D. Divya, Bhasi Marath and M.B. Santosh Kumar
This study aims to bring awareness to the developing of fault detection systems using the data collected from sensor devices/physical devices of various systems for predictive…
Abstract
Purpose
This study aims to bring awareness to the developing of fault detection systems using the data collected from sensor devices/physical devices of various systems for predictive maintenance. Opportunities and challenges in developing anomaly detection algorithms for predictive maintenance and unexplored areas in this context are also discussed.
Design/methodology/approach
For conducting a systematic review on the state-of-the-art algorithms in fault detection for predictive maintenance, review papers from the years 2017–2021 available in the Scopus database were selected. A total of 93 papers were chosen. They are classified under electrical and electronics, civil and constructions, automobile, production and mechanical. In addition to this, the paper provides a detailed discussion of various fault-detection algorithms that can be categorised under supervised, semi-supervised, unsupervised learning and traditional statistical method along with an analysis of various forms of anomalies prevalent across different sectors of industry.
Findings
Based on the literature reviewed, seven propositions with a focus on the following areas are presented: need for a uniform framework while scaling the number of sensors; the need for identification of erroneous parameters; why there is a need for new algorithms based on unsupervised and semi-supervised learning; the importance of ensemble learning and data fusion algorithms; the necessity of automatic fault diagnostic systems; concerns about multiple fault detection; and cost-effective fault detection. These propositions shed light on the unsolved issues of predictive maintenance using fault detection algorithms. A novel architecture based on the methodologies and propositions gives more clarity for the reader to further explore in this area.
Originality/value
Papers for this study were selected from the Scopus database for predictive maintenance in the field of fault detection. Review papers published in this area deal only with methods used to detect anomalies, whereas this paper attempts to establish a link between different industrial domains and the methods used in each industry that uses fault detection for predictive maintenance.
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Keywords
Beena Puthillath, Bhasi Marath and Babu Chembakthuparambil Ayappan
This study aims to explore the factors influencing electrical accidents. Here, the authors aim to understand and model the causes of electrical accidents at multiple levels.
Abstract
Purpose
This study aims to explore the factors influencing electrical accidents. Here, the authors aim to understand and model the causes of electrical accidents at multiple levels.
Design/methodology/approach
In the study, the authors have tried to put causes of accidents in the electricity distribution segment, in the framework of the Swiss Cheese model. Delphi kind of expert survey was conducted to find the Cheese Slice (level) and the causes (holes) for electrical accidents. Inputs from a hundred experts having more than five years of experience in electrical utility companies have been used to find Cheese Slice and holes, to explain the occurrence of an electrical accident.
Findings
Effective training for safe work practices, safe knowledge and closer supervision would go a long way to plug the holes in the Cheese Slice in human factors. The difference in perception of managers, supervisors and workers on the importance of various causes of electrical accidents are also presented and discussed.
Research limitations/implications
This research is based on expert opinion and survey where respondent perception is reported. Actual accident data has not been used here.
Practical implications
The holes or causes of accidents at different levels (Cheese Slice) have been identified for plugging or removal for better safety.
Social implications
Electrical energy is widely used, and therefore, electrical safety is a social concern and also improving it is a social need.
Originality/value
The study contributes to electrical safety issues in the electrical utility sector.
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The aim of this research is to analyze empirical evidence of the effect of governance structure (GS) on perceived success of the succession process. It is also reported that in…
Abstract
Purpose
The aim of this research is to analyze empirical evidence of the effect of governance structure (GS) on perceived success of the succession process. It is also reported that in India, family firms have a more informal organization structure and governance and have an informal and unplanned approach to bringing the successors into family business. Previous studies have reported that GS is an important factor for a successful succession process. This study examines the role of management succession planning as an intervening variable to achieve perceived success of the succession process.
Design/methodology/approach
Data have been collected using a questionnaire schedule with 113 respondents who are successors from family business firms in Kerala, India. The study uses snowball sampling technique. Partial least square-structural equation modeling has been used to do data analysis.
Findings
The results of the study showed that GS has a significant positive effect on the success of the succession process. GS has a significant positive effect on management succession planning. Management succession planning partially mediates the relationship between GS and perceived success of the succession process.
Research limitations/implications
The results of the study indicate the effect of GS on the relationship between, perceived success of the succession process and management succession planning. The mediating role of management succession planning in the above relationship is also confirmed. Therefore, before starting the succession process a good GS should be put in place for ensuring the success of the succession process. Family firms must implement the succession plan well to make the succession process successful.
Originality/value
The main contribution of the study is to empirically investigate the effect of GS and management succession planning to enhance the success of the succession process.