Manufacturing companies have to create new customer value by racing against other companies to develop new businesses, new products, and new services in the global market. That said, it is required of their high quality and short lead time to increase the production rate. Additionally, the information volume which is dealt with inside the manufacturing companies is increasing by the use of digital technologies utilized in engineering activities such as 3D printers, BIG DATA, IoT, AI assets, and others. Accordingly, many manufacturing companies are continuously making efforts to improve their innovation and Kaizen abilities. They are doing that for reducing the manufacturing lead times that include not only the physical lead time, such as the product assembling time in direct operations but also in the case of information lead time, the document creations in indirect operations as well. This study focuses on indirect operations that employ dealing with information processing in the office. The operation which deals with information is different from the one that deals with physical products. Therefore, in this research, the characteristics of indirect operations which deal with information are made clear. Second, the behavior of indirect operations ’lead time is made clear by the use of simulation models. Third, the structural equation for the indirect operations’ lead time is set by the simulation results. Fourth, in order to create a straightforward flow of information, a conceptual picture of Quality Function Deployment (QFD) which utilizes job function deployment is also proposed by this study.

Forecasting water demand is very important for pure water reservoirs because the amount of water supply to water supply stations cannot be changed frequently according to the variation in demand. The aim of this study is to propose a forecasting method for water demand applicable all over Japan. In our previous studies, we proposed three forecasting methods and one correcting method for water demand using data from four Japanese prefectures. These forecasting methods adopted the following three processes: (1) multivariate regression analysis, (2) using multiple year data of the amount of daily water supply, and (3) correcting the obtained multivariate regression formula by single regression analysis. The results showed that the proposed forecasting methods ’precision was approximately 2%. However, the forecasting precision could not be improved further. Thus, this study focuses on correcting the method and forecasting error. In our previous studies, the correcting method that was proposed by using a single regression analysis consisted of the following three steps: (1) temporary forecasting values were calculated by obtained multiple regression formula using daily water supply data close to the forecasting day; (2) correcting coefficients were estimated by a single regression analysis using the relation between temporary forecasting values and actual amounts; and (3) the multiple regression formula was corrected using the obtained correcting coefficient. Thus, the proposed correcting method was very simple in our previous studies. In this paper, the factors of forecasting error are estimated based on the relationship between the forecasting and actual amounts. Then, the new correction method is examined using these factors.

At present, because of diverse user needs, types and construction of products tend to be fractionated and complicated. Material handling costs at large-scale production facilities, regarded as an important factor, are said to account for about 15%–75% of all factory costs. Therefore, to achieve higher efficiency and lower production costs, conventional single floor buildings are being replaced by multi-floor buildings. Recently, when a new factory is designed, a few circular buildings are included in addition to rectangular buildings, which are still used frequently. Nevertheless, little development of multi-floor layouts has occurred for circular buildings. As the number of work sites at factories increase,the number of combinations of work sites (factory layout designs) is expected to increase exponentially. Therefore, a longer time is necessary for precise solutions using mathematical programming. Finding an optimal solution within a realistic calculating time is difficult. Therefore, to obtain a nearly optimal layout that approximates the best solution with high accuracy, some optimization method (meta-heuristic) must be used. For this study, a technique to produce a layout for a rectangular building and a circular building for a multi-floor factory using genetic algorithms (GAs) is used as one optimization method. The building shape is then subjected to comparative examination. Productivity values obtained according to the building shape, as calculated by the total material handling costs between work sites, are compared using numerical experiments to clarify the effectiveness of layout techniques for rectangular buildings and circular buildings.