Hybrid Manufacturing Process Planning for Arbitrary Part and Tool Shapes. (October 2022)

• Record Type: Journal Article
• Authors: Harabin, George P.; Behandish, Morad
• Is Part Of: Computer aided design. Volume 151(2022)
• Publication Date: 2022-10
• Subjects: Hybrid manufacturing -- Process planning -- Spatial reasoning -- Additive manufacturing -- Machining; 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.2022.103299
• Languages: English
• ISSNs: 0010-4485

Abstract

Abstract: Hybrid manufacturing (HM) technologies combine additive and subtractive manufacturing (AM/SM) capabilities in multi-modal process plans that leverage the strengths of each. Despite the growing interest in HM technologies, software tools for process planning have not caught up with advances in hardware and typically impose restrictions that limit the design and manufacturing engineers' ability to systematically explore the full design and process planning spaces. We present a general framework for identifying AM/SM actions that make up an HM process plan based on accessibility and support requirements, using morphological operations that allow for arbitrary part and tool geometries to be considered. To take advantage of multi-modality, we define the actions to allow for temporary excessive material deposition or removal, with an understanding that subsequent actions can correct for them, unlike the case in unimodal (AM-only or SM-only) process plans that are monotonic. We use this framework to generate a combinatorial space of valid, potentially non-monotonic, process plans for a given part of arbitrary shape, a collection of AM/SM tools of arbitrary shapes, and a set of relative rotations (fixed for each action) between them, representing build/fixturing directions on 3-axis machines. Finally, we define a simple objective function quantifying the cost of materials and operating time in terms of deposition/removal volumes and use a search algorithm to explore the exponentially large space of valid process plans to find "cost-optimal" solutions. We demonstrate the effectiveness of our method on 3D examples. Graphical abstract: Highlights: Enable hybrid manufacturing process planning for arbitrary part and tool geometries. Define a discrete search space of additive and subtractive manufacturing actions. Use set-theoretic morphological operations to define manufacturing actions. Satisfy accessibility, minimum feature size/shape, and support requirements. Use conservative (under-fill or over-cut) or aggressive (over-fill or under-cut) policies. Use iterative deepening A* search to find cost-effective and valid process plans.