This study offers suggestions that may clarify the relations between innovation and a country’s national character, and help design solutions to constantly shifting social problems at the individual and organizational level. Specifically, it calculates a signal-to-noise ratio by using the global innovation index （GII） published by the World Intellectual Property Organization （WIPO） to indicate the state of innovation in each country as a signal and classifying national characteristics as factors that can and cannot be controlled at the national level. By use of this metric it was possible to show that the actions needed to raise the GII differ according to national character. This study accordingly offers countries or organizations suggestions for policy design.

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Thermal mass flow controllers are used in the semiconductor manufacturing process. A thermal MFC has three main components: a thermal mass flow sensor, a laminar flow bypass, and a flow control valve. To obtain a flow rate and response characteristic of high accuracy and low variability, it is particularly necessary to improve the stability of the thermal mass flow sensor. In the development of a new thermal mass flow sensor, quality engineering techniques were applied to a series of processes: parameter design was applied during the development process, production parameter optimization was applied to reduce variability in the production process, and Mahalanobis-Taguchi methods were used to optimize zero stability inspection. Three results were obtained:（1） robust sensor characteristics relating mass flow to sensor output;（2）low-drift zero stability by optimization of production parameters; and（3）optimal inspection by MT methods, using quickly obtained data.

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When high-performance liquid chromatography（HPLC）is applied to multicomponent medicines, quality is quantified by the use of waveform patterns and the Mahalanobis-Taguchi system offers an effective means of making pass/fail decisions. Incorrect decisions have posed a problem, however, because of the wide tolerance ranges of multicomponent medicines, and because of external factors that cause unavoidable scatter in the results of HPLC analysis. We have therefore studied methods of creating a more robust unit space by building scatter into the unit space so that the pass/fail decisions are more immune to scatter and tolerance effects. Two such methods were studied: in one, the unit space was created from data that included analytic scatter generated by random numbers; in the other, principal component analysis and Cholesky decomposition were applied to data having the same factor-to-factor correlation coefficients and corresponding to the passing tolerance range. These methods were shown to be capable of creating unit spaces with improved discriminatory power that were robust with respect to the above unavoidable sources of error.

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