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.

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.

Maximizing design potential: investigating the effects of utilizing opportunistic and restrictive design for additive manufacturing in rapid response solutions

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Rohan Prabhu ◽  
Jordan Scott Masia ◽  
Joseph T. Berthel ◽  
Nicholas Alexander Meisel ◽  
Timothy W. Simpson
Keyword(s):  
Additive Manufacturing ◽  
Design Methodology ◽  
Linear Models ◽  
Design For Additive Manufacturing ◽  
Content Type ◽  
Manufacturing Efficiency ◽  
Material Usage ◽  
Build Time ◽  
Rapid Prototyping And Manufacturing ◽  
Design For Am

Purpose The COVID-19 pandemic has resulted in numerous innovative engineering design solutions, several of which leverage the rapid prototyping and manufacturing capabilities of additive manufacturing. This paper aims to study a subset of these solutions for their utilization of design for AM (DfAM) techniques and investigate the effects of DfAM utilization on the creativity and manufacturing efficiency of these solutions. Design/methodology/approach This study compiled 26 COVID-19-related solutions designed for AM spanning three categories: (1) face shields (N = 6), (2) face masks (N = 12) and (3) hands-free door openers (N = 8). These solutions were assessed for (1) DfAM utilization, (2) manufacturing efficiency and (3) creativity. The relationships between these assessments were then computed using generalized linear models to investigate the influence of DfAM utilization on manufacturing efficiency and creativity. Findings It is observed that (1) unique and original designs scored lower in their AM suitability, (2) solutions with higher complexity scored higher on usefulness and overall creativity and (3) solutions with higher complexity had higher build cost, build time and material usage. These findings highlight the need to account for both opportunistic and restrictive DfAM when evaluating solutions designed for AM. Balancing the two DfAM perspectives can support the development of solutions that are creative and consume fewer build resources. Originality/value DfAM evaluation tools primarily focus on AM limitations to help designers avoid build failures. This paper proposes the need to assess designs for both, their opportunistic and restrictive DfAM utilization to appropriately assess the manufacturing efficiency of designs and to realize the creative potential of adopting AM.

A Design for Additive Manufacturing Ontology to Support Manufacturability Analysis

2018 ◽  
Author(s):  
Samyeon Kim ◽  
David W. Rosen ◽  
Paul Witherell ◽  
Hyunwoong Ko
Keyword(s):  
Additive Manufacturing ◽  
Design For Additive Manufacturing ◽  
Semantic Query ◽  
Ontology Language ◽  
Build Time ◽  
High Level ◽  
Design Freedom ◽  
Am Processes ◽  
Manufacturing Feature

Design for additive manufacturing (DFAM) provides design freedom for creating complex geometries and guides designers to ensure manufacturability of parts fabricated using additive manufacturing (AM) processes. However, there is a lack of formalized DFAM knowledge that provides information on how to design parts and how to plan AM processes for achieving target goals, e.g., reducing build-time. Therefore, this study presents a DFAM ontology using the web ontology language (OWL) to formalize DFAM knowledge and support queries for retrieving that knowledge. The DFAM ontology has three high level classes to represent design rules specifically: feature, parameter, and AM capability. Furthermore, the manufacturing feature concept is defined to link part design to AM process parameters. Since manufacturing features contain information on feature constraints of AM processes, the DFAM ontology supports manufacturability analysis of design features by reasoning with Semantic Query-enhanced Web Rule Language (SQWRL). The SQWRL rules in this study also help retrieve design recommendations for improving manufacturability. A case study is performed to illustrate usefulness of the DFAM ontology and SQWRL rule application. This study contributes to developing a knowledge base that can be reusable and upgradable and to analyzing manufacturing analysis to provide feedback about part designs to designers.

scholarly journals GEOMETRICAL BENCHMARKING OF LASER POWDER BED FUSION SYSTEMS BASED ON DESIGNER NEEDS

2021 ◽  
Vol 1 ◽  
pp. 1657-1666
Author(s):  
Joaquin Montero ◽  
Sebastian Weber ◽  
Christoph Petroll ◽  
Stefan Brenner ◽  
Matthias Bleckmann ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Use Case ◽  
Powder Bed Fusion ◽  
Design For Additive Manufacturing ◽  
Laser Powder Bed Fusion ◽  
Measuring Systems ◽  
Powder Bed ◽  
Geometric Dimensioning And Tolerancing ◽  
Uncertainty Map ◽  
New System

AbstractCommercially available metal Laser Powder Bed Fusion (L-PBF) systems are steadily evolving. Thus, design limitations narrow and the diversity of achievable geometries widens. This progress leads researchers to create innovative benchmarks to understand the new system capabilities. Thereby, designers can update their knowledge base in design for additive manufacturing (DfAM). To date, there are plenty of geometrical benchmarks that seek to develop generic test artefacts. Still, they are often complex to measure, and the information they deliver may not be relevant to some designers. This article proposes a geometrical benchmarking approach for metal L-PBF systems based on the designer needs. Furthermore, Geometric Dimensioning and Tolerancing (GD&T) characteristics enhance the approach. A practical use-case is presented, consisting of developing, manufacturing, and measuring a meaningful and straightforward geometric test artefact. Moreover, optical measuring systems are used to create a tailored uncertainty map for benchmarking two different L-PBF systems.

scholarly journals REVIEW OF DESIGN HEURISTICS AND DESIGN PRINCIPLES IN DESIGN FOR ADDITIVE MANUFACTURING

2021 ◽  
Vol 1 ◽  
pp. 2571-2580
Author(s):  
Filip Valjak ◽  
Angelica Lindwall
Keyword(s):  
Additive Manufacturing ◽  
Design Process ◽  
Research Question ◽  
Design Principles ◽  
Current Status ◽  
Design For Additive Manufacturing ◽  
Design Heuristics ◽  
Similarities And Differences ◽  
Definition Of ◽  
Support Methods

AbstractThe advent of additive manufacturing (AM) in recent years have had a significant impact on the design process. Because of new manufacturing technology, a new area of research emerged – Design for Additive Manufacturing (DfAM) with newly developed design support methods and tools. This paper looks into the current status of the field regarding the conceptual design of AM products, with the focus on how literature sources treat design heuristics and design principles in the context of DfAM. To answer the research question, a systematic literature review was conducted. The results are analysed, compared and discussed on three main points: the definition of the design heuristics and the design principles, level of support they provide, as well as where and how they are used inside the design process. The paper highlights the similarities and differences between design heuristics and design principles in the context of DfAM.

scholarly journals Smooth Design of 3D Self-Supporting Topologies Using Additive Manufacturing Filter and SEMDOT

2020 ◽  
Vol 11 (1) ◽  
pp. 238
Author(s):  
Yun-Fei Fu ◽  
Kazem Ghabraie ◽  
Bernard Rolfe ◽  
Yanan Wang ◽  
Louis N. S. Chiu
Keyword(s):  
Additive Manufacturing ◽  
Compliant Mechanism ◽  
Optimization Method ◽  
Light Weight ◽  
Design For Additive Manufacturing ◽  
Compliance Minimization ◽  
Performance Requirements ◽  
Specific Performance ◽  
Smooth Design ◽  
Compliant Mechanism Design

The smooth design of self-supporting topologies has attracted great attention in the design for additive manufacturing (DfAM) field as it cannot only enhance the manufacturability of optimized designs but can obtain light-weight designs that satisfy specific performance requirements. This paper integrates Langelaar’s AM filter into the Smooth-Edged Material Distribution for Optimizing Topology (SEMDOT) algorithm—a new element-based topology optimization method capable of forming smooth boundaries—to obtain print-ready designs without introducing post-processing methods for smoothing boundaries before fabrication and adding extra support structures during fabrication. The effects of different build orientations and critical overhang angles on self-supporting topologies are demonstrated by solving several compliance minimization (stiffness maximization) problems. In addition, a typical compliant mechanism design problem—the force inverter design—is solved to further demonstrate the effectiveness of the combination between SEMDOT and Langelaar’s AM filter.

scholarly journals An Optimization Workflow in Design for Additive Manufacturing

2021 ◽  
Vol 11 (6) ◽  
pp. 2572
Author(s):  
Stefano Rosso ◽  
Federico Uriati ◽  
Luca Grigolato ◽  
Roberto Meneghello ◽  
Gianmaria Concheri ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Structural Optimization ◽  
Geometric Model ◽  
Complex Geometries ◽  
Design Phase ◽  
Design For Additive Manufacturing ◽  
Engineering Software ◽  
Embodiment Design ◽  
Pros And Cons

Additive Manufacturing (AM) brought a revolution in parts design and production. It enables the possibility to obtain objects with complex geometries and to exploit structural optimization algorithms. Nevertheless, AM is far from being a mature technology and advances are still needed from different perspectives. Among these, the literature highlights the need of improving the frameworks that describe the design process and taking full advantage of the possibilities offered by AM. This work aims to propose a workflow for AM guiding the designer during the embodiment design phase, from the engineering requirements to the production of the final part. The main aspects are the optimization of the dimensions and the topology of the parts, to take into consideration functional and manufacturing requirements, and to validate the geometric model by computer-aided engineering software. Moreover, a case study dealing with the redesign of a piston rod is presented, in which the proposed workflow is adopted. Results show the effectiveness of the workflow when applied to cases in which structural optimization could bring an advantage in the design of a part and the pros and cons of the choices made during the design phases were highlighted.

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