Computer-Aided Manufacturing and Design
Material type:
ArticleLanguage: English Publication details: Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2020Description: 1 electronic resource (198 p.)ISBN: - books978-3-03943-135-9
- 9783039431342
- 9783039431359
- History of engineering & technology
- product service system (PSS)
- availability
- field repair kit
- gradient-based algorithm
- robust genetic algorithm
- warpage
- design of experiments
- fringe pattern
- birefringence
- automatic design
- intelligent optimization method
- CFD
- fluid machinery
- pumps
- multi-function console
- data-driven design
- mismatch equation
- anthropometric measures
- algorithmic approach
- optimal design
- stretchable antenna-based strain sensor
- structural optimization
- structural health monitoring
- dimension reduction
- entropy-based correlation coefficient
- multidisciplinary design and analysis
- uncertainty-integrated and machine learning-based surrogate modeling
- additive manufacturing
- complexity
- modular design
- part consolidation
- product recovery
- product image design
- Kansei Engineering
- integrated decision system
- qualitative decision model
- quantitative decision model
- train seats
- measurement-assisted assembly
- coordination space
- assemblability
- small displacement torsor
- Kriging
- lower confidence bounding
- entropy theory
- product design
- simulation-based design optimization
- convolutional neural network
- object detection
- piping and instrument diagram
- unsupervised learning
- n/a
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Recent advancements in computer technology have allowed for designers to have direct control over the production process through the help of computer-based tools, creating the possibility of a completely integrated design and manufacturing process. Over the last few decades, "artificial intelligence" (AI) techniques, such as machine learing and deep learning, have been topics of interest in computer-based design and manufacturing research fields. However, efforts to develop computer-based AI to handle big data in design and manufacturing have not yet been successful. This Special Issue aims to collect novel articles covering artificial intelligence-based design, manufacturing, and data-driven design. It will comprise academics, researchers, mechanical, manufacturing, production and industrial engineers and professionals related to engineering design and manufacturing.
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