Safety at work The objective of the project Safety at Work is to increase safety at the workplace by applying and combining state of the art artefacts from personal protective equipment and ambient intelligence technology. In this state of the art document we focus on the developments with respect to how (persuasive) technology can help to influence behaviour in a natural, automatic way in order to make industrial environments safer. We focus on personal safety, safe environments and safe behaviour. Direct ways to influence safety The most obvious way to influence behaviour is to use direct, physical measures. In particular, this is known from product design. The safe use of a product is related to the characteristics of the product (e.g., sharp edges), the condition of people operating the product (e.g., stressed or tired), the man-machine interface (e.g., intuitive or complex) and the environmental conditions while operating the product (e.g., noisy or crowded). Design guidelines exist to help designers to make safe products. A risk matrix can be made with two axis: product hazards versus personal characteristics. For each combination one might imagine what can go wrong, and what potential solutions are. Except for ‘design for safety’ in the sense of no sharp edges or a redundant architecture, there is a development called ‘safety by design’ as well. Safety by design is a concept that encourages construction or product designers to ‘design out’ health and safety risks during design development. On this topic, we may learn from the area of public safety. Crime Prevention Through Environmental Design (or Designing Out Crime) is a multi-disciplinary approach to deterring criminal behaviour through environmental design. Designing Out Crime uses measures like taking steps to increase (the perception) that people can be seen, limiting the opportunity for crime by taking steps to clearly differentiate between public space and private space, and promoting social control through improved proprietary concern. Senses Neuroscience has shown that we have very little insight into our motivations and, consequently, are poor at predicting our own behaviour. It seems emotions are an important predictor of our behaviour. Input from our senses are important for our emotional state, and therefore influence our behaviour in an ‘ambient’ (invisible) way. The first sense we focus on is sight. Sight encompasses the perception of light intensity (illuminance) and colours (spectral distribution). Several researchers have studied the effects of light and colour in working environments. Results show, e.g., that elderly people can be helped with higher light levels, that cool colours like blue and green have a relaxing effect, while long-wavelength colours such as orange and red are stimulating and give more arousal, and that concentration and motivation of pupils at school can be influenced with light and colour settings. Identically, sound (hearing) has physiological effects (unexpected sounds cause extra cortisol -the fight or flight hormone- and the opposite for soothing sounds), psychological effects (sounds effect our emotions), cognitive effects (sounds effect our concentration) and behavioural effects (the natural behaviour of people is to avoid unpleasant sounds, and embrace pleasurable sounds). Smell affects 75% of daily emotions and plays an important role in memory, itis also important as a warning for danger (gas, burning smell). Research has shown that smell can influence work performance. Haptic feedback is a relative new area of research, and most studies focus on haptic feedback on handheld and automotive devices. Finally, employers have a duty to take every reasonable precaution to protect workers from heat stress disorders. Influence mechanisms: Cialdini To influence behaviour, we may learn from marketing psychology. Robert Cialdini states that if we have to think about every decision
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Recent years have seen a global rise in the failure of tailings dams. Studies investigating the causes of slope failure often recognise high intensity rainfall events to significantly contribute to liquefaction, erosion and overtopping. This study aims to investigate the influence of alternative physical and geohydrological processes that, under tension saturation conditions, contribute to slope instability in tailings dams. It has been suggested that the generation of transient pressure wave mechanisms by high intensity rainfall events, surface ponding and wetting front advancement result in the formation of an induced pressure head that triggers the mobilization of pre-event water. In order to quantify these physical processes, this study included the analysis of rapid transmission conditions in a silica fines mix, with similar physical and hydraulic characteristics as platinum tailings. A tall leak-proof soil column, containing the soil sample compacted to in-situ dry bulk density, was fitted with seven observation ports. Each port consisted of a pore air pressure probe, a mini tensiometer and a time domain reflectometry probe. After set-up and initial stabilisation, three separate artificial high intensity rainfall events were applied to the surface. Monitoring of hydraulic state variables was recorded at thirty second intervals by automatic logging, thereby enabling the analysis of measured outcomes. Observations showed instant spikes in pore air pressure ahead of the wetting front, as well as a number of delayed responses. The interpretation of lab results led to the conclusion that pressure diffusion mechanisms throughout the porous medium, could result in the rapid release and mobilisation of previously stagnant antecedent moisture, thereby enabling phreatic levels to rising rapidly and in excess to the amount of surface infiltration. Also, since an increase in pore water pressure is likely to cause a reduction in shear strength, it is suggested that these physical and geohydrological processes could have an adverse impact on the stability of tailings dams.
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This paper proposes an amendment of the classification of safety events based on their controllability and contemplates the potential of an event to escalate into higher severity classes. It considers (1) whether the end-user had the opportunity to intervene into the course of an event, (2) the level of end-user familiarity with the situation, and (3) the positive or negative effects of end-user intervention against expected outcomes. To examine its potential, we applied the refined classification to 296 aviation safety investigation reports. The results suggested that pilots controlled only three-quarters of the occurrences, more than three-thirds of the controlled cases regarded fairly unfamiliar situations, and the flight crews succeeded to mitigate the possible negative consequences of events in about 71% of the cases. Further statistical tests showed that the controllability-related characteristics of events had not significantly changed over time, and they varied across regions, aircraft, operational and event characteristics, as well as when fatigue had contributed to the occurrences. Overall, the findings demonstrated the value of using the controllability classification before considering the actual outcomes of events as means to support the identification of system resilience and successes. The classification can also be embedded in voluntary reporting systems to allow end-users to express the degree of each of the controllability characteristics so that management can monitor them over time and perform internal and external benchmarking. The mandatory reports concerned, the classification could function as a decision-making parameter for prioritising incident investigations.
