Success factors for demonstration projects of small-scale stationary fuel cells in residential buildings

Worldwide small-scale micro-CHPs account for the largest share in the fuel cell market by units of installation (not by installed power output). Notably, the Japanese Ene-Farm program is responsible for over 400.000 micro-CHP fuel cell installations (until the end of June 2021). This is the largest worldwide deployment program and it reflects the long- and outstanding commitment of both the Japanese government and the Japanese industry to form a ‘Hydrogen Society’. In Europe, the situation is entirely different. European projects like PACE financed by the European joint undertaking for hydrogen and fuel cells give a positive impulse for fuel cell based micro-CHP, however it has to be judged as insufficient for a market transformation measure. Presently, only Germany, notably by the KFW433 program, is providing frame conditions for a rollout of fuel cell based micro-CHP systems. This article analyses the success factors for the implementation of Ene-Farm systems in Japan. It compares the different frame conditions of Japan and European countries like Austria and discusses the question whether an Ene-Farm project based on the Japanese success factors could be replicated in Austria. On a bird’s eye, a European perspective will be derived from the analysis.

loyalty of workers to industrial organization

The differences in roles between individuals in Western factories and in Japanese factories - the ways in which individuals are given responsibility and authority, what rewards are given, and behaviors are rewarded - have a close relationship with the differences between their two cultural backgrounds. Japanese industry has for decades coated the top of a very and once feudal society for several centuries. The loyalty of workers to industrial organization, the paternal style of motivating and paying workers, the deep involvement of the company in all things which were to the eyes of the workers' private affairs - all of these had something in common with Japanese pre-industrial social organization. This equation does not underestimate the massive changes that have taken place in Japan during its industrialization period. Japan has changed enormously; and the changes continue. However, if the study of industrialization in Japan is to be relevant for the study of economic development in other Asian nations, then the nature of the changes that have occurred must be well understood.

Salary scale and the diversity of wage systems

In any society or group, the behavior and manner of acting that are highly rated can be estimated based on the level of appreciation given by the group to that level of behavior. This reward system will be studied to show the kinds of behavior group members are expected to get by the group and the kinds of behavior that - through the reward system - will be strengthened and perpetuated in the group. The study of the wage and incentive systems of Japanese factories revealed very well the differences between Western industry and modern Japanese industry. The study also showed both the types and magnitude of the differences that underlie attitudes and behaviors that distinguish modern industry in Japan from that in the United States. In the following discussion, the wage system in one factory will be examined in detail to illustrate the particular central trend that appears in all studied factories. Since the monetary wage system for work performed is only a part of the entire wage system, it will also examine the general pattern of non-monetary benefits, welfare efforts, incentive programs for workers, using specific plans and costs of a particular factory.

Homogenization of Japanese Industrial Technology From the Perspective of R&D Expenses

The aim of this paper is to discuss the reasons for the decline in the profitability of Japanese R&D from the perspective of in-house R&D efforts. Focusing on changes in the allocation ratio of in-house R&D expenses by industry from 1972 to 2017, technological structure changes in the Japanese industry during that period are empirically analyzed. Based on the analysis, the technological structure of the Japanese industry has been consistently moving toward homogenization since 1972. Homogenization is mainly directed toward the related technical fields of automobiles and information and communication machinery/equipment/electronic parts, which are the main industries that currently lead the Japanese economy. While the types of technical knowledge possessed by the Japanese industry are decreasing, there is a lack of R&D activities that will create new products and markets and increase the pie of the Japanese industry or greatly promote the metabolism of technology of the entire industry.

Calibration procedures for torque measuring devices by using a reference type torque calibration machine at NMIJ

NMIJ / AIST has been disseminating the national torque standard to Japanese industry by using deadweight type torque standard machines (DWTSMs). In general, DWTSMs can generate more precise torque than other types of TSMs. On the other hand, the calibration takes much longer time than others. One possible solution is to use a reference type torque calibration machine (RTCM). RTCMs have been developed in some national metrology institutes (NMIs). We have started the development of the first RTCM in the range of 100 mN · m to 10 N · m. In this study, we developed the automatic calibration system of the RTCM and investigated the calibration procedures for a low nominal capacity torque measuring device (TMD). It was found that the calibration could be realised by the RTCM, compared with the reliable DWTSM of rated capacity of 10 N · m at NMIJ.

Guidelines for Quality Assurance of Machine Learning-Based Artificial Intelligence

Significant effort is being put into developing industrial applications for artificial intelligence (AI), especially those using machine learning (ML) techniques. Despite the intensive support for building ML applications, there are still challenges when it comes to evaluating, assuring, and improving the quality or dependability. The difficulty stems from the unique nature of ML, namely, system behavior is derived from training data not from logical design by human engineers. This leads to black-box and intrinsically imperfect implementations that invalidate many principles and techniques in traditional software engineering. In light of this situation, the Japanese industry has jointly worked on a set of guidelines for the quality assurance of AI systems (in the Consortium of Quality Assurance for AI-based Products and Services) from the viewpoint of traditional quality-assurance engineers and test engineers. We report on the second version of these guidelines, which cover a list of quality evaluation aspects, catalogue of current state-of-the-art techniques, and domain-specific discussions in five representative domains. The guidelines provide significant insights for engineers in terms of methodologies and designs for tests driven by application-specific requirements.

Operational Performance of Electric Power Firms: Comparison between Japan and South Korea by Non-Radial Measures

This study compares the electric power sectors between Japan and South (S) Korea. Both nations have been under a global trend of deregulation. To assess their progress due to industrial change and technology development, we use Data Envelopment Analysis (DEA) as an assessment tool that enables us to evaluate the level of simultaneous achievements on economic and technological measures, so assessing the degree of holistic development. DEA has been widely applied for performance assessment in the past decades. In this study, the method compares electric power firms by their operational efficiencies. To compare their achievements, it is necessary to develop a new type of DEA application for performance measurement. The proposed approach adds two analytical capabilities. First, the approach needs to handle “zero” in a data set and then restrict multipliers (i.e., weights among inputs and outputs) without any prior information to increase our empirical reliability. No study has simultaneously explored the two capabilities in DEA. Using the proposed method, our empirical study identifies two findings. One of the two is that the electric power industry of S. Korea outperformed that of the Japanese industry in the observed periods (2014–2018) because the Japanese power sector still suffered from an occurrence of the Fukushima Daiichi nuclear plant disaster which occurred on 1 March 2011. However, the difference has been gradually diminishing because the Japanese electricity industry has been gradually recovering from the huge disaster. The other is that the S. Korean power industry has been in a descending trend because the nation has shown technical regress as a result of inconsistent technology development (e.g., shifting its R&D: Research and Development) focus from electrical engineering to chemistry). The former R&D area is essential in maintaining the technical level of S. Korea′s electric power industry.

A Model of Sales and Operations Planning: Example of Parameters Used and Decision-Making Process in a Japanese Industry

Many companies are facing a constant need to develop coordination between operational functions to quickly respond to customer requests. Thus, many practitioners are resorting to an established and integrated business management methodology, the Sales and Operations Planning (S&OP). The impact of the S&OP on operational performance was significantly demonstrated in many studies. However, it turns out that the theoretical studies made differ from what is actually applied, in addition to several parameters that are considered in the calculations especially with regard to Japanese industries. So, how is S&OP operated in this industry? What are the different calculation parameters used? and how are the results obtained and analyzed?In this paper, we will first present a short literature review of S&OP and its role and benefits. Then, we present a model of S&OP used in a wire harnesses Japanese industry. The goal is to show first a concrete example, where we present the various parameters considered in the calculations, and then we will explain how the resulting graphs are analyzed by managers and what could be done as corrective actions in case of gap existing.