Archetypes of assistance systems and their impacts on manufacturing performance and job quality

As workplaces become increasingly complex, manufacturing companies must adopt technologies that not only fulfill customer requirements but also prioritize high-quality jobs for production workers. Assistance systems are gaining popularity because they can enhance manufacturing performance and support sufficient job quality. However, there is a lack of detailed insights into the application-specific impact of the systems. This study classifies the use of assistance systems in manufacturing, deriving characteristic archetypes and mapping their impacts through a systematic review of existing literature. Analyzing 56 cases from 40 studies using descriptive and cluster analysis, four main archetypes are identified: (1) manually operated physical execution support for routine assembly tasks, (2) automatically operated and adaptable visual task guidance for routine assembly tasks, (3) automatically operated and adaptive visual support for non-routine diagnostics tasks, and (4) automatically operated and adaptive physical execution support for routine assembly. Findings suggest that these archetypes offer potential benefits and risks for job quality and manufacturing performance. However, their successful use requires careful consideration of role division, task execution capabilities, task support capabilities, and long-term impacts. The current literature on assistance systems needs more longitudinal empirical studies to provide clear guidance for both researchers and industry practitioners. • Assistance system archetypes based on their technological capabilities and manufacturing applications. • A systematic literature review of papers (2015 to 2024) assessing the application-specific impact of assistance systems on manufacturing performance or job quality. • Four assistance system archetypes, based on 56 manufacturing application cases, emerge from a cluster analysis. • Determining factors for the varying impact of assistance system archetypes on job quality and manufacturing performance remain unclear. • Assistance system literature requires an in-depth assessment of role division, task execution capabilities, task support capabilities, and long-term impacts to establish determining factors.