Based on virtual maintenance, this paper aims to propose a time prediction method of assembly and disassembly (A&D) actions of product maintenance process to enhance existing methods’ prediction accuracy, applicability and efficiency.
First, a framework of A&D time prediction model is constructed, which describes the time prediction process in detail. Then, basic maintenance motions which can comprise a whole A&D process are classified into five categories: body movement, working posture change, upper limb movement, operation and grasp/placement. A standard posture library is developed based on the classification. Next, according to motion characteristics, different time prediction methods for each motion category are proposed based on virtual maintenance simulation, modular arrangement of predetermined time standard theory and the statistics acquired from motion experiment. Finally, time correction based on the quantitative evaluation method of motion time influence factors is studied so that A&D time could be predicted with more accuracy.
Case study of time prediction of products’ various A&D processes is conducted by implementing the proposed method. The prediction process of diesel cooling fan disassemble time is presented in detail. Through comparison, the advantages and effectiveness of the method are demonstrated.
This paper proposes a more accurate, efficient and applicable product A&D time prediction method. It can help designers predict A&D time of a product maintenance accurately in early design phases without a physical prototype. It can also provide basis for the verification of maintainability, the balance of the design of product structure and system layout.
Cai, K., Zhang, W., Chen, W. and Zhao, H. (2019), "A study on product assembly and disassembly time prediction methodology based on virtual maintenance", Assembly Automation, Vol. 39 No. 4, pp. 566-580. https://doi.org/10.1108/AA-12-2017-177Download as .RIS
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