A technology of efficient configuration of a ship’s critical process equipment

ABSTRACT

The design efficiency of the technological equipment determines the product development cycle, and its design scheme relies mainly on the experience of the designer. This study proposes a rapid design method for intelligent configuration of fixture bill of material (BOM) structures based on machine learning. Firstly, the technical support intelligent CAD system are introduced, which consists of the model and technical route planning required for fixture design. Secondly, a process model is established through the model-based definition (MBD). The angle cosine algorithm of the n-dimensional vector is used to calculate the similarity between the new model and the library model, which intelligently infer the best similar model. Then, the virtual assembly BOM structure of a similar case is transformed into a 3D configurable BOM structure. Based on the above models, the assembly structure of technological equipment is automatically configured with machine learning. Finally, the corresponding technological equipment design system was developed and verified through a case study, and the results show that the proposed method can improve resource utilization and design efficiency. Therefore, enabling users to quickly design 3D models of complex products.

KEYWORDS:

• Similarity retrieval
• machine learning
• configurable structure
• technological equipment design

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This work was supported by the National Defense Basic Scientific Research Foundation [A0720133010].