A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, in fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg, 2017 / This study examines the application of the investigation process in industry to reduce electrical arc flash incidents. Literature indicates that three streams (policies, completed investigations and investigators) influence the application of the investigation process; however, these are traditionally analysed independently without examining the dynamic influences between them. This study combines and analyses those dynamic interactions, and testing at a steel plant demonstrates that this approach allows industry to identify site specific deficiencies. The investigation process requirements, identified in literature, were used to qualitatively and quantitatively analyse the three streams. The results were interpreted using triangulation. Deficiencies around disseminating reports and using experienced investigators were identified. These plant specific deficiencies are an improvement from generic findings in literature. This study contributed to knowledge in the field of incident investigations by proposing a holistic approach that is operationally ready, and identifies deficiencies specific to the industry in which it is used. / MT 2018

Mankind, and the development of people, exists due to risk-taking behaviour. It is not that humans should not take risks, but rather the ability to identify the magnitude of risk exposure in order that mankind‟s actions would be so selected as to mitigate exposed risk factors, that no harm should befall them. The approach to health and safety (H&S) has always been to manage H&S environmental factors that could have a negative impact on people, capital, and organisational systems. However, the critical component of human risk-taking behaviour that would have a far greater impact has rarely been acknowledged as part of the drivers that increase risk exposure. Human behaviour is a major contributing factor in accident causation. Although human error cannot be completely eliminated, it should be identified and correctly managed according to each individual‟s risk-taking profile. The reason people decide to take certain risks under certain conditions and the effect it has on H&S management systems is a key component to managing organisational risk exposure. To quantify the value of individual risk-taking behaviour could provide management with better opportunities of lowering the organisational risk exposure. Human risk-taking behaviour is influenced by each individual‟s perception of risk. Such perception of risk will influence decisions on risk-taking behaviour, which in turn is influenced by the individual‟s psychological profile and environmental factors, including character and the impact of a cultural environment. The electrical construction and maintenance industry differs from other similar industries in that the physical entity of electricity requires not only sensory perception for the identification and evaluation of risk factors, but also requires specialised knowledge and testing equipment to evaluate the parameters of electrical installation, plant or equipment. Without such competence, direct exposure to most electrical installations could be fatal. The optimum human resource (HR) solution for managing the risk potential of high risk-taking behaviour is the rating and allocation of specific job tasks that can match and limit the individual potential for risk-taking behaviour and the impact on organisational incident statistics. Maintaining and optimising employee job performance enables organisations to better achieve pre-set goals and missions. Such improvements being a catalyst for better job performance by setting limitations on high risk-taking behaviour, that will improve H&S performance by lowering incident rates.

Indiana University-Purdue University Indianapolis (IUPUI) / Lithium-ion battery is one kind of rechargeable battery, and also renewable, sustainable and portable. With the merits of high density, slow loss of charge when spare and no memory effect, lithium-ion battery is widely used in portable electronics and hybrid vehicles. Apart from its advantages, safety is a major concern for Lithium-ion batteries due to devastating incidents with laptop and cell phone batteries. Overcharge and over-discharge are two of the most common electrical abuses a lithium-ion battery suffers. In this thesis, a fuzzy-rule-based system is proposed to detect the over-charge and over-discharge failure in early time. The preliminary results for the failure signatures of overcharged and over-discharged lithium-ion are listed based on the experimental results under both room temperature and high temperature. A fuzzy-rule-based model utilizing these failure signatures is developed and validated. For over-charge case, the abnormal increase of the surface temperature and decrease of the voltage are captured. While for over discharge case, unusual temperature increase during overcharge phases and abnormal current decrease during overcharge phases are obtained. The inference engine for fuzzy-rule-based system is designed based on these failure signatures. An early warning signal will be given by this algorithm before the failure occurs. This failure detection and early warning system is verified to be effective through experimental validation. In the validation test, the proposed methods are successfully implemented in a real-time system for failure detection and early warning. The result of validation is compatible with the design expectation. Finally an accurate failure detection and early warning system is built and tested successfully.