In many practical situations, the states of the systems and their components are assumed to take more than two different levels, ranging from working perfectly to complete failre. In a multi-state system, both the system and the components are allowed to be in M+1 possible states, where M is a positive integer that represents the system or components in a state working perfectly. while zero is a state of complete failure. Therefore, the multi-state system reliability model provides more flexibility for the modeling of equipment conditions. In this study, we discuss the multi-state consecutive-k-out-of-n:F system. This system is applicable to the quality control problem for batch products, preventive maintenance problem for oil pipeline systems, and similar items. For the consecutive-kout-of-n:F system, the optimal arrangement problem, where the solution is obtained by the arrangement of components with maximum system reliability, is one of the most important problems in this system. So, we consider the optimal component arrangement for a multi-state consecutive-k-out-of-n:F system that has the maximum expectation values for the system state distribution when these components are arranged in positions in the system. The multi-state consecutive-k-out-of-n:F system consists of ii components arranged along a linear path. As the number of components n increases, the number of calculations to obtain the exact solution to the optimal component arrangement problems becomes large. Therefore, in this study, first, we propose an algorithm for obtaining the exact solution for optimal arrangement problems in multi-state consecutive-k-out-of-n:F systems. It is possible to solve the problems if the expectations for all arrangements are calculated. However, we have to calculate the expected values for many arrangements. We propose an algorithm, which is based on the branch-and-bound method, to obtain optimal solutions for such problems and remove operations that are not useful via certain properties of the arrangements. Next, we evaluate our proposed algorithm in terms of the computing time. The results of the numerical experiments show that the proposed algorithm is more efficient for systems where the number of components a is large.

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In this paper, we consider the effect of lot splitting, which is the procedure of splitting a production order into smaller sub-lots that are free to move independently through stages of the manufacturing process. In this lot splitting, there is a trade-off relationship between the material movement and the lead time. We analyze the effect of the lot splitting in simulation experiments under the model of an open shop environment, where there are no restrictions on the order in which the operations of a job are performed. Generally, the average lead time to manufacture the products becomes shorter as a result of lot splitting of each job. However, we show that there are some cases where lot splitting leads to disadvantages, such as when too much lot splitting increases the average lead time when the machine utilization is high and/or the setup time to process the material is relatively long in proportion to the processing time of the jobs. In addition, we propose a new material handling rule, called the time-based rule, which can create the best balance of shorter lead time and less frequent material movement simultaneously. In this time-based rule, we assume that the processing completion time of each production lot is known using radio frequency identification (RFID) to monitor the production progress. The effectiveness of the proposed method is verified in the simulation experiments.

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This paper discusses 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 the part inventory must be kept equal to the part consumption for the maximum time interval. Therefore, development of a schedule to reduce the total amount of the inventory of each part to a minimum is required. In previous studies, an approximate algorithm was proposed. In this paper, a revised method is developed to obtain a better solution. Moreover, using numerical examples, the properties of operation of the lot production lines controlled by the schedule based on the newly developed method are analyzed.

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To evaluate driver responses during the process of perception, the response time from the point when subjects detect stimuli presented in their field of view was investigated from the viewpoint of human cognitive reliability. The period of time required for a subject to stop the car when an obstacle appears on the road is obtained through conducting a driving simulation braking experiment. Using the human cognitive reliability model, we evaluated the effect of several performance shaping factors (PSFs), such as experience, stress level and quality of the interface device, on response time. We found that response times for perception, cognition and action of the driver corresponded to rule- based, knowledge-based and skill-based behaviors. It was shown that the effect of the PSFs yielded response times that can be predicted using the proposed human cognitive reliability analysis.

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Over the last few years, there has been remarkable growth in the diversity of products and services offered to customers across all industries. With this increased choice of products and services, the bargaining power of buyers is increasing. Companies are finding it more difficult to differentiate themselves based on the products and services they offer to customers. Customers are in the position where they can choose from a range of products and services from more than one company. This shift of power from company to customer forces companies to focus on customer retention and loyalty through improved customer experience rather than product and service offering. The objective of this paper is to introduce a framework called the enhanced customer experience framework (ECEF) which aims to enhance customer experience through improved business processes. This paper will also attempt to critically evaluate the ECEF by discussing the advantages and disadvantages associated with the methodology followed. The ECEF can assist managers to satisfy customer needs. By designing business processes to convey products and services according to the needs of the customer, companies will be able to benefit from the strategic competitive advantage of customer loyalty.

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This paper proposes an integrated production and inventory cycle over an entire whole green manufacturing supply chain consisting of: multiple-raw materials suppliers (tier-2 suppliers), multiple parts suppliers (tier-i suppliers), a manufacturer, multiple distributors, multiple retailers and a third-party product collector. In the whole manufacturing supply chain, tier-2 suppliers supply raw materials to tier-i suppliers producing parts. Parts from tier-i suppliers are then supplied to a manufacturer who manufactures and assembles parts into finished products. Then, the finished products are delivered to distributors who distribute them to retailers. Since each player wishes to minimize total cost for itself and can supply multiple raw materials and parts, there is a need for coordination among players in the supply chain. The coordination used in this paper is for both centralized and decentralized decision processes. Owing to environmental and ecological consciousness and responsibility as a result of increasingly rigid environmental legislation and growing environmental concerns in recent years, this paper also considers some parts of used products being reused in new products. A mathematical model with multiple decision variables is developed. A numerical example is presented and results discussed.

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The quality of the exterior colors of automobiles has become a major aesthetic factor (preference) influencing the car buying process. Accordingly, in this study, we introduce the Automobile Exterior Color Design Approach Model (AECD-AM) and verify the model's effectiveness. In creating the model, the authors utilize information from their own research on "Kansei (emotional) engineering" applied to automobiles. First, the study determines the four elements most desired by young people in exterior colors (classy, luxurious, dignified and sporty). Next, we determine the six elements of color (hue, luminosity, intensity, shine, opacity and graininess) that influence young buyers the most. Correspondence analysis is then applied with the aid of statistical science (multivariate analysis) in order to correlate the young people's preferences with the color elements, enabling the influence of each color element to be determined. Based on these findings, the model has subsequently been applied in exterior color development (paints and painting methods), demonstrating significant results.

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Demand is growing for design of services and products that provide affective experiences. Recent studies have indicated people tend to enjoy services or products that can engender affects (emotions, moods and feelings). A number of studies have investigated the relationships between design parameters and human affects, while some others were concerned with how to design affect-eliciting services and products. However, few studies have specifically examined what the essential elements that elicit human affects may be. The purpose of this study is to therefore find general factors contributing to the generation of human affects. First, free narrative descriptions about things or experiences that could elicit affects are collected from participants and analyzed to extract the elements contributing to the generation of human affects. Second, a questionnaire-based investigation was conducted to validate the elements extracted. Factor analysis was employed to investigate the factor structure of the extracted elements. Results showed that the extracted affective elements could be grouped into eight factors, named "affective factors." Meanwhile, the relationship between affect and affective factors was validated using correlation analysis. The results of this study suggest possible ways to elicit human affects while also serving as a reference tool for designers of products and services.

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