Organisational learning model for utility asset management using knowledge engineering approach.

Under the evolving environment, a utility company is required to improve the operation and maintenance of its physical assets usually in the forms of an asset management program. This paper proposes an organisational learning model for the utility companies with respect to the asset management activities. CommonKADS is utilised as a tool to capture the knowledge associated with managing the assets from the learning processes of the utility company. A case study of Bangpakong power plant in Thailand is presented. The results show that by applying the proposed methodologies, the learning processes within the utility companies can be categorised and explained by five major learning steps of breakdown, corrective, preventive, predictive, and proactive maintenances

Dynamic adjustment of age distribution in Human Resource Management by genetic algorithms.

Adjustment of a given age distribution to a desired age distribution within a required time frame is dynamically performed for the purpose of Human Resource (HR) planning in Human Resource Management (HRM). The adjustment process is carried out by adding the adjustment magnitudes to the existing number of employees at the selected age groups on the yearly basis. A model of a discrete dynamical system is employed to emulate the evolution of the age distribution used under the adjustment process. Genetic Algorithms (GA) is applied for determining the adjustment magnitudes that influence the dynamics of the system. An interesting aspect of the problem lies in the high number of constraints; though the constraints are fundamental, they are considerably higher in number than in many other optimization problems. An adaptive penalty scheme is proposed for handling the constraints. Numerical examples show that GA with the utilized adaptive penalty scheme provides potential means for HR planning in HRM

Enhancing university research activities with knowledge management.

In the new economy, innovation is regarded as one of the solutions for almost every organisation to survive in the new business era. Universities, especially in terms of research activities, are no difference since they strive for novelties which potentially lead to innovation. An experienced researcher in the university has continually created tacit knowledge in a specific domain, but typically found it difficult to share this tacit knowledge among other researchers for the problem solving purpose. To overcome this problem and to better stimulate knowledge sharing activities among university researchers, Knowledge Management and Knowledge Engineering, particularly KADS, are utilised in this paper to assist a group of different domain researchers in putting their experiences together. In this way, each researcher can make explicit his or her tacit knowledge into KADS task, inference and domain knowledge models. The structured knowledge models captured from different researchers can then be merged together. In this paper, the research in Knowledge Management is selected as a case study, and the results show that the relevant tacit knowledge has been made explicit from a researcher and allow other researchers to share the knowledge as well as to add their own knowledge. Hence, their common research theme is effectively created, and also maintained by a group of researchers

A Gaussian process based fleet lifetime predictor model for unmonitored power network assets

This paper proposes the use of Gaussian Process Regression to automatically identify relevant predictor variables in a formulation of a remaining useful life model for unmonitored, low value power network assets. Reclosers are used as a proxy for evaluating the efficacy of this method. Distribution network reclosers are typically high-volume assets without on-line monitoring, leading to an insufficient understanding of which factors drive their failures. The ubiquity of reclosers, and their lack of monitoring, prevents the tracking of their individual remaining life, and, confirms their use in validating the proposed process. As an alternative to monitoring, periodic inspection data is used to evaluate asset risk level, which is then used in a predictive model of remaining useful life. Inspection data is often variable in quality with a number of features missing from records. Accordingly, missing inputs are imputed by the proposed process using samples drawn from an advanced form of joint distribution learned from test records and reduced to its conditional form. This work is validated on operational data provided by a regional distribution network operator, but conceptually is applicable to unmonitored fleets of assets of any power network

An alternative electricity market architecture for an inclusion of distributed generation in a competitive environment

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The Effect of Female Directors on ESG Practice: Evidence from China

This paper empirically examines the impact of female directors on corporate ESG disclosure scores based on upper echelons theory and women’s ethics of care theory by conducting a multiple regression analysis on 8193 observations of Chinese listed companies from 2010 to 2020. Our results demonstrate the importance of female directors’ participation in promoting corporate ESG practices. We conclude that the higher the proportion of female directors on the board, the higher the corporate ESG practice score. Further analysis also revealed that a favorable institutional environment and non-state enterprises positively moderate the relationship between female directors and corporate ESG practices. These results highlight the significant contribution of female directors to corporate ESG practices. Our paper sheds additional light on issues related to female directors and corporate ESG practices in Chinese listed companies, expands the theoretical knowledge of ethical decision-making and institutional environments in listed companies, enriches research in the area of female directors’ decision-making, and has important implications for corporate governance related policy-making in China

An application of HHI to study electricity market design issues

This paper presents a study of market design issues for the future Electricity Supply Industry of countries in transition from monopolistic to more competitive structures. An approach is developed to apply a standard measurement of market concentration, such as Herfindahl Hirschman Index (HHI) within the market design context. Typically, HHI is used to study market power issues in established electricity markets. The approach presented in this paper indicates that HHI can also be used as a primary method to study market design ahead of implementation. A dynamic simulation of the Thai market is used to confirm the applicability of the approach presented in this paper