Exact Tool Sizing for Feature Accessibility

Lim, Theodore; Corney, Jonathan; Clark, D. E. R.

doi:10.1007/s001700070013

Cited by 31 publications

(10 citation statements)

References 11 publications

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“…In fact, Steps 1' and 2' seem so obvious that they are standardly used in algorithms for computing the area of B [9,10]. However, there are a few cases in which Steps 1' and 2' will lead to incorrect results.…”

Section: ' a -Kca'mentioning

confidence: 98%

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A geometric algorithm for selecting optimal set of cutters for multi-part milling

Yao

Gupta

Nau

2001

Proceedings of the Sixth ACM Symposium on Solid Modeling and Applications

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For the manufacture of milled parts, it is well known that the size of the cutter significantly affects the machining time. However, for small-batch manufacturing, the time spent on loading tools into the tool magazine and establishing z-length compensation values is just as important. If we can select a set of milling tools that will produce good machining time on more than one type of parts, then several unnecessary machine-tool reconfiguration operations can be eliminated. This paper describes a geometric algorithm for finding an optimal set of cutters for machining a set of 2½D parts. In selecting milling cutters we consider both the tool loading time and the machining time and generate solutions that allow us to minimize the total machining time. Our problem formulation addresses the general problem of how to cover a target region to be milled with a cylindrical cutter without intersecting with the obstruction region; this definition allows us to handle both open and closed edges in the target region. Our algorithm improves upon previous work in the tool selection area in following ways: (1) in selecting cutters, it accounts for the tool loading time, and (2) it can simultaneously consider multiple different parts and select the optimal set of cutters to minimize the total manufacturing time.

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Section: ' a -Kca'mentioning

confidence: 98%

“…Most existing cutter selection algorithms select milling cutters by minimizing the machining time and do not account for tool loading time [1,2,5,6,7,8,9,10,11,12,13,14]. In most cases, the existing algorithms will recommend using a different set of cutters for each new type of part.…”

Section: Introductionmentioning

confidence: 98%

A geometric algorithm for selecting optimal set of cutters for multi-part milling

Yao

Gupta

Nau

2001

Proceedings of the Sixth ACM Symposium on Solid Modeling and Applications

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“…Clark (2000) use a proprietary feature finder to reduce parts to simple features, and used offset curves to determine tool accessibility [7][8]. They pioneer the method of allowing the feature finder to determine the smallest radius in the feature, and automatically selecting a tool based on that radius.…”

Section: List Of Tablesmentioning

confidence: 99%

Automated Estimation of Time and Cost for Determining Optimal Machining Plans

Blarigan

Campbell

Eftekharian

et al. 2012

Volume 2: 32nd Computers and Information in Engineering Conference, Parts a and B

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In any manufacturing setting, producing a machined part is a complicated, multi-step process. It requires coordination between an engineer and a machinist to ensure all goals are met. A machinist creates a part based generally on personal experience and intuition, and while they know that this will result in the finished product, it is not guaranteed that the process plan chosen is the quickest or least expensive way to make the part. In the past year, we have been developing an automated tool that analyzes a solid model to determine its best process plan. The tool is essentially comprised of a reasoning engine that determines what processes are valid for particular sections of the part, and an evaluation engine that estimates the time and cost of the candidate processes. This paper presents the implemented evaluation engine, which assigns individual values of time and cost to machine operations. The evaluation starts with an automated tool selection strategy. The engineering model is able to determine the machining time of the tool(s) chosen. The method presented here takes a unique approach to machining time estimation that balances the trade-off between accuracy and computational time. Preliminary results suggest that the method is able to achieve accuracy near that of commercial CAM packages, with a much lower computational expense. The evaluation model takes into account non-productive manufacturing times (e.g. fixturing, inspection), and translates these to related costs. The method will be presented and discussed in this paper along with some preliminary results.

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“…Lim et al (2000), propose a methodology for exact tool sizing for feature accessibility, based on an algorithm for computing the volume of a 2D profile accessible to a given tool using offset operators. In Lim et al (2001), a greedy heuristic to select cutters based on cutting times determined using un-machined areas is developed.…”

Section: Multiple Tool Selection For Pocket Machining -A Reviewmentioning

confidence: 99%

“…In modern CAD/CAM systems, the task of cutter specification is typically left to the user (Veeramani and Gau 1997, Lim et al 2000, D'Souza et al 2001. Furthermore, most systems do not provide any support for geometrical analysis of cutter selection (Lim et al 2001).…”

Section: Introductionmentioning

confidence: 99%

Optimal tool selection for 2.5D milling, part 2: a Voronoi mountain approach for generalized pocket geometries

Seth¹,

Stori²

2005

International Journal of Computer Integrated Manufacturing

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Cutter selection is a critical subtask of machining process planning. In part 2 of this twopart series, we develop a robust approach for the selection of an optimal sequence of milling cutters. We rely on the Voronoi mountain construction algorithm developed in part 1 to support generalized pocket geometries containing multiple obstruction regions and contours consisting of circular arc and linear segments. Open edges are supported in both the original pocket contours as well as the intermediate edges that bound removal regions for subsequent tools in the optimal sequence. Exact tool-path lengths are computed for the multiple tool sequences rather than relying on area-based estimates of machining time and cost. An externally supplied table of machining technology data is required to drive the tool selection algorithm.

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Exact Tool Sizing for Feature Accessibility

Cited by 31 publications

References 11 publications

A geometric algorithm for selecting optimal set of cutters for multi-part milling

A geometric algorithm for selecting optimal set of cutters for multi-part milling

Automated Estimation of Time and Cost for Determining Optimal Machining Plans

Optimal tool selection for 2.5D milling, part 2: a Voronoi mountain approach for generalized pocket geometries

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