Display options
Cite
Strenge B, Schack T. Empirical relationships between algorithmic SDA-M-based memory assessments and human errors in manual assembly tasks. Sci Rep. 2021;11(1):9473doi: 10.1038/s41598-021-88921-1.
Strenge, B., & Schack, T. (2021). Empirical relationships between algorithmic SDA-M-based memory assessments and human errors in manual assembly tasks. Scientific reports, 11(1), 9473. https://doi.org/10.1038/s41598-021-88921-1
Strenge, Benjamin, and Schack, Thomas. "Empirical relationships between algorithmic SDA-M-based memory assessments and human errors in manual assembly tasks." Scientific reports vol. 11,1 (2021): 9473. doi: https://doi.org/10.1038/s41598-021-88921-1
Strenge B, Schack T. Empirical relationships between algorithmic SDA-M-based memory assessments and human errors in manual assembly tasks. Sci Rep. 2021 May 04;11(1):9473. doi: 10.1038/s41598-021-88921-1. PMID: 33947879; PMCID: PMC8097020.
Copy Download .nbib Format: NLM
Share it on

Sci Rep. 2021 May 04;11(1):9473. doi: 10.1038/s41598-021-88921-1.

Empirical relationships between algorithmic SDA-M-based memory assessments and human errors in manual assembly tasks.

Scientific reports

Benjamin Strenge, Thomas Schack

Affiliations

  1. Center for Cognitive Interaction Technology (CITEC), Neurocognition and Action Group, Bielefeld University, 33615, Bielefeld, Germany. [email protected].
  2. Center for Cognitive Interaction Technology (CITEC), Neurocognition and Action Group, Bielefeld University, 33615, Bielefeld, Germany.

PMID: 33947879 PMCID: PMC8097020 DOI: 10.1038/s41598-021-88921-1

Abstract

The majority of manufacturing tasks are still performed by human workers, and this will probably continue to be the case in many industry 4.0 settings that aim at highly customized products and small lot sizes. Technical systems could assist on-the-job training and execution of these manual assembly processes, using augmented reality and other means, by properly treating and supporting workers' cognitive resources. Recent algorithmic advancements automatized the assessment of task-related mental representation structures based on SDA-M, which enables technical systems to anticipate mistakes and provide corresponding user-specific assistance. Two studies have empirically investigated the relations between algorithmic assessments of individual memory structures and the occurrences of human errors in different assembly tasks. Hereby theoretical assumptions of the automatized SDA-M assessment approaches were deliberately violated in realistic ways to evaluate the practical applicability of these approaches. Substantial but imperfect correspondences were found between task-related mental representation structures and actual performances with sensitivity and specificity values ranging from 0.63 to 0.72, accompanied by prediction accuracies that were highly significant above chance level.

References

  1. Front Psychol. 2016 Jan 08;6:1981 - PubMed
  2. Front Psychol. 2020 Dec 21;11:597913 - PubMed
  3. Clin Rehabil. 2007 Sep;21(9):822-32 - PubMed
  4. PLoS One. 2014 Apr 17;9(4):e95175 - PubMed
  5. Front Robot AI. 2019 Jun 21;6:43 - PubMed
  6. Psychol Rev. 2004 Oct;111(4):1036-60 - PubMed
  7. Front Hum Neurosci. 2014 May 22;8:328 - PubMed
  8. PLoS One. 2019 Feb 22;14(2):e0212414 - PubMed
  9. Clin Rehabil. 2018 Jan;32(1):103-115 - PubMed
  10. Neurosci Lett. 2006 Jan 2;391(3):77-81 - PubMed
  11. Prog Brain Res. 2009;174:231-50 - PubMed

Publication Types