ABSTRACT
This chapter provides an introductory overview of workload assessment and its applications in modern industry. It begins by defining the workload construct and its basis in cognitive neuroscience. Applications of workload measurement broadly include improving productivity, safety, and employee wellbeing. There are multiple methods used to assess workload, including self-report, psychophysiological, and behavioral (performance-based) measures. All have strengths, limitations, and challenges that practitioners should be aware of. In this chapter, criteria for evaluating workload measures for reliability, validity, and practical utility are provided. Industrial applications for workload assessment are illustrated in relation to the manufacturing industry, transportation, and power generation. Relevant issues include designing interfaces and systems to support the user, the impacts of sudden transitions in workload, managing the challenges of underload, and enhancing organizational support and the work environment. The nuclear power industry provides an example of how workload assessment contributes to maintaining plant safety. The manufacturing industry, along with other domains such as power generation and transportation, is being transformed by digital technologies for autonomous operations and AI. These issues are discussed in the context of advancements in technology and the assessment challenges for future industrial applications, including digitalized nuclear power plants. We conclude with summary points that capture the main issues in workload assessment for industrial applications.
