This article provides a chronological account of the evolution of the concept of product warranty and its development over the four millennia to its present state at the dawn of twenty-first century A.D. This study examines how the concept of product warranty originated and illustrates how this concept was an integral element of accepted business practices in commerce and trade over the ages in almost all civilizations spanning the entire globe. The civilizations include the Babylonian and Assyrian civilizations of twenty-first century B.C., the Roman era of the fifth century B.C., Bavarian rule at the start of the Christian era, earlier Jewish period of the second century A.D., Hindu period of the fifth, Islamic era of the eighth, Russian period of the early tenth, church rule of the medieval times, customs of the English borough, and ultimately the post-industrial era of consumerism and today's times of warranty legislation.

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The highest balancing efficiency in robot work is attained by the minimum number of robots. When the minimum number of robots is not attained by the cycle time, it can be attained by increasing the cycle time. But increasing the cycle time leads to a rise in cost because the robot functions increase. This study, therefore, searches for a work configuration where the number of robots times cost is at a minimum. As most practical factories engage in manufacturing multiple products, it is searched from the viewpoint of all products manufactured in robot line of a factory. As a result, we propose how to obtain minimum cost using cycle time and the number of robots, or namely, the optimal economic assignment. Finally, the procedure for creasing the optimal economic work assignment is presented.

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In this paper, a new layout expression based on the location matrix and some heuristics are proposed for the determination of aisle structure and I/O locations of each department in a facility layout problem. The proposed genetic algorithm-based algorithm finds multiple solutions along the Pareto optimal frontier. The objective here is to minimize (1) material handling cost and (2) building area. The material movements assume that they are transferred along the shortest distance aisle between the I/O locations of those departments. The results of computational experiments show the effectiveness of the proposed algorithm.

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This paper discusses a supply chain for harvesting and delivering fresh agricultural products from a single farmland to multiple markets under the condition of periodical flowering. We formulate a two-phase optimization model for selecting the optimal combination of transportation methods to maximize the total revenue obtained from the harvesting-delivery process of fresh agricultural products, provided that the products are supplied to each market in proportion to market size under a selected combination of transportation methods with corresponding delivery lead-times from a single farmland to multiple markets. We propose a graphical method for determining the optimal combination of transportation methods that includes flexibility for possible changes in prices of fresh agricultural products in multiple markets, using a multi-objective decision-making scheme to maximize the total sales income and minimize the total transportation cost. Numerical examples with real data on transportation costs available in Indonesia are demonstrated to show the effectiveness of the proposed method.

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In this paper, the similarities and differences between Japanese Cell Manufacturing (JCM) and Cellular Manufacturing (CM) are compared in regard to the following four points : 1) implementation changes, 2) cell features, 3) advantages and disadvantages of implementation, and 4) mechanisms behind the advantages and disadvantages. The comparison made it clear that while some similarities exist in cell features and advantages and disadvantages of implementation, JCM and CM are completely different in terms of the implementation changes and mechanisms behind the advantages and disadvantages. CM is implemented as a result of shifting from a job shop to a flow shop, whereas JCM is implemented as a result of three changes in a flow shop. Based on these findings, it is possible to conclude that JCM is a new type of manufacturing system that should be considered separately from CM. However, existing studies that offer complex discussions of the similarities and differences of the two systems tend to focus on cell features and advantages of implementation. The fact that some similarities can be found in these two points could be the reason why JCM and CM are often considered to be the same.

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In this paper, we propose a new approach to facility layout problems. Almost all manufacturing systems involve random elements such as variable inter-arrival times of orders and variable processing times, which reduce manufacturing efficiency. For such systems, instead of minimizing the traditional materials handling cost. our aim is to find an optimal layout that absorbs the randomness as effectively as possible and results in the best manufacturing efficiency. We call this type of layout problem a "Stochastic Facility Layout Problem (SFLP)." We choose the manufacturing lead-time as the performance measure, formulate an optimal facility layout and buffer space allocation problem for job-shop type production systems in which relatively largesized parts are transferred by Automated Guided Vehicles(AGVs) and processed via variable routes in First-Come-First-Served (FCFS) manner. Our approach is based on an approximate Markov analysis using a decomposition technique for evaluating the lead-time and a genetic algorithm for searching the optimal combination of buffer space allocation and layout.

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The vehicle routing problem with multiple use of vehicles is a variant of the classical vehicle routing problem in which vehicles can be used several times during a working day. We propose a method to determine the lower bound of this problem by solving the degree-constrained minimum γ-tree problem and the 0-1 knapsack problem. We also propose a method to determine a near-optimal solution to the problem by successively decreasing the difference between the upper and lower bounds. Numerical experiments are carried out to verify the effectiveness of the proposed method.

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