Methodology for complexity and cost comparison between subtractive and additive manufacturing processes

被引:11
作者
Touze, S. [1 ]
Rauch, M. [1 ]
Hascoet, J-Y [1 ]
机构
[1] Ecole Cent Nantes, Inst Rech Genie Civil & Mecan GeM, UMR CNRS 6183, 1 Rue Noe, F-44321 Nantes, France
关键词
Additive manufacturing; Machining; Manufacturing complexity; Costing; Octree decomposition; Raycasting; DESIGN; SYSTEM;
D O I
10.1007/s10845-022-02059-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This works presents a methodology, along with its software implementation called "Design 2 Cost ", for evaluating the manufacturing cost and complexity of a part built by a subtractive (e.g. milling) or additive (e.g. laser metal deposition, Selective laser melting, wire-arc additive manufacturing) process. The overall manufacturing complexity is calculated as a weighted average of morphological and material criteria, which are defined either locally or globally. The local morphological criteria are calculated over the leaf nodes of an octree representation of the part using a raycasting technique. This allows to efficiently probe the local geometry of the part and compare it with manufacturing constraints emanating from the manufacturing process and its associated effector. This algorithm yields a cartography of the local complexity criteria that helps visualizing the problematic regions for the processes under consideration. The software is accompanied by a database that feeds the required material and process properties needed for the calculation of the manufacturing complexity and cost. The proposed methodology therefore permits a technical and economic comparison of manufacturing processes for a given geometry and material, as well as a comparison of various part geometries and materials for a given manufacturing process.
引用
收藏
页码:555 / 574
页数:20
相关论文
共 20 条
[1]   QUANTIFYING THE ROLE OF PART DESIGN COMPLEXITY IN USING 3D SAND PRINTING FOR MOLDS AND CORES [J].
Almaghariz, Eyad S. ;
Conner, Brett P. ;
Lenner, Lukas ;
Gullapalli, Ram ;
Manogharan, Guha P. ;
Lamoncha, Brandon ;
Fang, Maureen .
INTERNATIONAL JOURNAL OF METALCASTING, 2016, 10 (03) :240-252
[2]   A review of Additive Manufacturing technology and Cost Estimation techniques for the defence sector [J].
Busachi, Alessandro ;
Erkoyuncu, John ;
Colegrove, Paul ;
Martina, Filomeno ;
Watts, Chris ;
Drake, Richard .
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY, 2017, 19 :117-128
[3]   A decision support system for material and manufacturing process selection [J].
Giachetti, RE .
JOURNAL OF INTELLIGENT MANUFACTURING, 1998, 9 (03) :265-276
[4]   Automated identification of defect geometry for metallic part repair by an additive manufacturing process [J].
Hascoet, Jean-Yves ;
Touze, Stephane ;
Rauch, Matthieu .
WELDING IN THE WORLD, 2018, 62 (02) :229-241
[5]   An enabling digital foundation towards smart machining [J].
Hentz, J. B. ;
Nguyen, V. K. ;
Maeder, W. ;
Panarese, D. ;
Gunnink, J. W. ;
Gontarz, A. ;
Stavropoulos, P. ;
Hamilton, K. ;
Hascoeet, J. Y. .
EIGHTH CIRP CONFERENCE ON INTELLIGENT COMPUTATION IN MANUFACTURING ENGINEERING, 2013, 12 :240-245
[6]   Machine learning integrated design for additive manufacturing [J].
Jiang, Jingchao ;
Xiong, Yi ;
Zhang, Zhiyuan ;
Rosen, David W. .
JOURNAL OF INTELLIGENT MANUFACTURING, 2022, 33 (04) :1073-1086
[7]  
Jonata L., 2016, PART COMPLEXITY MEAS
[8]   Manufacturing complexity evaluation at the design stage for both machining and layered manufacturing [J].
Kerbrat, O. ;
Mognol, P. ;
Hascoet, J. -Y. .
CIRP JOURNAL OF MANUFACTURING SCIENCE AND TECHNOLOGY, 2010, 2 (03) :208-215
[9]  
Kerbrat O., 2009, THESIS
[10]   A new DFM approach to combine machining and additive manufacturing [J].
Kerbrat, Olivier ;
Mognol, Pascal ;
Hascoet, Jean-Yves .
COMPUTERS IN INDUSTRY, 2011, 62 (07) :684-692