Human factors play a relevant role in the dynamic work environments of the manufacturing sector in terms of production efficiency, safety, and sustainable performance. This is particularly relevant in assembly lines where humans are widely employed alongside automated and robotic agents. In this situation, operators' ability to adapt to different levels of task complexity and variability in each workstation has a strong impact on the safety, reliability, and efficiency of the overall production process. This paper presents an application of a theoretical and empirical method used to assess the matching of different workers to various workstations based on a quantified comparison between the workload associated with the tasks and the human capability of the workers that can rotate among them. The approach allowed for the development of an algorithm designed to operationalise indicators for workload and task complexity requirements, considering the skills and capabilities of individual operators. This led to the creation of human performance (HP) indices. The HP indices were utilized to ensure a good match between requirements and capabilities, aiming to minimise the probability of human error and injuries. The developed and customised model demonstrated encouraging results in the specific case studies where it was applied but also offers a generalizable approach that can extend to other contexts and situations where job rotations can benefit from effectively matching operators to suitable task requirements.

Human capabilities refer to an individual's innate and acquired abilities that enable them to complete a given task. These capabilities contain physical, mental, and cognitive skills. In an industrial environment, the complexity and nature of duties vary, and different jobs require different levels and types of human capabilities. For example, in an assembly line, a task that demands assembling small and fragile parts would require a high level of manual skill and precision. Understanding the human capabilities necessary for a job and matching them with the worker's capabilities is crucial for designing and implementing tasks in industrial settings. The term "ability corners" describes equipment (hardware and software) for evaluating and measuring human capabilities in industrial workplaces. The results of these tests are used to match workers with the specific abilities needed for a particular workstation. This study proposes improving the "ability corners" by addressing some limitations, such as the insufficient number of tests to assess human capabilities and the lack of consideration for workers' motivation, personality traits, and other factors that might affect their performance on the task. Furthermore, the study in which they were adopted does not consider the dynamic nature of assembly line work or the possible changes in workers' capabilities over time due to factors such as experience, training, or fatigue. The present revision aims to enhance the accuracy and effectiveness of the "ability corners" approach by integrating new techniques, devices, and benchmarks into the current method to guarantee that the worker is well-suited for the job and can execute it safely. This work is part of our Collaborative Intelligence for Safety-Critical Systems (CISC) project research activity. https://www.ciscproject.eu/

The challenge to make cities and human settlements inclusive, safe, and resilient, including mitigation and adaptation strategies against disaster, is a central issue in achieving sustainability. This research proposes a tool to measure local vulnerability from a multi-risk approach. The municipality of Moncalieri, Italy, was used as a case study within the research activities of the Responsible Risk Resilience Centre from the Polytechnic of Turin to test the vulnerability matrix. The tool consists of a mathematical framework for the territorial vulnerability assessment that integrates multiple indicators clustered into three factors defined as sensitivity, pressures, and hazards, weighted according to a participatory procedure. Space-dependent analyses using the Geographical Information System were developed from the multiple nested indicators to project the vulnerability index onto a homogeneous grid in the territory of interest. Thematic maps referring to the systemic vulnerability by different sensitivity components were generated. The tool not only contributes to increasing the awareness of territorial vulnerability but also offers support to resilience-based decision-making in designing technical measures of policies at a local scale. Further research is required to implement the framework in different scenarios and develop the model's temporal behaviour.