Optimal toolpath pattern identification for single island, sculptured part rough machining using fuzzy pattern analysis

Li, Hui; Dong, Zuomin; Vickers, G. W.

doi:10.1016/0010-4485(94)90092-2

Cited by 60 publications

(32 citation statements)

References 9 publications

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“…Feed rate clustering was introduced to improve machining productivity. The use of the cutting force prediction model led to 4 to 16 percent reduction of machining time, which translated into increased productivity and better loading on the machine tool. An analysis of the machine process model showed that the cutting force model produces conservative results due to the preferred over prediction on cutting force.…”

Section: Discussionmentioning

confidence: 99%

“…Incorporating various machining constraints, such as tool breakage and chatter, the maximum instantaneous cutting volume is maintained through out the machining process with the optimal machining parameters. The considered machining parameters include the tool path pattern, depth of cut, cross cutting depth, and feed rate [3][4][5][6]. The approach can significantly improve the productivity of sculptured part machining, ranging from 15-45 percent.…”

Section: Background and Motivationmentioning

confidence: 99%

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Machining Process Modeling for Intelligent Rough Machining of Sculptured Parts

Pop

Vickers

Dong

1999

Machining Impossible Shapes

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Abstract:Rough machining removes the excess part material and dominates the machining time of a sculptured part. Maximization of the material removal rate using optimized cutting parameters for rough machining can considerably improve productivity. This work focuses on the identification, improvement and testing of a machining process model that is generally applicable to various cutting geometry, as well as model parameters that cover a broad range of cutting conditions. A method for acquiring machining parameters of various 2 y, D milling operations for a generic cutting force model is proposed. The improved cutting force model requires few cutting tests, provides fast and accurate predictions, and supports future upgrading. Testing has shown a good agreement between predicted and measured cutting forces. A considerable saving of machining time can be achieved. BACKGROUND AND MOTIVATIONIn recent years, applications of sculptured parts increased significantly due to their unique functional and aesthetic properties, as well as the advances of new thermosetting materials and wide use of plastic materials. Machining of sculptured parts is usually completed in two stages: rough machining and finish machining. Depending on the shape of the stock and part, sometimes as much as 80 percent of the machining time is allocated to the roughing operation. A reduction of the machining time at this stage would considerably reduce machining time and consequently lower the costs of production. This objective can be accomplished by the maximization of the Material Removal Rate (MRR) and appropriate selection of cutters and cutting parameters.At present most tool path planning and programming programs for sculptured part machining focus on the accurate production of the curved surfaces. Modest attention is given to the optimization of the machining parameters to achieve the maximum productivity. This is partially due to the complex nature of the sculptured part tool path planning and programming task. Different from the cases of simple rotational and prismatic parts, rough machining of sculptured parts has to deal with constantly changing cutting volume due to the varying difference between a stock of regular shape and a part with sculptured surfaces. It is very often that conservative machining parameters are used through out the rough machining process to avoid a sudden deep cut due to the curvature change of the part to avoid any damage to the cutter, the machine and the part. This approach considerably slows down the machining and lowers productivity. In principle, this problem can be solved using the adaptive machining

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Section: Discussionmentioning

confidence: 99%

Section: Background and Motivationmentioning

confidence: 99%

Machining Process Modeling for Intelligent Rough Machining of Sculptured Parts

Pop

Vickers

Dong

1999

Machining Impossible Shapes

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“…22 With this cutting tool, the productivity of the process is improved, the machining time is reduced, and good surface finishes are obtained for planar surfaces. 19,[22][23][24] This type of tool is mostly used in three-axis machining centers during the manufacturing of prismatic components with planar surfaces. Nevertheless, it is possible to process complex surfaces depending on the chosen toolpath.…”

Section: Cutting Tool Selectionmentioning

confidence: 99%

“…This stage of the process is based on a high rate of material removal that has a significant effect on the machining time, especially for relative medium/large parts. [19][20][21] A parallel toolpath and planar cutting tool are used, as these types of cutting tool are recommended for the rough machining stage. 19,[22][23][24] The methodology is applied first to a mirror cover and then to other three automotive components.…”

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confidence: 99%

Determining the Optimum Parting Direction in Plastic Injection Molds Based on Minimizing Rough Machining Time during Mold Manufacturing

2016

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ABSTRACT:The versatility of plastic materials allows engineering components of very complex geometries and functionalities to be injection molded from them. Because the manufacturing cost of a mold increases with the complexity of the cavity, it is important to optimize the design of component and mold concurrently. In this study, a methodology for determining the optimum parting direction (PD) considering mold-manufacturing factors such as tool accessibility and the amount of material to be removed is presented. The methodology starts with an accessibility analysis in which a three-dimensional part is discretized, and candidate PDs are selected based on maximizing the accessible area, that is, the area that can be machined with a single workpiece orientation or setup. Then, the rough machining process is considered, and an optimum PD that minimizes the rough machining time for both the cavity and core plates is selected. The methodology is applied to four different automotive components: a mirror cover, an interior panel, a pillar, and a fender splash shield. C 2016 Wiley Periodicals, Inc. Adv Polym Technol 2016, 0, 21656; View this article online at wileyonlinelibrary.com.

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“…Many types of path patterns have been developed for AM, as summarized in Table 1 [13][14][15][16][17][18][19][20][21][22][23][24][25][26]. It is found that the essential step to generate paths is offsetting.…”

Section: Introductionmentioning

confidence: 99%

A practical path planning methodology for wire and arc additive manufacturing of thin-walled structures

Ding

Pan

Cuiuri

et al. 2015

Robotics and Computer-Integrated Manufacturing

262

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This paper presents a novel methodology to generate deposition paths for wire and arc additive manufacturing (WAAM). The medial axis transformation (MAT), which represents the skeleton of a given geometry, is firstly extracted to understand the geometry. Then a deposition path that is based on the MAT is efficiently generated. The resulting MAT-based path is able to entirely fill any given cross-sectional geometry without gaps. With the variation of step-over distance, material efficiency alters accordingly for both solid and thinwalled structures. It is found that thin-walled structures are more sensitive to step-over distance in terms of material efficiency. The optimal step-over distance corresponding to the maximum material efficiency can be achieved for various geometries, allowing the optimization of the deposition parameters. Five case studies of complex models including solid and thin-walled structures are used to test the developed methodology. Experimental comparison between the proposed MAT-based path patterns and the traditional contour path patterns demonstrate significant improved performance in terms of gap-free cross-sections. The proposed path planning strategy is shown to be particularly beneficial for WAAM of thin-walled structures. Abstract: This paper presents a novel methodology to generate deposition paths for wire and arc additive manufacturing (WAAM). The medial axis transformation (MAT), which represents the skeleton of a given geometry, is firstly extracted to understand the geometry. Then a deposition path that is based on the MAT is efficiently generated. The resulting MATbased path is able to entirely fill any given cross-sectional geometry without gaps. With the variation of step-over distance, material efficiency alters accordingly for both solid and thinwalled structures. It is found that thin-walled structures are more sensitive to step-over distance in terms of material efficiency. The optimal step-over distance corresponding to the maximum material efficiency can be achieved for various geometries, allowing the optimization of the deposition parameters. Five case studies of complex models including solid and thin-walled structures are used to test the developed methodology. Experimental comparison between the proposed MAT-based path patterns and the traditional contour path patterns demonstrate significant improved performance in terms of gap-free cross-sections. The proposed path planning strategy is shown to be particularly beneficial for WAAM of thin-walled structures.

show abstract

Optimal toolpath pattern identification for single island, sculptured part rough machining using fuzzy pattern analysis

Cited by 60 publications

References 9 publications

Machining Process Modeling for Intelligent Rough Machining of Sculptured Parts

Machining Process Modeling for Intelligent Rough Machining of Sculptured Parts

Determining the Optimum Parting Direction in Plastic Injection Molds Based on Minimizing Rough Machining Time during Mold Manufacturing

A practical path planning methodology for wire and arc additive manufacturing of thin-walled structures

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