<p>With manufacturing companies facing societal and economic challenges, their error risk in manual assembly lines is increasing. A demographic change can be observed in many industrialized countries, negatively influencing performance levels. Furthermore, a shortage of skilled workers with the required qualifications is another challenge for companies. The increasing product variance and the pressure regarding costs, quality, and time imply a higher load on the employees. This discrepancy between rising load and potentially diminishing performance levels can lead to increasing errors in manual assembly. Developing a taxonomy of error-influencing factors for manual assembly lines is a crucial step, as it enables a systematic decision on preventive measures to hinder the development of errors. This contribution introduces this taxonomy, which is the core of the research and is based on a structured literature review, numerous expert interviews, and an expert workshop. Furthermore, a method for selecting the most relevant error-influencing factors for companies’ individual use cases is presented, offering a practical solution to a pressing industry problem.</p>

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A methodology for the prioritization of factors influencing human errors in manual assembly lines

  • Bjoern Klages,
  • Annina Metzner,
  • Michael F. Zaeh

摘要

With manufacturing companies facing societal and economic challenges, their error risk in manual assembly lines is increasing. A demographic change can be observed in many industrialized countries, negatively influencing performance levels. Furthermore, a shortage of skilled workers with the required qualifications is another challenge for companies. The increasing product variance and the pressure regarding costs, quality, and time imply a higher load on the employees. This discrepancy between rising load and potentially diminishing performance levels can lead to increasing errors in manual assembly. Developing a taxonomy of error-influencing factors for manual assembly lines is a crucial step, as it enables a systematic decision on preventive measures to hinder the development of errors. This contribution introduces this taxonomy, which is the core of the research and is based on a structured literature review, numerous expert interviews, and an expert workshop. Furthermore, a method for selecting the most relevant error-influencing factors for companies’ individual use cases is presented, offering a practical solution to a pressing industry problem.