CAD-Integrated Cost Estimation and Build Orientation Optimization to Support Design for Metal Additive Manufacturing

2017 ◽  
Author(s):  
Michael Barclift ◽  
Andrew Armstrong ◽  
Timothy W. Simpson ◽  
Sanjay B. Joshi
Keyword(s):  
Additive Manufacturing ◽  
Cost Estimation ◽  
Application Programming Interface ◽  
External Support ◽  
Support Design ◽  
Build Orientation ◽  
3D Cad ◽  
Build Time ◽  
Cad Models ◽  
Integrated Cost

Cost estimation techniques for Additive Manufacturing (AM) have limited synchronization with the metadata of 3D CAD models. This paper proposes a method for estimating AM build costs through a commercial 3D solid modeling program. Using an application programming interface (API), part volume and surface data is queried from the CAD model and used to generate internal and external support structures as solid-body features. The queried data along with manipulation of the part’s build orientation allows users to estimate build time, feedstock requirements, and optimize parts for AM production while they are being designed in a CAD program. A case study is presented with a macro programmed using the SolidWorks API with costing for a metal 3D-printed automotive component. Results reveal that an imprecise support angle can under-predict support volume by 34% and build time by 20%. Orientation and insufficient build volume packing can increase powder depreciation costs by nearly twice the material costs.

Development of CAD-Integrated Cost Estimator to Support Design for Additive Manufacturing

2017 ◽  
Author(s):  
Andrew P. Armstrong ◽  
Michael Barclift ◽  
Timothy W. Simpson
Keyword(s):  
Additive Manufacturing ◽  
Application Programming Interface ◽  
Extrusion Process ◽  
Design For Additive Manufacturing ◽  
Support Design ◽  
Cost Estimates ◽  
Overall Design ◽  
Build Time ◽  
Integrated Cost ◽  
User Knowledge

Design for Additive Manufacturing is an evolving field that allows alternative design approaches to facilitate improvements in parts and builds by taking advantage of the capability of additive manufacturing (AM). Currently, available CAD software does not provide sufficient tools for AM designers, which results in a complex iterative process requiring multiple file types and programs. The complicated process of generating build time and cost estimates prevents designers from being able to efficiently optimize their parts for the AM process. Through the Solidworks Application Programming Interface a user-controlled macro was developed to generate build time and cost estimates by automatically creating support structures from multiple planes of comparative Ray Trace vector grids. The macro provides the user with visual and qualitative part information at the first stage in the design/file workflow, curtailing the current complex workflow to reduce overall design time. The macro is focused on the material extrusion process due to the diversity in available machines and build control, favoring user knowledge of specific parameters to calculate the build time and cost. Limitations of the approach along with extensions to other AM processes are also discussed.

A statistical method for build orientation determination in additive manufacturing

2019 ◽  
Vol 25 (1) ◽  
pp. 187-207 ◽  
Author(s):  
Yicha Zhang ◽  
Ramy Harik ◽  
Georges Fadel ◽  
Alain Bernard
Keyword(s):  
Additive Manufacturing ◽  
Statistical Method ◽  
Supervised Machine Learning ◽  
Surface Model ◽  
Generic Level ◽  
Content Type ◽  
Build Orientation ◽  
Cad Models ◽  
Feature Based ◽  
Orientation Determination

Purpose For part models with complex shape features or freeform shapes, the existing build orientation determination methods may have issues, such as difficulty in defining features and costly computation. To deal with these issues, this paper aims to introduce a new statistical method to develop fast automatic decision support tools for additive manufacturing build orientation determination. Design/methodology/approach The proposed method applies a non-supervised machine learning method, K-Means Clustering with Davies–Bouldin Criterion cluster measuring, to rapidly decompose a surface model into facet clusters and efficiently generate a set of meaningful alternative build orientations. To evaluate alternative build orientations at a generic level, a statistical approach is defined. Findings A group of illustrative examples and comparative case studies are presented in the paper for method validation. The proposed method can help production engineers solve decision problems related to identifying an optimal build orientation for complex and freeform CAD models, especially models from the medical and aerospace application domains with much efficiency. Originality/value The proposed method avoids the limitations of traditional feature-based methods and pure computation-based methods. It provides engineers a new efficient decision-making tool to rapidly determine the optimal build orientation for complex and freeform CAD models.

scholarly journals DECOMPOSITION ALGORITHM FOR TOOL PATH PLANNING FOR WIRE-ARC ADDITIVE MANUFACTURING

2018 ◽  
Vol Vol.18 (No.1) ◽  
pp. 96-107 ◽  
Author(s):  
Lam NGUYEN ◽  
Johannes BUHL ◽  
Markus BAMBACH
Keyword(s):  
Additive Manufacturing ◽  
Path Planning ◽  
Computer Aided Design ◽  
Tool Path ◽  
Heuristic Method ◽  
Support Material ◽  
Build Time ◽  
Cad Models ◽  
Aided Design ◽  
Wire Arc Additive Manufacturing

Three-axis machines are limited in the production of geometrical features in powder-bed additive manufacturing processes. In case of overhangs, support material has to be added due to the nature of the process, which causes some disadvantages. Robot-based wire-arc additive manufacturing (WAAM) is able to fabricate overhangs without adding support material. Hence, build time, waste of material, and post-processing might be reduced considerably. In order to make full use of multi-axis advantages, slicing strategies are needed. To this end, the CAD (computer-aided design) model of the part to be built is first partitioned into sub-parts, and for each sub-part, an individual build direction is identified. Path planning for these sub-parts by slicing then enables to produce the parts. This study presents a heuristic method to deal with the decomposition of CAD models and build direction identification for sub-entities. The geometric data of two adjacent slices are analyzed to construct centroidal axes. These centroidal axes are used to navigate the slicing and building processes. A case study and experiments are presented to exemplify the algorithm.

A Computational Design Framework for a Rapid Solid Freeform Fabrication Process

2000 ◽  
Author(s):  
Deepesh Khandelwal ◽  
T. Kesavadas
Keyword(s):  
Solid Freeform Fabrication ◽  
Optimization Technique ◽  
Three Dimensional ◽  
Computational Design ◽  
Freeform Fabrication ◽  
3D Cad ◽  
Build Time ◽  
Cad Models ◽  
Efficient Machine ◽  
Novel Concept

Abstract Solid Freeform Fabrication (SFF) techniques in recent years have shown tremendous promise in reducing the design time of products. This technique enables designers to get three-dimensional physical prototypes from 3D CAD models. Although SFF has gained popularity, the manufacturing time and cost have limited its use to small and medium sized parts. In this paper we have proposed a novel concept for rapidly building SFF parts by inserting prefabricated inserts into the fabricated part. A computational algorithm was developed for determining ideal placement of inserts/cores in the CAD model of the part being prototyped using a heuristic optimization technique called Simulated Annealing. This approach will also allow the designers to build multi-material prototypes using the Rapid Prototyping (RP) technique. By using cheaper pre-fabricates instead of costly photopolymers, the production cost of the SFFs can be reduced. Additionally it will also reduce build time, resulting in efficient machine utilization.

scholarly journals STUDIES ON MASK-LESS ELECTROCHEMICAL ADDITIVE MANUFACTURING

2021 ◽  
Author(s):  
Abhishek Bhardwaj
Keyword(s):  
Additive Manufacturing ◽  
High Power ◽  
Room Temperature ◽  
Three Dimensional ◽  
High Impact ◽  
Layer By Layer ◽  
Metal Parts ◽  
3D Cad ◽  
Cad Models

<div>Added substance Manufacturing (AM) of metallic designs is a warm cycle of layer by layer metal added substance fabricating measure produces parts straightforwardly from 3D CAD models. In this assembling interaction confined electrochemical affidavit joins with the added substance producing technique to make metal parts at room temperature. In this paper, the attainability of Mask-less Electrochemical Additive Manufacturing (ECAM), as a non-warm interaction is considered. Layer by layer testimony has been finished utilizing the electrochemical tips to make nickel microstructures. All the while beat wave qualities and their impacts on affidavit have been considered. </div><div>Confined electrodeposition (LED) was investigated as an AM the interaction with high power over measure boundaries and yield boundaries. The confinement of electrodeposition is completed by utilizing Ultra microelectrodes (UME) and low tossing power electrolytes. Variety in some cycle boundaries, for example, voltage and terminal hole are found to have a high impact on yield boundaries like thickness. The reproductions can anticipate the yield width of affidavit of analyses with a blunder of 8- 30%, so it can possibly apply as an added substance-producing strategy of complex three-dimensional (3D) parts on the microscale.</div>

scholarly journals Determination of optimal build orientation for additive manufacturing using Muirhead mean and prioritised average operators

2019 ◽  
Vol 30 (8) ◽  
pp. 3015-3034 ◽  
Author(s):  
Yuchu Qin ◽  
Qunfen Qi ◽  
Paul J. Scott ◽  
Xiangqian Jiang
Keyword(s):  
Additive Manufacturing ◽  
Fuzzy Decision ◽  
Decision Matrix ◽  
Build Orientation ◽  
Part Quality ◽  
Determination Process ◽  
Build Time ◽  
Finite Set ◽  
Multi Attribute Decision Making

Abstract Build orientation determination is one of the essential process planning tasks in additive manufacturing since it has crucial effects on the part quality, post-processing, build time and cost, etc. This paper introduces a method based on fuzzy multi-attribute decision making to determine the optimal build orientation from a finite set of alternatives. The determination process includes two major steps. In the first step, attributes that are considered in the determination and heterogeneous relationships of which are firstly identified. A fuzzy decision matrix is then constructed and normalised based on the values of the identified attributes, which are quantified by a set of fuzzy numbers. In the second step, two fuzzy number aggregation operators are developed to aggregate the fuzzy information in the normalised matrix. By comparing the aggregation results, a ranking of all alternative build orientations can then be generated. Two determination examples are used to demonstrate the working process of the proposed method. Qualitative and quantitative comparisons between the proposed method and other methods are carried out to demonstrate its feasibility, effectiveness, and advantages.

Investigating the Impacts of Heterogeneous Infills on Structural Strength of 3D Printed Parts

2019 ◽  
Vol 799 ◽  
pp. 276-281
Author(s):  
Ramisha Sajjad ◽  
Sajid Ullah Butt ◽  
Khalid Mahmood ◽  
Hasan Aftab Saeed
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Three Dimensional ◽  
Weight Ratio ◽  
3D Cad ◽  
Fused Deposition ◽  
Material Usage ◽  
Rectangular Pattern ◽  
Build Time ◽  
Deposition Modeling

Additive Manufacturing is a manufacturing process based on layers for making three dimensional scaled physical parts directly from 3D CAD data. Fused Deposition Modeling (FDM) is widely used technology that provides functional prototypes in various thermoplastics. In additive manufacturing, filling patterns are of two types; External and Internal filling patterns. Multiple patterns are developed for both filling categories. In this work, a heterogeneous infill strategy is used by choosing developed patterns in order to improve strength to weight ratio, material usage and build time for parts. A rectilinear pattern combination with triangular and rectangular pattern has been chosen for 3D printing. The tensile testing is performed on the printed specimens to calculate the strength to weight ratio. By comparing the obtained results, a strategy based on maximum strength to weight ratio, minimum material usage and reduced build time is recommended for FDM technology.

scholarly journals STUDIES ON MASK-LESS ELECTROCHEMICAL ADDITIVE MANUFACTURING

2021 ◽  
Author(s):  
Abhishek Bhardwaj
Keyword(s):  
Additive Manufacturing ◽  
High Power ◽  
Room Temperature ◽  
Three Dimensional ◽  
High Impact ◽  
Layer By Layer ◽  
Metal Parts ◽  
3D Cad ◽  
Cad Models

<div>Added substance Manufacturing (AM) of metallic designs is a warm cycle of layer by layer metal added substance fabricating measure produces parts straightforwardly from 3D CAD models. In this assembling interaction confined electrochemical affidavit joins with the added substance producing technique to make metal parts at room temperature. In this paper, the attainability of Mask-less Electrochemical Additive Manufacturing (ECAM), as a non-warm interaction is considered. Layer by layer testimony has been finished utilizing the electrochemical tips to make nickel microstructures. All the while beat wave qualities and their impacts on affidavit have been considered. </div><div>Confined electrodeposition (LED) was investigated as an AM the interaction with high power over measure boundaries and yield boundaries. The confinement of electrodeposition is completed by utilizing Ultra microelectrodes (UME) and low tossing power electrolytes. Variety in some cycle boundaries, for example, voltage and terminal hole are found to have a high impact on yield boundaries like thickness. The reproductions can anticipate the yield width of affidavit of analyses with a blunder of 8- 30%, so it can possibly apply as an added substance-producing strategy of complex three-dimensional (3D) parts on the microscale.</div>

Orientation Optimization in Additive Manufacturing: Evaluation of Recent Trends

2021 ◽  
Author(s):  
Jannatul Bushra ◽  
Hannah D. Budinoff
Keyword(s):  
Additive Manufacturing ◽  
Optimization Methods ◽  
Optimization Method ◽  
Optimization Techniques ◽  
Practical Implementation ◽  
Objective Functions ◽  
Build Orientation ◽  
Computational Optimization ◽  
Build Time ◽  
Orientation Optimization

Abstract Build orientation in additive manufacturing influences the mechanical properties, surface quality, build time, and cost of the product. Rather than relying on trial-and-error or prior experience, the choice of build orientation can be formulated as an optimization problem. Consequently, orientation optimization has been a popular research topic for several decades, with new optimization methods being proposed each year. However, despite the rapid pace of research in additive manufacturing, there has not been a critical comparison of different orientation optimization methods. In this study, we present a critical review of 50 articles published since 2015 that proposes a method for orientation optimization for additive manufacturing. We classify included papers by optimization methods used, AM process modeled, and objective functions considered. While the pace of research in recent years has been rapid, most approaches we identified utilized similar objective functions and computational optimization techniques to research from the early 2000s. The most common optimization method in the included research was exhaustive search. Most methods focused on broad applicability to all additive manufacturing processes, rather than a specific process, but a few works focused on powder bed fusion and material extrusion. We also identified several areas for future work including integration with other design and process planning tasks such as topology optimization, more focus on practical implementation with users, testing of computational efficiency, and experimental validation of utilized objective functions.

scholarly journals Evaluation of Additive Manufacturing Processes in Fabrication of Personalized Robot

2017 ◽  
Vol 11 (1) ◽  
pp. 29-37 ◽  
Author(s):  
Shushu Wang ◽  
◽  
Rakshith Badarinath ◽  
El-Amine Lehtihet ◽  
Vittaldas Prabhu
Keyword(s):  
Additive Manufacturing ◽  
Fused Deposition Modeling ◽  
Customer Participation ◽  
Design Stage ◽  
Robot Arm ◽  
Mechanical Assembly ◽  
End Effector ◽  
Fused Deposition ◽  
Build Time ◽  
Cad Models

Customer participation in the design stage of creating personalized products is increasing. Additive manufacturing (AM) has become a popular enabler of personalization. In this study, we evaluate the fabrication of an open-source robot arm in terms of cost, build time, dimensional and locational accuracy, end-effector accuracy, and mechanical properties. The mechanical components of the table-top robot were fabricated using two different AM processes of fused deposition modeling (FDM) and material jetting (polymer jetting or PolyJet). A reduction of infill density by 50% in the FDM process slightly decreased the building time, material cost, and tensile strength, but induced a 95% reduction in yield strength. A simulation of the mechanical assembly using the CAD models for the robot and the expected tolerances of the components estimated the end-effector positioning accuracy as 0.01–0.22 mm. The 3D printed robot arm was redesigned and fabricated using the best evaluated process in this study.

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