Cognitive and metabolic workload assessment techniques: A review in automotive manufacturing context

Abstract

Ergonomics assessment in the automotive industry has, to date, focused mainly on physical ergonomics, for example, manual handling and posture. However, workload and, in particular, metabolic and cognitive workload, contributes to worker efficiency but has not received sufficient attention to yield practical guidance for industry. Successful workload assessment requires in-depth understanding of the context in which it will be conducted and of the various assessment techniques which will be applied, with consideration given to factors such as feasibility, resources, and skill of the assessor. These requirements are met with challenges within large and complex organizations and are often dealt with in a piecemeal and isolated matter (i.e., reactive workload assessment). The present paper explores these challenges within the automotive manufacturing industry and aims to develop a decision matrix to guide effective selection of workload assessment techniques focused on metabolic and cognitive demands. It also presents the requirements for time, equipment, and knowledge to implement these techniques as part of a participatory ergonomics approach. Early findings suggest that most assessment techniques reviewed require further development, for example, to establish the acceptance criteria for the specific workload scenario. However, five methods (Garg, Borg RPE, IPAQ, SWAT, and NASA-TLX) are ready to use in certain applications.Ultimately, the findings suggest that it is possible to implement a participatory workload evaluation program within large and complex manufacturing plants.

A Preliminary Experimental Study on the Workers’ Workload Assessment to Design Industrial Products and Processes

“…This was first demonstrated in the design of nuclear power plants and air traffic control systems. In the last 5-6 years, cognitive workload assessment has also spread into industrial sectors, from process manufacturing to transport, construction, and energy [17]. The main objective of cognitive ergonomics is to improve the performance of human tasks in complex, dynamic and technologically advanced environments, through the design of effective support, understanding the fundamental principles of human activities associated with the principles of engineering design and development.…”

“…The user experience refers to the user's perceptions and responses that result from the use of a system, product, or service; this includes users' emotions, perceptions, comfort, and behaviors [16]. However, the human factors assessment in the automotive industry has, to date, mainly focused on physical ergonomics, analyzing the risks related to incongruous postures and the handling of loads, without considering the cognitive and emotional aspects [17]. Human factors have been introduced in engineering that consider the physical risks that correlate with possible musculoskeletal disorders, and that concurrently assess the psychological, social, and cultural needs of human beings [16], in order to guarantee human comfort and safety, and consequently to improve user performance.…”

Optimizing Human–Robot Teaming Performance through Q-Learning-Based Task Load Adjustment and Physiological Data Analysis

“…The NASA TLX has proven to be a reliable and widely used method for assessing task load in various domains, including healthcare [25], manufacturing [26], and education [27]. This tool assesses task load based on six indices; however, the importance of each index varies significantly across different tasks, and assigning accurate weights to each index presents a complex challenge [28].…”

Efficacy of real-time audio biofeedback on physiological strains for simulated tasks with medium and heavy loads

“…Heard et al (2018) surveyed these metrics and stated that EEG, heart rate/heart rate variability, skin temperature, and skin impedance conform "sensitivity" criteria with the ability to reliably detect physical workload levels where at least three published articles show the corresponding evidences. Subjective evaluation tools including Borg Rating of Perceived Exertion (Borg RPE) scale, Borg CR-10 scale, Pain Estimation Charts-The McGill Pain Questionnaire, and Visual Analog (VA) scale have also been adopted to assess physical workloads (Dadashi et al, 2022;DiDomenicoa and Nussbaum, 2008;Mehta and Agnew, 2015). Among these scales, Borg CR-10 scale is sensitive to physical demand changes (DiDomenicoa and Nussbaum, 2008;Shariat et al, 2018;Zamunér et al, 2011).…”