In the development of the new product and the management of technologies, it is important to make decisions based on the information about technological trends, such as patents. The relationship between the application range and field of technology has become complicated due to the use of increasingly sophisticated technologies in recent years. Along with this, knowledge sharing between decision-makers and engineers has become increasingly difficult. Under these circumstances, there is a need for an efficient tool capable of supporting knowledge sharing among engineers and managers whose expertise are in different areas. The purpose of this study is the knowledge extraction of patent data through constructing a text-mining patent map using the random forest methodology. By extracting the knowledge from the results learned using the technological information obtained through random forest as the supervised signal, we have constructed patent maps that take the relationships between technical fields into consideration. The method we propose creates a patent map by combining two-dimensional kernel density estimation and multi-dimensional scaling based on a similarity matrix calculated applying the internal components of the random forest. We also deal with calculation results of non-negative matrix factorization as a random forest input, thereby avoiding the vulnerability of the random forest noise variables. Non-negative matrix factorization is useful for interpreting the important variables extracted in the random forest. In the experiment, we confirmed the behavior of the method proposed using Japanese patent data.

In the production field, savings in labor and manpower are being achieved by means of automation and mechanization of processes. However, several operations still partly depend on manual work in assembly, inspection, and equipment maintenance processes. In particular, assembly operations for large products force workers to match their postures to the work positions of the products and equipment. Maintaining and repeating such awkward postures increases the workload and causes lower-back pain and upper-limb disorders. To evaluate work posture in the production field, methods based on observation by analysts are often used. Representative methods include OWAS, RULA, and REBA, all of which are readily available. However, results depend on the analyst's skill level and evaluation of the worker's posture is time-consuming. In this study, we propose a method for easily estimating posture during assembly work. An experiment was conducted to clarify the effects that assembly height and direction have upon work posture, and the evaluation value of the work posture was determined under each condition based on OWAS. Then, a table based on OWAS was constructed incorporating the height of the worker and height and direction of the assembly parts as inputs for estimating work posture. Furthermore, we verified the accuracy of this technique. The correlation coefficient between observation by an analyst and the proposed method was 0.77, and the estimation accuracy was 61.2%. This result indicates that the proposed method is valid.

To enable services to be provided continuously at the time of a disaster, organizations have to prepare some countermeasures in the form of a business continuity plan. Before planning the countermeasures, it is necessary for the organization to evaluate its current capabilities based on its available resources and intricate interdependencies in order to estimate the effectiveness of possible countermeasures. Using the concept of a dependency graph, a model is constructed to calculate the amount of services based on amount of available resources. The node and edge categories are classified to determine the structure of the proposed model. Next, we establish variables, and finally a formula for evaluation is created. The model proposed is applied to medical services and the capabilities of a hospital are measured. In conclusions, efficacy of this model is confirmed by simulation using actual data in a hospital. Using this model, effectiveness of countermeasures can be grasped quantitatively.

In the area of materials stock-flow analysis, the cumulative graph is an effective method to visualize and analyze flow patterns and embedded problems, leading to identifying ways to improve material flows in production and service systems. However, since the conventional approach of cumulative flow graphs assumes a tandem flow shop-type one-way flow, the graph cannot be used in complicated flow patterns where each stage is comprised of parallel processes and materials flow back-and-forth between these stages. This paper proposes a method to apply a cumulative flow graph to the case of such parallel flow pattern, where a single stage is comprised of a main system and a subsystem, and materials repeatedly flow between these systems before finally flowing out from the process. For the purpose of identifying fundamental problems in the material flow, the method proposed focuses on depicting stock quantity in each system on the cumulative flow graph. The paper finally applies the method proposed to the actual case of a physical distribution system comprised of the main and secondary warehouses, and the validity of the method proposed is discussed and clarified using practical examples.

In recent years, short-line production, which are allocated many work elements in a process, has become the mainstream in manual assembly bases in order to cope with multi-product production. In these production lines, many examples are seen in which the target productivity which is set at the process planning cannot be achieved because these lines cannot perform with the tact time and line balance which is assumed at process planning. It is indicated that the reason is because allocating many work elements in a process causes process time extension.

Therefore, this study analyzed real manual assembly lines of major home appliance based on overseas, and observed that there is 1.8 times process time extension between net process time and process time which is set at the process planning. Moreover, it was observed that the process time extension was affected by the number of work element in a process. Then, this study proposed a method to estimate process work time considering the number of work element in a process.

In recent years, one of the problems in corporate management is that information system maintenance costs are higher development costs. One of the causes of this problem is inquiries from customers. It is difficult to predict occurring the timing of inquiries from customers. Therefore, it takes much time to respond to customers' inquiries, especially when said inquiries come after operators have been arranged and equipment has already been prepared. There are studies of factors that lead to inquiries from customers, but there are no studies regarding the timing of inquiries. In this study, factors related to the response time to customers are examined by statistical analysis. From these examinations, a prediction model for the timing of customer inquiries from customers is proposed.