RESUMEN
Lightning strikes, a prominent meteorological event, pose a significant risk of triggering technological disruptions within the process industry. To better understand this phenomenon, an analysis focused on past lightning-triggered events was carried out, examining open-source industrial-accident databases to compile a new NaTech-driven dataset of 689 records. First, an overall quantitative analysis revealed that over 80 % of these events involved incidents or loss of containment. Notably, 83.3 % of them occurred during the spring and summer, indicating a seasonal pattern. Based on the frequency of functional attributes, the chemical and petrochemical macro-sector was the most vulnerable, followed by storage and warehousing. About 40 % of all classifiable events happened on storage equipment, while 21 % happened on electric and electronic devices. Given the lack of valuable information for the principal source of data (NRC), the technological scenarios triggered were characterized using a refined subset of 127 observations, obtained considering the "other sources" of data. Fire scenarios predominated at 56 %; coincidentally, roughly 70 % of all scenarios involved hazardous substances classified as physical hazards. Estimated losses for the available information underscored the adverse consequences of lightning-triggered NaTech events, highlighting their major impact on both safety and the environment. An analysis of the event tree showed the logical path from the lightning strike to the final ignition scenarios (considering a subset of 107 records). This path accounted for 36 % of the classifiable records that directly affected the structure, while more than 50 % of them did not. Bayesian network structures made it possible to get conditional probabilities from the event tree and improved the model by adding attributes for vulnerable equipment and macro-sectors. In order to deal with the uncertain data, algorithms were used to generalize the models that were obtained from smaller subsets of data with more accurate information to the whole dataset. It provides an important additional view of unclassifiable data that otherwise remained in the dark. This novel insight contributes to increase the vulnerability awareness of industrial assets against lightning strikes.
RESUMEN
These datasets contain measures from multi-modal data sources. They include objective and subjective measures commonly used to determine cognitive states of workload, situational awareness, stress, and fatigue using data collection tools such as NASA-TLX, SART, eye tracking, EEG, Health Monitoring Watch, a survey to assess training, and a think-aloud situational awareness assessment following the SPAM methodology. Also, data from a simulation formaldehyde production plant based on the interaction of the participants in a controlled control room experimental setting is included. The interaction with the plant is based on a human-in-the-loop alarm handling and process control task flow, which includes Monitoring, Alarm Handling, Recovery planning, and intervention (Troubleshooting, Control and Evaluation). Data was collected from 92 participants, split into four groups while they underwent the described task flow. Each participant tested three scenarios lasting 15-18 min with a -10-min survey completion and break period in between using different combinations of decision support tools. The decision support tools tested and varied for each group include alarm prioritisation vs. none, paper-based vs. Digitised screen-based procedures, and an AI recommendation system. This is relevant to compare current practices in the industry and the impact on operators' performance and safety. It is also applicable to validate proposed solutions for the industry. A statistical analysis was performed on the dataset to compare the outcomes of the different groups. Decision-makers can use these datasets for control room design and optimisation, process safety engineers, system engineers, human factors engineers, all in process industries, and researchers in similar or close domains.
RESUMEN
Storage of flammable liquids is a common activity in many industrial domains. A history of accidents shows that liquid storage has been involved in several critical accidents due to the large amount of hazardous substances potentially involved in the incident. Safe storage of flammable liquids is often guaranteed through blanketing of the internal atmosphere of the tank through the introduction of an inert gas, usually nitrogen. A double action pressure safety valve is often installed on the tank to protect the tank from damage in the event of overpressure or depression. In case of depression, an inert gas, usually nitrogen, is fed to the vapor space of the tank to maintain the vapor composition outside of the flammability limits. In case of lack of nitrogen, the opening of the pressure safety valve allows air to enter. The entry of air, especially if prolonged, can bring the atmosphere inside the tank to explosive conditions. This paper presents a simplified model for the estimation of the internal composition of the tank following the entry of air due to the opening of the pressure safety valve, following the process of fluid removal in case of lack of nitrogen. The model also allows the estimation of how much liquid can be safely removed. The simplified model can analyze both the case of a single tank and a tank farm.
RESUMEN
Data were collected in an automotive production plant during a campaign of observations performed by safety experts. A period of one week of observations was done during which safety experts monitored the working activity of an assembly line. All accident-precursors identified were reported in a format and immediately analysed and classified according to HFACS. Each collected element was classified in 3 categories as: unsafe acts (related to human behaviour), unsafe condition (related to the working condition and working organisation) and near miss (a situation that involved workers without physical consequence for them). Then each element was classified according to the four levels of HFACS: individual factor (violation or error), environmental factor, supervision and organisational factor. This step was supported by short interview with workers and/or supervisors involved to better identify the characterising factors of the event. This survey allowed the identification and classification of 100 accident-precursors that could be used in the company where they have been collected and, more in general, in manufacturing companies, to identify behaviours and areas of improvement for health and safety based on more recurrent factors that characterised the observed events, according to the methodology described in Baldissone et al. [1].
RESUMEN
Monitoring product temperature is mandatory in a freeze-drying process, in particular in the process development stage, as final product quality may be jeopardized when its temperature trespasses a threshold value, that is a characteristic of each product being freeze-dried. To this purpose thermocouples are usually inserted in some of the vials of the batch to track product dynamics. The position of the thermocouple inside the vials strongly affects the reading of the temperature evolution during the freeze-drying process and, thus, it is necessary to place them in the right position, in such a way that correct information about product temperature is obtained. In this work, at first, the probability of the operational error resulting into a wrong positioning of the thermocouple inside the vial has been estimated experimentally. Then, the effect of this error has been assessed in terms of risk of exceeding the limit temperature in the primary drying step. Both 4R and 10R vials have been considered, and the investigation evidenced that the probability of incorrect thermocouples placement can reach 30% for 10R vials, and about 32% for 4R vials. These probability values increase, respectively, to 47 and 39% when the trays containing the vials are shifted to their final position. Then, through IR thermal imaging it has been possible to evaluate the temperature gradients in a vial, pointing out that the temperature difference between the product at the center of the vial, where the thermocouple is supposed to be, and that of the wall, that is quite often measured by the thermocouples, can be about 1°C. Therefore, associated to each thermocouple reading there is a probability distribution of product temperature. These figures can be used to assess the risk of exceeding the limit temperature in a freeze-drying process and, thus, to quantify suitable safety margins when evaluating thermocouple readings to take into account the operational errors, given a risk tolerability criteria.