Topology Optimization for Manufacturing with Accessible Support Structures. (January 2022)

• Record Type: Journal Article
• Authors: Mirzendehdel, Amir M.; Behandish, Morad; Nelaturi, Saigopal
• Is Part Of: Computer aided design. Volume 142(2022)
• Publication Date: 2022-01
• Subjects: Design for manufacturing -- Topology optimization -- Support structures -- Accessibility analysis -- Multi-axis machining -- Hybrid manufacturing; Computer-aided design -- Periodicals; Engineering design -- Data processing -- Periodicals; Computer graphics -- Periodicals; Conception technique -- Informatique -- Périodiques; Infographie -- Périodiques; Computer graphics; Engineering design -- Data processing; Periodicals; Electronic journals; 620.00420285
• DOI: 10.1016/j.cad.2021.103117
• Languages: English
• ISSNs: 0010-4485

Abstract

Abstract: Metal additive manufacturing (AM) processes often fabricate a near-net shape that includes the as-designed part as well as the sacrificial support structures that need to be machined away by subtractive manufacturing (SM), for instance multi-axis machining. Thus, although AM is capable of generating highly complex parts, the limitations of SM due to possible collision between the milling tool and the workpiece can render an optimized part non-manufacturable. We present a systematic approach to topology optimization (TO) of parts for AM followed by SM to ensure removability of support structures, while optimizing the part's performance. A central idea is to express the producibility of the part from the near-net shape in terms of accessibility of every support structure point using a given set of cutting tool assemblies and fixturing orientations. Our approach does not impose any artificial constraints on geometric complexity of the part, support structures, machining tools, and fixturing devices. We extend the notion of inaccessibility measure field (IMF) to support structures to identify the inaccessible points and capture their contributions to non-manufacturability by a continuous spatial field. IMF is then augmented to the sensitivity field to guide the TO towards a manufacturable design. The approach enables efficient and effective design space exploration by finding nontrivial complex designs whose near-net shape can be 3D printed and post-processed for support removal by machining with a custom set of tools and fixtures. We demonstrate the efficacy of our approach on nontrivial examples in 2D and 3D. Highlights: Topology optimization for AM then-SM hybrid manufacturing Incorporate accessibility constraint for support removal in topology optimization A support removal planning algorithm to detach the part from the platform. Multiple benchmark and realistic examples in 2D and 3D.