A study of factors relating to health and safety in the engineering industry in Northern Ireland

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An expert system for the development of a health and safety policy/risk assessment in the plastics industry

Health and safety policies may be regarded as the cornerstone for positive prevention of occupational accidents and diseases. The Health and Safety at Work, etc Act 1974 makes it a legal duty for employers to prepare and revise a written statement of a general policy with respect to the health and safety at work of employees as well as the organisation and arrangements for carrying out that policy. Despite their importance and the legal equipment to prepare them, health and safety policies have been found, in a large number of plastics processing companies (particularly small companies), to be poorly prepared, inadequately implemented and monitored. An important cause of these inadequacies is the lack of necessary health and safety knowledge and expertise to prepare, implement and monitor policies. One possible way of remedying this problem is to investigate the feasibility of using computers to develop expert system programs to simulate the health and safety (HS) experts' task of preparing the policies and assisting companies implement and monitor them. Such programs use artificial intelligence (AI) techniques to solve this sort of problems which are heuristic in nature and require symbolic reasoning. Expert systems have been used successfully in a variety of fields such as medicine and engineering. An important phase in the feasibility of development of such systems is the engineering of knowledge which consists of identifying the knowledge required, eliciting, structuring and representing it in an appropriate computer programming language.

Safety culture during major organisational change

This research examines the effect of major changes, in the external context, on the safety culture of a UK generating company. It was focused on an organisation which was originally part of the state owned Central Electricity Generating Board and which, by the end of the research period, was a self-contained generating company, operating in a competitive market and a wholly owned subsidiary of a US utility. The research represents an attempt to identify the nature and culture of the original organisation and to identify, analyse and explain the effects of the forces of change in moulding the final organisation. The research framework employed a qualitative methodology to investigate the effects of change, supported by a safety culture questionnaire, based on factors identified in the third report of the ACSNI Human Factors Study Group; Organising for Safety, as being indicators of safety culture. An additional research objective was to assess the usefulness of the ACSNI factors as indicators of safety culture. Findings were that the original organisation was an engineering dominated technocracy with a technocentric safety culture. Values and beliefs were very strongly held and resistant to change and much of the original safety culture survived unchanged into the new organisation. The effects of very long periods of uncertainty about the future were damaging to management/worker relationships but several factors were identified which effectively insulated the organisation from any of the effects of change. The forces of change had introduced a beneficial appreciation of the crucial relationship between safety risk assessment and commercial risk assessment.Although the technical strength of the original safety culture survived, so did the essential weakness of a low level of appreciation of the human behavioural aspects of safety. This led to a limited, functionalist world view of safety culture, which assumed that cultural change was simpler to achieve than was the case and an inability to make progress in certain areas which were essentially behavioural problems.The factors identified by ACSNI provided a useful basis for the site research methodology and for identifying areas of relative strength and weakness in the site safety arrangements.

Experiences on dynamic simulation software in chemical engineering education

Commercial process simulators are increasing interest in the chemical engineer education. In this paper, the use of commercial dynamic simulation software, D-SPICE® and K-Spice®, for three different chemical engineering courses is described and discussed. The courses cover the following topics: basic chemical engineering, operability and safety analysis and process control. User experiences from both teachers and students are presented. The benefits of dynamic simulation as an additional teaching tool are discussed and summarized. The experiences confirm that commercial dynamic simulators provide realistic training and can be successfully integrated into undergraduate and graduate teaching, laboratory courses and research. © 2012 The Institution of Chemical Engineers.

Representing human expertise by the OWL web ontology language to support knowledge engineering in decision support systems

Clinical decision support systems (CDSSs) often base their knowledge and advice on human expertise. Knowledge representation needs to be in a format that can be easily understood by human users as well as supporting ongoing knowledge engineering, including evolution and consistency of knowledge. This paper reports on the development of an ontology specification for managing knowledge engineering in a CDSS for assessing and managing risks associated with mental-health problems. The Galatean Risk and Safety Tool, GRiST, represents mental-health expertise in the form of a psychological model of classification. The hierarchical structure was directly represented in the machine using an XML document. Functionality of the model and knowledge management were controlled using attributes in the XML nodes, with an accompanying paper manual for specifying how end-user tools should behave when interfacing with the XML. This paper explains the advantages of using the web-ontology language, OWL, as the specification, details some of the issues and problems encountered in translating the psychological model to OWL, and shows how OWL benefits knowledge engineering. The conclusions are that OWL can have an important role in managing complex knowledge domains for systems based on human expertise without impeding the end-users' understanding of the knowledge base. The generic classification model underpinning GRiST makes it applicable to many decision domains and the accompanying OWL specification facilitates its implementation.