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Dealing with unexpected manufacturing events: Can Decision Support Systems improve operators’performance by decreasing stress and workload?

Mailliez, Mélody and Battaïa, Olga and Roy, Raphaëlle N. Dealing with unexpected manufacturing events: Can Decision Support Systems improve operators’performance by decreasing stress and workload? (2020) In: 1st International Conference on Cognitive Aircraft Systems - ICCAS 2020, 18 March 2020 - 19 March 2020 (Toulouse, France). (Unpublished)

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Abstract

The modern manufacturing environment is very stressful for operators in charge of the production process. Unexpected events may deteriorate the operators’ performance by increasing their mental stress and workload. To overcome this phenomenon, several production scheduling and rescheduling tools have been developed. Nowadays, these decision support systems (DSS) are assumed to reduce operators’ workload because they automatically reschedule the production planning. However, findings from the literature remain equivocal. Indeed, the effect of DSS has only been reported at a subjective level and in the absence of disruptions. Given that the modern manufacturing environment is increasingly using DSS to help operators in their decisions, it is important to understand if workload can really explain the drop in operators’ performances and how they could be improved by DSS. We performed a semi-systematic literature review on six databases (PsycInfo, PsycArticles, IEEE explore, Pubmed, Google Scholar, and Web of science) regarding the effect of DSS on operators’ performance and workload. This literature review underlines the lack of research on this specific research question. As an opening, we propose a neuroergonomic experimental protocol designed to investigate this question of particular interest in rescheduling tasks. This innovative and new protocol is programmed using Matlab. Participants have to schedule the production planning (e.g. 15 tasks) on a limited number of resources (e.g. 5 machines). In some trials, unexpected events such as the unavailability of a resource may occur. As a result, participants have to reschedule all the production planning. In some of the trials, they can use the help of the decision support system that instantly proposes a new production schedule, whereas in the remaining trials they can’t use it. Workload and stress are evaluated using subjective measures (e.g. the NASA-TLX for workload, and the Perceived Stress Scale for stress), behavioral ones (e.g. accuracy and response time) as well as physiological ones (i.e. electroencephalography - EEG - and electrocardiography - ECG). This study paves the way towards developing the neuroergonomic approach on DSS use and the manufacturing environment.

Item Type:Invited Conference
Audience (conference):International conference without published proceedings
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Institution:Université de Toulouse > Institut Supérieur de l'Aéronautique et de l'Espace - ISAE-SUPAERO (FRANCE)
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Deposited On:11 May 2021 00:22

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