Machine learning becomes much more widespread than before. So finally it’s time to implement it in computer aided design too.
The short list of possible applications of the artificial intelligence within the Mechanical Engineering and Architecture, Engineering, and Construction with the high-level descriptions is provided below. On some of them I am working at the moment. This is not entire list, but allows to understand how useful and cutting-edge this technology is.
Systems engineering approach
Implement and support the linkage between: system model, interactions between subsystem and implementation of this system in geometry model.
Perform the work breakdown structure and workflow generation, according to the standardized workflows, early performed by users.
Part library categorization
Categorize parts across libraries by their shapes and parameters.
Parametrizing of non-parametric solids
Parametrize STL and IGES, using geometry parsers and library of standard parameters for the parts and assemblies.
Natural language user interface
Interaction with CAD systems using text or voice conversation in natural language: review the model (pan, rotate, zoom, comments, etc.), call common commands and perform input.
Design wizards and generators
Improving the behavior of wizards and generators according to standards and technical specification of overall project.
- Fasteners generator
- Frame generator
- Mold-base generator for casting and molding
- Hole generator
- Thread generator
Handling of Agile/Scrum development process
PDM/PLM management according to Agile/Scrum methodologies. Schedule meetings of engineers and other involved persons. Handle the data and update project and parts properties appropriately according to the decisions. Perform the work breakdown structure according to technical specifications and recommendations for further implementation and supervision.
Verification of conformity to standards
Design check of performed design operations according to standards and technical specifications.
Manage the heritage of scanned drawings and blueprints, performing further using of this data in Civil engineering, AEC and mechanical engineering. This includes: parsing, recognition, data extraction, automated build of 3D models, etc.
Applications for Mechanical engineering
Improved part selection according to system model of design, technical specification and standards.
Constraints within assembly
Intelligent setting of constraints with reduced user interaction.
Applications for AEC
Tracing of HWAC, electricity and engineering systems
Perform tracing of HWAC, electricity, engineering systems, structured cabling, etc. systems according to the design.
Reinforcement and structural system generators
Calculating optimal reinforcement and structural systems and appropriate documentation.
Construction process verification
Compare ‘as designed’ vs ‘as built’ using data from 3D scanners, etc.
Exploitation and management
Cost-efficient management of building according to the data from different type of sensors.
The matrix of ML algorithms applied to possible applications is provided below:
|Systems engineering approach||●|
|Part library categorization||●||●|
|Parametrizing of non-parametric solids||●||●||●|
|Natural language user interface||●|
|Design wizards and generators||●|
|Handling of Agile/Scrum development process||●|
|Verification of conformity to standards||●||●|
|Constraints within assembly||●||●|
|Tracing of HWAC, electricity and engineering systems||●||●|
|Reinforcement and structural system generators||●||●|
|Construction process verification||●||●||●|
|Exploitation and management||●||●||●|