Computer-Aided Design and Engineering for Advanced Manufacturing Systems
Advanced computer-aided design and engineering methodologies for modern manufacturing systems, integrating digital design tools with manufacturing process optimization.
Authors
Y. Wang, K. Shimada
Publication Details
Computer-Aided Design and Engineering for Advanced Manufacturing Systems
This research develops advanced computer-aided design and engineering methodologies for modern manufacturing systems, addressing critical challenges of design complexity, manufacturing integration, digital transformation, and optimization requirements for accelerated time-to-market. The work creates comprehensive integrated design environments with parametric modeling, multi-physics simulation capabilities, design optimization with automated parameter adjustment, and knowledge-based design systems with expert rules. Key technical innovations include multi-objective optimization with genetic algorithms and topology optimization, design for manufacturing with manufacturability analysis and cost estimation, virtual manufacturing with digital factory modeling and simulation, digital twin technology for real-time physical-digital synchronization, and seamless CAD/CAM/CAE software interoperability with PLM system integration and cloud-based collaboration platforms.
Automotive and aerospace manufacturing applications benefit from engine component design optimization, aircraft structural component development, crashworthiness analysis, lightweight design with material optimization, and composite material design with assembly sequence planning. The work demonstrates significant improvements in design accuracy, reduced manufacturing lead times, improved first-time-right production rates, decreased material waste, and enhanced product quality through comprehensive validation in real-world manufacturing environments. Manufacturing companies and engineering teams can leverage this expertise for developing next-generation design systems, implementing artificial intelligence and machine learning integration, advancing generative design and algorithmic exploration, creating virtual and augmented reality immersive design capabilities, and establishing sustainable design practices that enable mass customization, distributed manufacturing, human-centered design, and service-oriented product development with continuous improvement and competitive advantage.
Note: Generated via condensation from detailed technical content. Full research specifications available in original publication: 23-jcde-yuyang-wang.pdf
Publication Info
Venue
Journal of Computing and Design Engineering (JCDE)
Volume
10
Pages
214-223
Year
2023
DOI
10.1093/jcde/xxxxxxx
Topics