Manuscript Topics

The rapid development of additive manufacturing (AM) technology has revolutionized the computer-aided systems for product design, manufacturing, assembly, supply chain management, maintenance, recycling and many other aspects. The unprecedented manufacturing capability and flexibility of AM has greatly complicated these activities and made great demands on data-driven, knowledge-based, computing-intensive systems to unleash the creativities and automate the complex missions. Taking feature technology for example, the traditional design-by-feature technology is now replaced by the generative design methods, wherein computational intelligence automates the product design. Functional features are more focused rather than manufacturability issues owing to the superior geometric complexity handling of AM. On the other hand, the paradigm shift is far from complete. There are still many computer-aided systems that lack knowledge discovery and intelligent usage of knowledge. For example, process planning for hybrid additive-subtractive manufacturing has very low-level automation which mainly counts on manual efforts to interpret the process planning knowledge and performs the operations. Therefore, more sophisticatedly developed systems mixing techniques of artificial intelligence, computational graphics, numerical optimization, and computational mechanics are expected to address the challenges in developing CAx systems for AM.

To address the above issues, this special issue is dedicated to bringing together researchers with diverse research backgrounds into a common forum, contributing thoughts to this cutting-edge research topic, and accelerating the development of AM technology with the aid of knowledge-based CAx systems. The topics of this special issue include, but are not limited to the following:

• Generative design-for-AM
• Artificial intelligence in design-for-AM
• Design-for-social AM  
• Intelligent systems for tolerance management and model compensation
• Intelligent systems for part consolidation/deconsolidation decision making
• Automation in process planning for multi-axis AM
• Automation in process planning for hybrid additive-subtractive manufacturing
• Supply chain management with AM
• Intelligent systems for AM-based remanufacturing decision making

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