Workload Assessment for Manual and Automated Processes in Life Sciences

Abstract

In life science process development, optimized manual protocols are converted to semi-automated processes to address high throughput and accuracy demands and to promote technician safety. However, little research has been conducted on technician workload assessment as a basis for identifying and prioritizing automation targets. The objectives of this study were to: 1) assess technician workload in a manual protocol and identify automation “targets” (for load reduction); and 2) compare workload with prototype automation vs. purely manual performance. Three expert technicians performed a mercury analysis process for three replications. Perceived workload was collected for each task using the NASA-Task Load index (TLX). Results on the manual process indicated “pipetting” and “measuring/recording” tasks to pose significantly higher perceived workload. The pipetting task posed the highest mental demand and risk of repetitive strain injuries, and was identified as a priority automation target. An automated pipetting system was prototyped and integrated in the manual protocol. The technician’s role was changed to transporting materials and programming tasks. In general, findings indicate that perceived workload assessment can be used to effectively identify target tasks for automation in life science processes. Technicians perceived significantly lower workload when performing automated pipetting, as compared with manual performance. However, there may be other factors (e.g., task time, number of steps) that influence workload and such factors may represent other targets for automation.

Keywords: Cognitive Workload, Human-Automation Interaction, Life Sciences, Tasks Analysis

DOI: 10.54941/10015