A combination of logistic analysis and scanner data was the mainstream of marketing studies during the 1980 s and the 1990 s. In recent years, however, maintaining customers has been taken very seriously by lots of organizations, because consumers are beginning to build original values on brand choices. Consequently, in addition to the examination of short-term fluctuation, such as sales promotions, the management of brand equity has become increasingly important. The brand switch model proposed by Nakajima (1998) is one of the studies that deals with brand loyalty. This model describes the state change of loyalty using Markov chain. Therefore, it can analyze the influence of loyalty on the brand evaluation without assuming a steady market. The purpose of this article is to construct a brand choice model from the viewpoint of brand loyalty. First, the state change of loyalty after purchasing is described based on Nakajima (1998). Second, the choice probability of each brand is expressed using traditional brand choice models. This proposed model makes it possible for us to understand the influence of loyalty on the brand evaluation and choice probability of each brand simultaneously. We expect this model to make a contribution to brand analysis from multiple angles and to the planning of marketing strategies.

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The CCC (Cumulative Count of Conforming) chart of which quality characteristic is the cumulative count of conforming items inspected before observing a nonconforming one has been discussed by several researchers, Bourke, Kaminsky et al., Nelson, Glushkobsky, and Xie et al. Moreover, Xie et al. have extended the CCC chart to the CCC-γ chart of which quality characteristic is the cumulative count of conforming items inspected before observing γ (≥2) nonconforming ones to detect more sensitively changes in the fraction defective p for high-yield processes. Recently, Wu et al. have presented a Synthetic chart that is an integration of the Shewhart-type charts, such as x^^- chart and p chart, and the CCC chart to have a higher power for detecting moderate process shifts in quality characteristics on Shewhart-type charts. Kusukawa and Ohta have presented the CS (Confirmation Sample)ccc-γ chart for detecting more sensitively small or moderate changes in p for both upward and downward shifts in high-yield processes. As a superior chart for high-yield processes, we present a new Synthetic chart for high-yield processes that is an integration of the CSccc-γ chart and the CCC-γ chart. In use of the proposed Synthetic chart, the quality characteristic is initially judged as either in-control or out-of-control, using the confirmation control limits of the CSccc-γ chart. If the process was not judged as in-control by the CSccc-γ chart, the process is successively judged by using the CCC-γ chart for conforming the judgement of the CSccc-γ chart. It is demonstrated through computer simulation that the proposed Synthetic chart is more sensitive in detecting small or moderate changes in p for both of upward and downward shifts in high-yield processes than the CSccc-γ chart by comparing the ANOS (Average Number of Observations to Signal) of the proposed chart and those of the CSccc-γ chart.

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As a feature of tool lifetime in a wear-out failure mode, it is pointed out that as the cutting speed slows, the lifetime lengthens and the variance becomes larger. In other words, the tool lifetime has a statistical feature that the expectation and variance of the tool lifetime change according to variation in the cutting speed. As a distribution including this feature, the log-normal distribution, which has the correlation of the expectation with the variance, is adopted. In determining whether or not a production lot of tool is accepted based on the mean time to failure (MTTF) of tool lifetime, we wish to provide the most effective sample size and the acceptance criterion for the specified producer and consumer risks. Then, in the design of reliability tests for assuring MTTF in the log-normal distribution, even if the log-nomal distribution is transformed into the normal distribution, the reliability test for assuring MTTF in the log-normal distribution sometimes cannot be designed in the normal distribution. Therefore, the objective of this article is to propose a procedure for designing reliability tests for assuring MTTF in the log-normal distribution employed as the distribution of tool lifetime, by using a chi-square approximation for log-normal distribution. Further, we also consider the optimum cutting speed in testing under the proposed reliability tests as an economical cutting speed in testing.

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We propose a new framework of facility layout problems which takes the production efficiency into account explicitly. In the classical framework of facility layout problems, layouts are evaluated only by the material handling cost, and any aspects as to how layouts affect the production efficiencies are not considered. In real systems, however, the layout of facilities do affect the production efficiencies such as throughput, lead time and so on. Thus, in general, there should exist the "best" layout which absorbs the variability involved in the system and attains the highest production efficiency. In short, our problem is to find the layout of facilities which results in the maximal production efficiency. We refer this type of layout problems as the "Stochastic Facility Layout Problem (SFLP)". In this paper, we present an example of SFLP which finds an optimal combination of the facility layout and the buffer space allocation to achieve the maximal throughput. In case when the physical size of a buffer space can not be ignored compared with the facility itself, allocating buffer spaces to a facility affects the distances between facilities. In such a case, the production efficiency (throughput, say) depends on both buffer space allocation and facility layout in a complex way. Our problem gives rational solutions for such a situation. Through this example problem, we discuss the merits and the demerits of SFLP compared with the classical facility layout problems.

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The analytic hierarchy process (AHP) proposed by T.L.Saaty is a method for decision making that takes into consideration uncertain situations or multiple evaluation criteria. In AHP, a decision maker gives values of paired comparisons between evaluation criteria and substitutive propositions. Saaty proposed the eigen vector method (EV method) to calculate evaluation values called weights of the substitutive propositions from a given pair-wise comparison matrix. On the other hand, logarithmic least square error method (LLS method) has been proposed. It is a technique that calculates weights of the substitutive propositions based on statistical theory. In the LLS, a linear logarithm model assumes an identical variance for noises and the logarithmic least square error method is applied to calculate the weights. This supposition seems to be useful in many practical cases. However, a pair comparative value depends on decision makers. In other words, there may exist the case such that "the pair comparative value between substitutive propositions A and B is more reliable than that between B and C" arise in practice. That is, when a paired comparison matrix is made, the reliability of each comparative pair may be different in the matrix. In this case, it is more suitable that we assume the noises with different variances in the log-linear model. In the conventional LLS, even if the reliability of each comparative pair is different in the matrix it cannot be used for the analysis. In this paper, we show a new method that takes into consideration the reliability of decision makers for each comparative pair value. We propose the weight estimation method of AHP based on a weighted least squares error method where weights represent the conviction of decision maker. If a decision maker can give a precise comparative pair value, then the proposed method is theoretically sound. Furthermore, from a simulation experiment, we examined the properties of the proposed method. We show that a better estimator than LLS can be acquired even if weights that are different from the right values calculated from true variances of noises.

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A new method of implementing process planning under a competitive environment is proposed for a single-stage multifunctional production system, such as a machining center. This system, named the "Dynamic Process Planning System", has a strategic decision function in order to overcome competitive factories. The main characteristic of the system with the strategic decision function is the ability to quickly change the process plan by analyzing the competitive data. In order to competitively machine workpieces as a product on a pallet under the minimum elapsed time criterion, the completion time of workpiece machining in one's own factory must be within that of the machining time of the competitor factory. To realize this idea, a hierarchical model consisting of four sub-systems with a strategic decision was developed under the minimum elapsed time criterion. This system implements the appropriate process planning, while adjusting the solutions of the following four sub-problems as needed by the decision maker : (Prob. 1) workpiece grouping and machining conditions, (Prob. 2) allocation of workpieces, (Prob. 3) sequence of machining operations, and (Prob. 4) pallet scheduling. These problems are connected with a hierarchical structure. Finally, actual use of the proposed dynamic process planning system is demonstrated as an example.

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This paper addresses the dynamic lot size scheduling problem for processing multiple items in a multi-stage production system so as to minimize the total cost, consisting of setup costs and holding costs, over the planning horizon under the constraint of shipment requirements. In this problem, there exists various heterogeneous decision features such as lot sizing, lot sequencing, dispatching and so on. We present a Lagrangean decomposition coordination method that enables us to simultaneously solve all of these decision features involved in this problem without specifying or awakening to them one by one. First, splitting the planning horizon into very small time slots, we denote a state of processing as to each item on each machine at the time slot by using a binary decision variable that takes the value of unity if it is processed, or zero if not. Second, dealing with the transition of the inventory state of each item and the time transition of each setup explicitly, we formulate the problem into a multi-dimensional dynamic optimization problem with constraints. Third, paying attention to the separable property of the problem and the existence of interaction constraints related to machine interferences and work-in-process inventory balances, we decompose the whole problem into item-based sub-problems to dissolve the curse of dimensionality. At the aim of guaranteeing the decomposability, problem formulation is made by the concepts of echelon inventory. Each sub-problem is reformulated into the dynamic programming of one dimension. The computational procedure consists of solving sub-problems for given Lagrangean multiplier values and coordinating those values, which is repeated until the interaction constraints are satisfied. Finally, we verify the presented method by solving an illustrated example.

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This study presents an analysis method for processes of reading printed advertisements in terms of acquired information quantity and strategy by use of eye tracking data. Acquired information quantity is evaluated on the basis of a combination of the following three indices : total reading duration, fixation duration, and number of fixations. Information acquisition strategy is elicited in the form of a reader's cognitive behaviour concerning how information about advertising claims was acquired. To extract these strategies, we categorize information in advertisements into 4 groups in terms of the claims involved as follows : Brand name, explanation of benefits, catch copy, and others. Each reader's strategy is classified into one of 11 categories (ex. wholistic monitoring strategy category, and so forth) on the basis of the most frequently observed adjacency pairs of information groups gazed at. A series of experiments was performed with thirteen female subjects in order to analyse the effects of television commercials (CM's) on the process of reading printed advertisements for the same product applying the proposed method. Self-reported data were also obtained to examine the relationship between the subject's reading process and her personal profile, e.g., interest in brands exposed in printed advertisements and daily attitudes towards advertising media. As one of the major results obtained by applying the proposed method, we could find evidence that the degree of matching between contents of printed advertisements and those of CM's may affect reading processes. We also reached another conclusion that subjects' daily attitudes towards advertising media may be one of the major factors for individual differences in reading processes. The results obtained seem to make a contribution to decision-making for effective media planning in practical advertising companies.

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The concern of this paper is to describe a participatory ergonomics method for work improvement (kaizen) in terms of ergonomics. Ergonomic implications of Participatory Ergonomics are : (1) to participate in group discussion on identifying the factors of workload and problematic causes in quality and productivity, (2) to find a solution to these factors, and (3) to secure the quality of working life. For this purpose, participatory ergonomics has the following program : (1) to organize two teams, "the project committee" consisting of managers of personnel, production engineering, production management, safety and welfare divisions as well as the labor union, and the working group consisting of supervisors and all quality circles. The former has the role of strategic planning of work improvement and budget planning for conduction work improvement. The latter perform surveys of detrimental problems happening in the workplace and proposes solutions to the project committee. Both teams first learn ergonomics concerning physiological/psychological characteristics of human beings and how to decrease the workload from the viewpoint of ergonomics. The working group surveys, for instance, the working postures alongside the production lines and seeks the ergonomic factors forcing these bad postures. They measure the energy expenditure for perform the work and find the ergonomic countermeasure to lessen the workload. It is of importance to lead the participatory ergonomic outcome to develop the tools concerning participatory ergonomics. Regarding the present paper, we have developed (1) the Sociotechnical System Chart, (2) Job Redesign Diagnosis Assessment, (3) Working Posture Assessment, and (4) WPA Measurement Kit. The Sociotechnical System concept is an integration of human side and technology side in production lines and it presupposes incorporation of human development potential as well as autonomy in the workplace. The stories of work improvement in Daikin (an air-conditioner maker), Mitsubishi Motors (an engine production factory), Nissan Motors, and Nissan Diesel (a truck maker) are described here.

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