The role of Industry 4.0 enabling technologies for safety management: A systematic literature review

Abstract Innovations introduced during the Industry 4.0 era consist in the integration of the so called "nine pillars of technologies" in manufacturing, transforming the conventional factory in a smart factory. The aim of this study is to investigate enabling technologies of Industry 4.0, focusing on technologies that have a greater impact on safety management. Main characteristics of such technologies will be identified and described according to their use in an industrial environment. In order to do this, we chose a systematic literature review (SLR) to answer the research question in a comprehensively way. Results show that articles can be grouped according to different criteria. Moreover, we found that Industry 4.0 can increase safety levels in warehouse and logistic, as well as several solutions are available for building sector

Prioritizing Human Factors in Emergency Conditions Using AHP Model and FMEA

One of the most critical issues related to safety in industrial plant is to manage accidents that occur in industries. In general, the causes of accidents are twofold: the presence of dangerous equipment and human errors. The aim of this study is to propose a novel approach to ensure safety in emergency conditions in industrial plant considering both of these factors. The proposed idea aims to integrate the human reliability analysis (HRA) and the failure modes and effects analysis (FMEA). The human errors and failure modes are categorized using a multicriteria approach based on analytic hierarchy process (AHP). The final aim is to present a novel methodological approach based on AHP to prioritize actions to carry out in emergency conditions taking into account both qualitative and quantitative factors. A real case study is analyzed. The analysis allowed to identify possible failure modes connected with human error process

Universal scaling of a classical impurity in the quantum Ising chain

We study finite size scaling for the magnetic observables of an impurity residing at the endpoint of an open quantum Ising chain in a transverse magnetic field, realized by locally rescaling the magnetic field by a factor $\mu \neq 1$. In the homogeneous chain limit at $\mu = 1$, we find the expected finite size scaling for the longitudinal impurity magnetization, with no specific scaling for the transverse magnetization. At variance, in the classical impurity limit, $\mu = 0$, we recover finite scaling for the longitudinal magnetization, while the transverse one basically does not scale. For this case, we provide both analytic approximate expressions for the magnetization and the susceptibility as well as numerical evidences for the scaling behavior. At intermediate values of $\mu$, finite size scaling is violated, and we provide a possible explanation of this result in terms of the appearance of a second, impurity related length scale. Finally, on going along the standard quantum-to-classical mapping between statistical models, we derive the classical counterpart of the quantum Ising chain with an impurity at its endpoint as a classical Ising model on a square lattice wrapped on a half-infinite cylinder, with the links along the first circle modified as a function of $\mu$.Comment: Update closer to published versio

Systematic Human Reliability Analysis (SHRA): A New Approach to Evaluate Human Error Probability (HEP) in a Nuclear Plant

Emergency management in industrial plants is a fundamental issue to ensure the safety of operators. The emergency management analyses two fundamental aspects: the system reliability and the human reliability. System reliability is the capability of ensuring the functional properties within a variability of work conditions, considering the possible deviations due to unexpected events. However, system reliability is strongly related to the reliability of its weakest component. The complexity of the processes could generate incidental situations and the worker appears (human reliability) to be the weakest part of the whole system. The complexity of systems influences operator's ability to take decisions during emergencies. The aim of the present research is to develop a new approach to evaluate human error probability (HEP), called Systematic Human Reliability Analysis (SHRA). The proposed approach considers internal and external factors that affect operator's ability. The new approach is based on Nuclear Action Reliability Assessment (NARA), Simplified Plant Analysis Risk Human Reliability (SPAR-H) and on the Performance Shaping Factors (PSFs) relationship. The present paper analysed some shortcomings related to literature approaches, especially the limitations of the working time. We estimated HEP, after 8 hours (work standard) during emergency conditions. The correlations between the advantages of these three methodologies allows proposing a HEP analysis during accident scenarios emergencies. SHRA can be used to estimate human reliability during emergencies. SHRA has been applied in a nuclear accident scenario, considering 24 hours of working time. The SHRA results highlight the most important internal and external factors that affect operator's ability

An Experimental Study on Developing a Cognitive Model for Human Reliability Analysis

Serious incidents that occur inside or caused by industrial plants represent a very critical issue. In this context, the human reliability analysis (HRA) is an important tool to assess human factors that influence human behaviour in disasters scenario. In fact, the reliability assessment of interaction between human-machine systems is an important factor that affects the overall performance and safety in industrial plants. However, even though HRA techniques have been available for decades, there is not a universal method/procedure to reduce human errors that affect human performance. This study aims to design a novel approach to investigate the relationship between human reliability and operator performance considering the dependence on the available time to make decisions

Quality Checks Logit Human Reliability (LHR): A New Model to Evaluate Human Error Probability (HEP)

In the years, several approaches for human reliability analysis (HRA) have been developed. The aim of the present research is to propose a hybrid model to evaluate Human Error Probability (HEP). The new approach is based on logit-normal distribution, Nuclear Action Reliability Assessment (NARA), and Performance Shaping Factors (PSFs) relationship. In the research, shortcomings related to literature approaches are analyzed, especially the limitations of the working time. For this reason, PSFs after 8 hours (work standard) during emergency conditions were estimated. Therefore, the correlation between the advantages of these three methodologies allows proposing a HEP analysis during accident scenarios and emergencies; a fundamental issue to ensure the safety and reliability in industrial plants is emergency Mmnagement (EM). Applying EM methodology, two main aspects are analyzed: system reliability and human reliability. System reliability is strongly related to the reliability of its weakest component. During incidental situations, the weakest parts of the whole system are workers (human reliability) and accidental scenarios influence the operator’s ability to make decisions. This article proposes a new approach called Logit Human Reliability (LHR) that considers internal and external factors to estimate human reliability during emergencies. LHR has been applied in a pharmaceutical accident scenario, considering 24 hours of working time (more than 8 working hours). The results highlighted that the LHR method gives output data more in conformity with data banks than the conventional methods during the stress phase in an accident scenario

Squeezing out predictions with leptogenesis from SO(10)

We consider the see-saw mechanism within a non-supersymmetric SO(10) model. By assuming the SO(10) quark-lepton symmetry, and after imposing suitable conditions that ensure that the right-handed (RH) neutrino masses are at most mildly hierarchical (compact RH spectrum) we obtain a surprisingly predictive scenario. The absolute neutrino mass scale, the Dirac and the two Majorana phases of the neutrino mixing matrix remain determined in terms of the set of already measured low energy observables, modulo a discrete ambiguity in the signs of two neutrino mixing angles and of the Dirac phase. The RH neutrinos mass spectrum is also predicted, as well as the size and sign of the leptogenesis CP asymmetries. We compute the cosmological baryon asymmetry generated through leptogenesis and obtain the correct sign and a size compatible with observations.Comment: 18 pages, 2 figures; minor changes, version accepted for publication in PR

Beyond the Guidelines: The Grey Zones of the Management ofGastric Cancer. Consensus Statements from the Gastric CancerItalian Network (GAIN)

The Grey Zones of the Management ofGastric Cancer. Consensus Statements from the Gastric CancerItalian Network (GAIN