Abstract
Manufacturing companies operate software for the manual collection of process data on the shop floor. A volatile utilization of such software by operators leads to insufficient data quality. The affected companies have difficulties to understand and improve the performance of their assembly processes. We design software to capture data on production disruptions for a manual assembly of complex products. This research investigates the operator's intention to use this software in a single case study. Thus, we conduct software tests and interviews with 51 potential users deploying the technology acceptance model 2 questionnaire. We find that the determinants perceived usefulness and job relevance are predictors for the intention to use software for manual data collection in the investigated context.
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