle; that is, birth, grow, maturity and death, and therefore, we have to decide when and how to stop production of the current product and start sales of the new product. To make a smooth product changeover, the pricing of both old and new products plays an important role. We developed the following heuristic optimization model to help managers decide this switching action and maximize profits in a market where the product has a short life cycle, like a personal computer. When thinking about the product demand, we considered three patterns : market growth, market retraction, unchanged market. For market growth, if is reasonable to think that the product's potential market size could be increased by new value being added through technological innovation of the product. In this paper, we propose a new model to help the manager's decision-making process regarding this switching action taking the maximization of profits at a given demand pattern into consideration. We approach the point using a planning base ranging from a few months to one year, not using long-term demand. This paper approaches development of a profit maximization model considering switch timing.
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  • Yoshiomi MUNESAWA, Hirokazu OSAKI, Yasuhiro KAJIHARA, Masahiko TATSUMI
    Type: Article
    2003 Volume 54 Issue 1 Pages 36-45
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    In this paper, we propose a distributed disassembly system in which products are disassembled into parts or units based on the home material separation criteria in each house for material recycling. In this system, a citizen disassembles the discarded electric appliance by oneself and separates disassembled parts according to material type (such as iron, copper, alminum) in each home, and separated waste parts are taken to the recycling collection point. This system can reduce the disassembly and separation work in the recycling center, because separated waste parts are collected at the center. The flows of wastes are used to evaluate the efficiency of the proposed system and a conventional electronic waste system. The amount of work is shown as a work unit, meaning the disassembly work or separation work for one part in this paper. Additionally, we propose a disassembly guideline for electronic waste which shows the main material in each part and connection for disassembly. In application, we estimated the work amount of the proposed system and a conventional system from actual data. The disassembling and separation work in the conventional system are overconcentrated in the recycling center. However the work in the distributed disassembly system is decentralized to each family discarding the waste product. It is clear that the variance in work amount and misclassification of material type depend on disassembly guideline information.
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  • Tomoyuki HIROTA, Hiroshi OHTA
    Type: Article
    2003 Volume 54 Issue 1 Pages 46-52
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    Competition and continuous improvement efforts have led many firms to review their production-inventory practices. In particular, given the push toward a "zero-inventory" goal, major companies have begun to search for conditions that determine when it is optimum to hold a finished-goods inventory and when it is not. There are two production policies. If a finished-goods inventory is held for a product, the product is produced as "make-to-stock" (MTS), and if it is not, it is produced as "make-to-order" (MTO). Note that the designation of a product as MTO merely indicates stockless production, and does not mean that the product is made to order due to custom specifications. Recently, Arreola-Risa et al. proposed the optimum conditions for MTO and MTS policies using the M/G/1 queuing model under the base-stock inventory policy as the production-inventory system model. To address the optimality of MTS and MTO policies, they considered a company that produces multiple products facing random demands and the inventory holding costs of managing the production-inventory system. However, they did not discuss the optimum base-stock level in the case of adopting the MTS policy and the derivation of the total expected cost. Hirota et al. proposed not only the optimum conditions for MTO and MTS policies, but also the optimum base-stock level for the MTS policy using the M/Er/1 queuing model as the production-inventory system model. However, they discussed this under stationary state conditions and the time element was not included. In this study, we propose the optimum production-inventory policy for MTO versus MTS under transitional state conditions, where the time element is taken into consideration using the M/M/1 queuing model instead of the M/Er/1 queuing model as the production-inventory system model.
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  • Takayuki FURUTANI, Hiroshi OHTA
    Type: Article
    2003 Volume 54 Issue 1 Pages 53-59
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    Inventory policies are crucial to all buyers and suppliers. Recent research trends in inventory management and supply chain management have also focused on the impact of customer behavior on the system and the interaction or relationship among supply chain partners. The flow of business, such as information and logistics, is improved from the viewpoint of the whole supply chain (i.e., including the customer), and it becomes a target to have the optimum outcome as a complete system. Recently, Sharafali et al. presented some stochastic models of cooperation between the supplier and buyer, and discussed the effect of cooperation in (s, S) inventory policies. On the other hand, Cheung & Zhang focused on another source of demand information distortion that leads to the well-known "bullwhip effect" : customer order cancellation. They found that cancellations, as major sources of inventory information distortion, increase total system costs. In this study, we treat a supply chain system consisting of the supplier, buyer and customer, where the buyer corresponds to a wholesaler, and analyze the affection of (s, S) inventory policies for the supplier and buyer following customer order cancellations. We also determine the discount wholesale price of the supplier against the buyer in order to motivate the buyer to cooperate, because the expected profit of the buyer in the cooperative policy that maximizes the expected profits of the entire system is less than that in the independent policy.
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  • Takayuki KATAOKA, Katsumi MORIKAWA, Katsuhiko TAKAHASHI, Nobuto NAKAMU ...
    Type: Article
    2003 Volume 54 Issue 1 Pages 60-70
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    This paper deals with management issues and survival strategies for smaller regional wholesale businesses. In Japan, a traditional market price system has been used in the wholesale sector, and many smaller wholesalers take a cut of the profits. However, the distribution business in Japan has dramatically changed in recent years as international competition and information technology have grown rapidly. As the result, traditional management strategies are hardly any longer useful for most Japanese companies. Also, retail businesses have become very selective in choosing wholesalers under these conditions. Retailers have even begun to trade directly with manufacturers, forsaking the useful information held by the wholesalers. Therefore, a few selected firms have been distinguished as winners, and it is time for the many unselected firms to review their management strategies because it is obvious that their survival depends on how fast they are willing to conduct the review. As regional wholesalers are very important for manufacturers and retail business in Japan, they should review the business know-how and management resources that they have, and explore every possibility for new business, including business cooperation. In other words, first they must figure out their original strong points, then combine traditional Japanese business customs with the strong points possessed by global wholesalers. Some public organizations have tried to analyze the wholesale business through many kinds of questionnaires. However their traditional analysis is often limited to summarizing the numbers of answers for each question, and therefore, it is difficult to figure out the relationship among what wholesalers are dealing with and the groups of each category. It is very important to figure out the relationships and groups among them because the wholesale business structure has become complicated. In this paper, we first classify the types of operations based on answers regarding their management issues and new business strategies by introducing correspondence analysis. We then discuss the new survival strategies by considering the results of the correspondence analysis, traditional results, and also types of operations. We lastly discuss the new strategies of new businesses and coordination for smaller regional wholesale businesses.
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  • Shigeru YAMADA, Ryotaro MATSUDA
    Type: Article
    2003 Volume 54 Issue 1 Pages 71-79
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    Human factors affecting software reliability in the development process should be clarified and controlled to improve software productivity and quality. Several references have proposed for hypothetical models to describe the causal relationships among the human factors and the software faults occurring in development activities. However, there are few studies which can verify a human factor model through software development experiments. In this paper, we conduct an experiment to clarify human factors and their interactions affecting software reliability by assuming a model of human factors which consist of inhabitors and inducers. In this experiment, we focus on the software design review process which is more effective than the other processes in the elimination and prevention of software faults. For an analysis of experimental results, a quality engineering approach based on the signal-to-noise ratio is introduced to clarify the relationships among human factors and seeded software faults detected by review activities, and the effectiveness of significant human factors judged by the design of experiment is evaluated. As a result, applying the orthogonal array L_<18>(2^1×3^7) to the human factor experiment, we obtain the optimal levels for the selected inhabitors and inducers.
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  • Type: Appendix
    2003 Volume 54 Issue 1 Pages 80-81
    Published: April 15, 2003
    Released: November 01, 2017
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  • Type: Appendix
    2003 Volume 54 Issue 1 Pages 82-
    Published: April 15, 2003
    Released: November 01, 2017
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  • Type: Appendix
    2003 Volume 54 Issue 1 Pages App1-
    Published: April 15, 2003
    Released: November 01, 2017
    JOURNALS FREE ACCESS
    Download PDF (68K)
  • Type: Appendix
    2003 Volume 54 Issue 1 Pages App2-
    Published: April 15, 2003
    Released: November 01, 2017
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    Download PDF (68K)
  • Type: Appendix
    2003 Volume 54 Issue 1 Pages App3-
    Published: April 15, 2003
    Released: November 01, 2017
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    Download PDF (68K)
  • Type: Appendix
    2003 Volume 54 Issue 1 Pages App4-
    Published: April 15, 2003
    Released: November 01, 2017
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  • Type: Appendix
    2003 Volume 54 Issue 1 Pages App5-
    Published: April 15, 2003
    Released: November 01, 2017
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