Literature DB >> 15204272

Identifying the task variables that influence perceived object assembly complexity.

Miles Richardson1, Gary Jones, Mark Torrance.   

Abstract

There is a general lack of understanding as to what issues affect assembly task performance when using diagrammatic instructions because few of the task variables contributing to assembly complexity have been identified. Using a task analysis of a range of self-assembly products, seven task variables hypothesized to predict assembly complexity were identified and studied in the instruction comprehension phase of assembly. Experiment 1 took nine real world assembly instructions and described each in terms of the seven task variables. Seventy-two participants gave a subjective rating of assembly difficulty for each assembly, showing a clear relationship between the task variables and perceived assembly difficulty. As real world assemblies provide little control a second experiment used an orthogonal design to systematically vary the values of each of the assembly task variables in 16 abstract assemblies. Forty-two participants compared the 16 assembly instructions to a final assembly. There was a clear relationship between the task variables and the time taken to view the instructions. Further, it was found that it is possible to predict the complexity of assembly tasks based upon the levels of the task variables identified. The task variables identified are a significant step towards identifying the factors that influence assembly complexity, together with providing progress towards a tool for predicting assembly complexity.

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Year:  2004        PMID: 15204272     DOI: 10.1080/00140130410001686339

Source DB:  PubMed          Journal:  Ergonomics        ISSN: 0014-0139            Impact factor:   2.778


  2 in total

1.  Influences of Augmented Reality Assistance on Performance and Cognitive Loads in Different Stages of Assembly Task.

Authors:  Zhen Yang; Jinlei Shi; Wenjun Jiang; Yuexin Sui; Yimin Wu; Shu Ma; Chunyan Kang; Hongting Li
Journal:  Front Psychol       Date:  2019-07-24

2.  The Binary-Based Model (BBM) for Improved Human Factors Method Selection.

Authors:  Matt Holman; Guy Walker; Terry Lansdown; Paul Salmon; Gemma Read; Neville Stanton
Journal:  Hum Factors       Date:  2020-06-18       Impact factor: 2.888

  2 in total

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