The design of the physical layout is the most important issue to be considered in the early stages of manufacturing system design. Operating costs and system efficiency are significantly affected by material handling. Generally, the facility layout problem is to find an optimal layout with respect to minimizing material handling costs between departments. In most existing studies on the problem, the distance between departments is assumed to be the rectilinear distance between the centers of the departments. Those approaches ignore the existence of aisle and I/O points in each department. A new design methodology for the facility layout problem is presented in this paper. Our objective is to minimize the penalty for the redundant aisle areas and irregular shapes of departments, besides material handling costs. The material movements assume that they are transferred along the shortest aisles between the I/O points of those departments. In this paper, a new layout expression based on location matrix and some heuristics are proposed for determining aisle structure and I/O points. In the new layout expression, the I/O points of each department are located according to intradepartment material flows. We develop an improvement-type layout algorithm based on simulated annealing. In this paper, we propose a new design methodology for the facility layout problem that considers the aisle structure and I/O points of each department. There are three types of I/O points (U, L and I type) and they are decided to minimize the objective while maintaining access to the aisle. Experimental results show that our approach performs quite well for the minimization of material handling costs and the aisle areas.

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As product lifecycle becomes shorter, facility layout should be adjusted effectively to meet dynamic change in product mix under a given system capability. This paper formulates a dynamic layout problem with different shapes and areas of facilities and alternative processing routes to minimize the total cost consisting of work flow costs and facility-rearrangement costs over a given planning horizon T. Since the total work flow depends on the selection of processing routes for all products, our dynamic layout problem requires the determination of not only layout, but also a set of processing routes in each period. This paper decomposes the original layout problem into a work-flow decision problem and a layout-position decision problem. In the former problem, an approximate Closed Queueing Network model is employed for representing the capacity constraint, and the best processing routes are determined to minimize the total work flow under a given layout in each period. The layout-position decision problem is solved using GA with a static and dynamic phase. In the static phase, a one-dimensional array chromosome is first constructed by assigning each facility number to a locus one by one. Hamamoto's method is used for decoding each chromosome to generate a two-dimensional layout. The static GA provides the best S layouts in work-flow cost for each period. In the dynamic phase, T candidate layouts over the planning horizon are first picked from among the ST layouts, and are represented as a permutation chromosome with length T. The dynamic GA provides the best layouts over the planning horizon so that the total cost including facility-rearrangement costs is minimized. Some simulation experiments are demonstrated to show that the proposed method efficiently yields a near optimal layout with high accuracy.

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In the practice of patent management, decisions on which patents should be preserved and utilized and which to abandon are crucial from the viewpoint of technology management strategy. As technology innovations evolve at different speeds across industrial sectors, patent management strategies may differ between sectors such as information and communications whose technology lifecycles are rather short, and sectors such as medicine whose research and development periods are long. Such differences in patent management practice, however, have not been fully studied. One of the major reasons for this is the availability of patent management information; records of patent practices are usually confidential and kept within organizations. Thus, detailed information is rarely available for comparative studies across organizations and sectors. In this study, patent renewal information, which is available to the public from the Japan Patent Office, is used to estimate the structures of patent preservation periods in seven Japanese industrial sectors. Information of 2,520 patents, which were registered between 1982 and 1999, and renewed or terminated between 1998 and 2002, was retrieved. Because the observation period was limited, Kaplan-Meier estimators were calculated. Obtained term structures were compared across industrial sectors. Possible factors that might have caused the difference were discussed. Pareto distribution, which had been assumed in previous studies for returns to patents, was shown not to be applicable for the above Japanese industries, while lognormal distribution was suggested.

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This paper discusses the optimal control problem of a remanufacturing system with stochastic variability in the demand rate. We consider two types of inventories. One is the actual product inventory in the factory, while the other is the virtual inventory that is still in use by the consumers. We also consider the multiple classes of product lifetime at the virtual inventory level. The system is formulated into a Markov Decision Process (MDP) to minimize the expected average cost per period. The MDP is a class of stochastic sequential processes in which the reward and transition probability depend only on the current state of the system and the current action. The models have gained recognition in such diverse fields as engineering, economics, communications and so on. Each model consists of states, actions, rewards and transition probabilities. In this study, the state of the remanufactuing system is defined by considering the levels of both inventories. The cost function is composed of various costs such as the holding cost, backlogging cost and other manufacturing costs. We obtain the optimal production policy that minimizes the expected average cost per period using the Policy-Iteration Method. Numerical results provide insights on the effects of the various conditions on the optimal policy. Finally, we consider four scenarios and discuss the optimal policy in each case.

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A circular connected-(r,s)-out-of-(m,n):F lattice system is a two-dimensional version of a circular consecutive-k-out-of-n:F system. This system consists of m×n components arranged in a cylindrical grid. Each of the m circles has n components, and this system fails if and only if there exists a grid of size r×s with all failed components. A circular connected-(r,s)-out-of-(m,n):F lattice system may be used in reliability models of "feelers for measuring temperature on reaction chamber" and "TFT (thin film transistor) liquid crystal display systems with 360° wide area." Malinowski and Preuss (1995) and Yamamoto and Miyakawa (1996) independently proposed recursive algorithms for the reliability of a circular connected-(r,s)-out-of-(m,n):F lattice system based on the same idea. Recursive algorithms are effective when the system size is small or moderate, much more computing time and memory capacity are needed as the system size, especially n, becomes larger. Therefore, an efficient algorithm is needed for the reliability of a circular connected-(r,s)-out-of-(m,n):F lattice system when the system size, especially n, becomes large. In this study, we propose a new recursive algorithm for the reliability of a circular connected-(r,s)-out-of-(m,n):F lattice system. For evaluating the proposed algorithm, the orders of computing time and memory capacity are given. Furthermore, we carry out a numerical experiment to compare our proposed algorithm to the preceding algorithm. The results indicate that the proposed algorithm is an effective algorithm for systems with large n.

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In short, the features of product development activities (especially, at the conceptual design stage) are that most of them depend on each engineer's experience and are very flexible. On the other hand, most product cost (about 70%-80%) is fixed at the conceptual design stage. Therefore, it is expected that the efficiency of design management can be increased if it is possible to establish an effective method to evaluate each product design concept at the upstream stage of design. In this paper, we are going to introduce a method with a group utility function as a consensus- based design evaluation method to effectively select a promising design concept at the upstream design stage where a quantitative evaluation for technical activities is difficult to be applied. We use absolute measurement- type AHP (Analytic Hierarchy Process) to determine concrete utility functions. We actually applied the proposed evaluation method to a real project for developing the spindle unit of three-dimensioned modeling machine at R Company as an example of real product design in a task force- typed project. As a consequence, we verified its effectiveness as a design evaluation method.

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