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

Revising the “Ability Corners” Approach: A New Strategy to Assessing Human Capabilities in Industrial Domains / ALBARRAN MORILLO, Carlos; Demichela, Micaela; Leva, Chiara. - ELETTRONICO. - (2023), pp. 2983-2990. (Intervento presentato al convegno 33RD EUROPEAN SAFETY AND RELIABILITY CONFERENCE (ESREL 2023) tenutosi a University of Southampton (UK) nel 3-7 September 2023) [10.3850/978-981-18-8071-1_P646-cd].

Revising the “Ability Corners” Approach: A New Strategy to Assessing Human Capabilities in Industrial Domains

Carlos Albarran Morillo;Micaela Demichela;Chiara Leva
2023

Abstract

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
2023
978-981-18-8071-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2981894