In a market, which demand highly customized products, workers face a great amount of complex tasks. To support them, the automotive industry has progressively adopted new innovative systems, called assistance systems. This human-system collaboration combines the effective characteristics of a system with humans’ unique cognitive skills. Due to the great value and variety of assistance systems, companies encounter big challenges when deciding in which one they should invest. So far, traditional criteria to evaluate manufacturing systems focus on their performance. These indicators could be grouped into economic factors, efficiency, quality, maturity and flexibility. Nonetheless, they fail to assess assistance systems, suggesting that the classic criteria might not be sufficient to encompass all the characteristics of those system. A promising approach, which could overcome these shortcomings, is considering user acceptance as a decisive criterion. This thesis presents a comparative between the traditional and the new criteria. For this purpose, pairwise comparisons and interviews with experts in the automotive field are conducted. This research reveals the importance of user acceptance for a system’s successful implementation. Additionally, an approach is presented to estimate the perceived acceptance by users. This method is validated through the evaluation of a smart watch, with a specific industrial application. In conclusion, the results showed that user acceptance should be included in methods that assess assistance systems. Furthermore, the approach to estimate user acceptance allows a more detailed analysis of users’ perceptions towards an assistance system.

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