Molded photoluminescent materials materials that resist degradation and deliver long, high afterglow are needed for use in commercial products. Ichikawa, Yamamoto, et al. used a light meter to select optimal molding conditions,and succeeded in finding highly robust molding conditions that reduced the necessary amount of photoluminescent material and thereby the cost. Their light meter, however, had a narrow measurement range, making it difficult to evaluate the uniformity of the afterglow over the entire surface of the luminescent body. The goal of the present study was one-step measurement of the entire luminescent body. In a first experiment, a digital video camera was used to evaluate a local part of the luminescent body. Since parameter design was in its third phase, high measurement precision was required. Conditions that improved the precision were found by focusing on the temperature characteristics of the digital video camera and the initial state of the luminescent body. These conditions were then applied in an L18 experiment that succeeded in obtaining a reproducible gain and identifying a superior set of molding conditions. Repetition of the measurement under identical conditions showed the measurement of the luminescent body to be very precise.
A study was carried out concerning the toxicity of chemical substances, using the error root mean square method to estimate the toxicity of new chemical substances before trial production. It became possible to discriminate substances of high toxicity from substances of low toxicity by comparing the estimated distances obtained by this method, and as a result, to make the development process more efficient and reduce needless prototyping costs. The study also succeeded in obtaining design information from itemized diagnoses of the individual substances, and in finding ways to improve the parameters unique to the substances. The study showed that quality engineering enables toxicity to be estimated at an early stage in the development of chemical substances, and that quality engineering can be used to avoid chemical toxicity problems.
Systems that generate electricity from renewable energy sources have become a focus of interest, and photovoltaic(PV) systems are being rapidly introduced. A particular problem of PV renewable energy systems is that their output power fluctuates greatly according to weather conditions. Connecting large numbers of unstable power generators such as PV systems to the power grid could compromise the quality of the power supply. To prevent degraded power quality, it is importallt to develop methods of predicting how constantly fluctuating power sources will change. In this paper, the MT system (T method-1) is used to predict electric power one hour in advance from time-series data obtained from meteorological observations. When the method was tested against actual observational data recorded at one-hour intervals, it was confirmed that the selection of the periods covered by the unit space and the signal data, the sizes of the hourly changes in feature variables, and transformations of these variables all contributed to improving the predictions.