Industrial design change task allocation method for complex product manufacturing based on implementation intention matching

• Published in: Journal of Advanced Mechanical Design, Systems, and Manufacturing Systems, and Manufacturing, 2024, Vol.18(5), pp.JAMDSM0074-JAMDSM0074
• Main Authors: SUN, Yiwei, QIAO, Yidan, XIAO, Jianghao, CHEN, Dengkai
• Format: Article
• Language: English
• Subjects: Algorithms; Collaboration; Design analysis; Design change; Design engineering; Filtration; Implementation intention; Industrial design; Manufacturing; Manufacturing process; Product development; Similarity; Task allocation; Task complexity; Taskload; Teams
• ISSN: 1881-3054; 1881-3054
• DOI: 10.1299/jamdsm.2024jamdsm0074

Industrial design change task refers to the task resulting from industrial design schemes changing processes due to manufacturing needs in complex product development. In order to make full use of the experience generated in design design change, this paper proposes an industrial design change task allocation method based on implementation intention. Based on the action stage model, the connotation of the implementation intention of industrial design tasks is proposed. Based on the state of the design change, the design team and design task model are constructed through the Extenics theory. A quantitative model of implementation intention and an evaluation method for generalization are constructed. The similarity between the design tasks and the support of the design team for the design tasks are quantified and calculated by the complex network. For change design tasks other than design activities, the collaborative filtering algorithm is improved to achieve design team recommendations based on task similarity. In the process of collaborative filtering, the relationship between tasks is considered, and the time loss caused by the propagation of tasks among different teams is evaluated to improve the effectiveness of the task allocation scheme. Take the change in the internal facility manufacturing requirements of the intelligent cabin as an example. Compared to the design process before applying this method, the task load of design teams was reduced by 18.74 %, which proved this method can support industry design change problems.