4.6 Article

Classification and Quantification of Human Error in Manufacturing: A Case Study in Complex Manual Assembly

Journal

APPLIED SCIENCES-BASEL
Volume 11, Issue 2, Pages -

Publisher

MDPI
DOI: 10.3390/app11020749

Keywords

human reliability analysis; manual assembly; human error; quality; ergonomics

Funding

  1. MITACS [IT12360]
  2. Natural Sciences and Engineering Research Council of Canada (NSERC)

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This study utilized SHERPA and HEART techniques to analyze human reliability in manual assembly operations, identifying error modes and probabilities in critical tasks. The research indicated that perceptually engaging assembly instructions and improving the inspection process have the potential to reduce assembly errors and enhance worker performance.
Manual assembly operations are sensitive to human errors that can diminish the quality of final products. The paper shows an application of human reliability analysis in a realistic manufacturing context to identify where and why manual assembly errors occur. The techniques SHERPA and HEART were used to perform the analysis of human reliability. Three critical tasks were selected for analysis based on quality records: (1) installation of three types of brackets using fasteners, (2) fixation of a data cable to the assembly structure using cushioned loop clamps and (3) installation of cap covers to protect inlets. The identified error modes with SHERPA were: 36 action errors, nine selection errors, eight information retrieval errors and six checking errors. According to HEART, the highest human error probabilities were associated with assembly parts sensitive to geometry-related errors (brackets and cushioned loop clamps). The study showed that perceptually engaging assembly instructions seem to offer the highest potential for error reduction and performance improvement. Other identified areas of action were the improvement of the inspection process and workers' provision with better tracking and better feedback. Implementation of assembly guidance systems could potentially benefit worker's performance and decrease assembly errors.

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