Abstract
The European Directive on Safety and Health at Work and the following normatives have the scope to provide high levels of health and safety at work, based on some general principles managing activities and including the risk assessment to continuously improve processes and workplaces. However, the working area changes and brings new risks and challenges for workers. Several of them are associated with new technologies, which determine complex human–machine interactions, leading to an increased mental and emotional strain. To reduce these emerging risks, their understanding and assessment are important. Although great efforts have already been made, there is still a lack of conceptual frameworks for analytically assessing human–machine interaction. This paper proposes a systematic approach that, beyond including the classification in domains to explain the complexity of the human–machine interaction, accounts for the information processing of the human brain. Its validation is shown in a major accident hazard industry where a smart safety device supporting crane related operations is used. The investigation is based on the construction of a questionnaire for the collection of answers about the feeling of crane operators when using the device and the evaluation of the Cronbach’s alpha to measure of the reliability of the assessment.
Highlights
The use of smart devices for the improvement of safety in workplaces is becoming enormously popular, in the chemical and process industry classified at major accident hazard [1], where the use of tools and machines is growing in number and complexity [2]
This paper presents a systematic approach for the identification, organisation and assessment of complexity factors, which has been applied to the use of a safety device supporting crane operators in performing their tasks
The investigation of human factors presented in this study represents a case of usercentred approach to the design of smart safety devices
Summary
The use of smart devices for the improvement of safety in workplaces is becoming enormously popular, in the chemical and process industry classified at major accident hazard [1], where the use of tools and machines is growing in number and complexity [2]. From the safety point of view, relevant workplaces are those where cranes are used for the handling/lifting of loads, because failures could be the cause of severe accidents [3,4,5]; there is a need to assess and manage the risk [6,7]. Minimising human factors in the design of machines is essential [8]; this permits the reduction of errors, the increase of the productivity and the enhancement of safety and comfort when humans interact with a system, etc
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