Orientation Optimization in Additive Manufacturing: Evaluation of Recent Trends

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.Immediate accessThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

‘Earning your scars’: An exploratory interview study of design for manufacturing at hardware startups

Although many design for manufacturing tools and methods have been developed, it is unclear if engineers at startups widely use these design support techniques. We interviewed twelve engineers employed at startups to better identify common practices related to design for manufacturing. Specifically, we sought to learn the design for manufacturing strategies and tools used, and the timing of considering manufacturing constraints—such as process cost and geometry restrictions—in startups’ new product development processes. Interviews were analyzed using an inductive coding approach. All interviewees viewed design for manufacturing as being necessary for a successful product launch, but the implementation of considering manufacturing constraints varied. Interviewees mainly learned of the importance of design for manufacturing through negative personal design experiences where they did not emphasize the consideration of manufacturing constraints, a process which was described as “earning scars.” Formal education was viewed by interviewees as having limited practical utility, and startups’ staffing and funding constraints contributed to informal new product development processes and design practices. We identified ten emergent informal design for manufacturing strategies employed at startups, with most strategies relying heavily on consulting external manufacturing experts. We noted only a limited use of design for manufacturing tools, such as manufacturing simulation software and cost modeling. Insights from this paper can lead to better educational practices, contribute to more contextualized advising of startups, and guide other resource-constrained design teams.nsf12 month embargo; published: 26 August 2022This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Will it print: a manufacturability toolbox for 3D printing

This study presents the development of a novel MATLAB-based virtual prototyping tool called Will It Print that evaluates part geometry to check for compliance with design-for-additive-manufacturing guidelines relating to manufacturability. Specifically, the tool analyzes the part geometry for potential problems regarding warping, toppling, poor surface finish, and small or overhanging features when the part is produced using fused-filament fabrication. This tool helps designers evaluate the manufacturability of their parts and provides suggestions to change part geometry and orientation to avoid print failures and improve part quality. In this study, Will It Print was used to redesign several models and to choose a build orientation for 3D printing. The original and redesigned models were printed and compared. The redesigned models had lower scrap rates and improved quality. Our open-source MATLAB tool enables novices to engage in virtual prototyping for 3D printing so they can print high-quality parts without inefficient trial-and-error printing. This tool will be especially helpful for students and practitioners with limited access to a 3D printer, such as in remote learning modalities, which have become prevalent in recent years.National Science Foundation Graduate Research Fellowship Program under Grant No. DGE-175281412 month embargo; published: 29 October 2021This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Connecting part geometry and cost for metal powder bed fusion

Additive manufacturing processes have enabled the production of parts with complex geometry. In addition, novel design approaches such as generative design and crowdsourced design challenges enable the rapid generation of many feasible design alternatives with similar functionality but distinct geometry. In this study, we use an illustrative example, focused on laser-based powder bed fusion of metals, to explore how geometry and topology differences among parts with the same functionality can drive differences in cost. To accomplish this, we utilize a process-based cost model that can account for how variations in part geometry of different design alternatives impact the cost of the additive manufacturing process and associated post-processing operations. The cost model identified differences of up to 14% between the least and most expensive design alternatives. Part mass and build time were the most influential factors to group different design into relatively similar cost groups. High part complexity was associated with lower part cost, and was not strongly correlated to reject rates. Comparing designs within these groups showed several conflicting factors such as additive manufacturing and post-processing scrap and reject rates, which were geometry dependent. This result highlights the need for methods to better understand and quantify the effect of part geometry on manufacturing outcomes related to cost, including powder usage, post-processing requirements, and failure rates. Such methods can help designers to weigh tradeoffs between different cost, sustainability, quality, and performance objectives to select a preferred design alternative.12 month embargo; published: 23 July 2022This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Exploring the impact of design tool usage on design for additive manufacturing processes and outcomes

Improving designers’ ability to identify manufacturing constraints during design can help reduce the time and cost involved in the development of new products. Different design for additive manufacturing (DfAM) tools exist, but the design outcomes produced using such tools are often evaluated without comparison to existing tools. This study addresses the research gap by directly comparing design performance using two design support tools: a worksheet listing DfAM principles and a manufacturability analysis software tool that analyzes compliance with the same principles. In a randomized-controlled study, 49 nonexpert designers completed a design task to improve the manufacturability of a 3D-printed part using either the software tool or the worksheet tool. In this study, design outcome data (creativity and manufacturability) and design process data (task load and time taken) were measured. We identified statistically significant differences in the number of manufacturability violations in the software and worksheet groups and the creativity of the designs with novel build orientations. Results demonstrated limitations associated with lists of principles and highlighted the potential of software in promoting creativity by encouraging the exploration of alternative build orientations. This study provides support for using software to help designers, particularly nonexpert designers who rely on trial and error during design, evaluate the manufacturability of their designs more effectively, thereby promoting concurrent engineering design practices

Community-driven PPE production using additive manufacturing during the COVID-19 pandemic: Survey and lessons learned

This study presents a detailed analysis of the production efforts for personal protective equipment in makerspaces and informal production spaces (i.e., community-driven efforts) in response to the COVID-19 pandemic in the United States. The focus of this study is on additive manufacturing (also known as 3D printing), which was the dominant manufacturing method employed in these production efforts. Production details from a variety of informal production efforts were systematically analyzed to quantify the scale and efficiency of different efforts. Data for this analysis was primarily drawn from detailed survey data from 74 individuals who participated in these different production efforts, as well as from a systematic review of 145 publicly available news stories. This rich dataset enables a comprehensive summary of the community-driven production efforts, with detailed and quantitative comparisons of different efforts. In this study, factors that influenced production efficiency and success were investigated, including choice of PPE designs, production logistics, and additive manufacturing processes employed by makerspaces and universities. From this investigation, several themes emerged including challenges associated with matching production rates to demand, production methods with vastly different production rates, inefficient production due to slow build times and high scrap rates, and difficulty obtaining necessary feedstocks. Despite these challenges, nearly every maker involved in these production efforts categorized their response as successful. Lessons learned and themes derived from this systematic study of these results are compiled and presented to help inform better practices for future community-driven use of additive manufacturing, especially in response to emergencies.No embargo COVID-19This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]