If you’re not fully convinced of the additive wave that’s sweeping manufacturing, a brief conversation with Penn State University Professor Timothy W. Simpson will quickly change your mind. The past few years has seen the additive manufacturing (AM) industry making big inroads into areas previously considered the stronghold of high-precision, production-only metalcutting and metal-finishing processes. Count as converts much of the aerospace/defense industry, which is leading the charge, along with medical and automotive.
Additive’s recent surge has been spurred on by GE’s acquisition of Morris Technologies, the launch of America Makes and the National Network of Manufacturing Innovation (NNMI) institutes, noted Simpson, Paul Morrow Professor of Engineering Design and Manufacturing at Pennsylvania State University (PSU; University Park, PA), and director of PSU’s new Additive Manufacturing and Design Graduate Program (http://AMDprogram.psu.edu).
“There was yet another step change again about a year and a half ago, when GE bought Concept Laser and Arcam,” Simpson said. “The big companies—GE, Honeywell, Pratt & Whitney—are invested heavily in AM technology. But now with GE’s second acquisition, you’re seeing the Tier Ones and Tier Twos, all the suppliers saying, ‘Uh-oh, this isn’t going away—we really better figure out how to remain relevant in the face of additive manufacturing.’ Given that GE dropped $1.6 billion on two AM system suppliers, everybody else is now making significant investments. Those are the two inflection points that continue to drive interest in AM.”
Aside from its extensive AM research, Penn State spurs interest in AM technology with the availability of its maker machines on campus to any of the university system’s 100,000 students at PSU’s 24 campuses, noted Simpson, who also serves as co-director of the Center for Innovative Materials Processing Through Direct Digital Deposition (CIMP-3D; http://www.cimp-3d.org), a research center in Innovation Park, located on the edge of the main PSU University Park campus.
The university gives students free access to the MakerBots and an Invention Studio through the Penn State Maker Commons
(https://makercommons.psu.edu/) that can be reached via the campus network. Simpson was a Penn State Teaching and Learning with Technology (TLT) Fellow in 2015, during which time he helped connect the 3D printing resources throughout the campus for use by students, staff and faculty, and create resources to get the community familiar with AM technologies.
“Part of my role as a [TLT] fellow was to build awareness, a culture around it [3D printing], and find lead users to get it into the classroom,” said Simpson of the TLT fellowship. “We’re continuing to promote and work across the university, and I integrated it permanently into a junior-level mechanical design course, ME 340, Mechanical Design Processes, that I teach, so that every one of our mechanical engineering students has some experience designing in 3D printing before they leave Penn State.” PSU’s ME 340 is a required course, and Penn State annually graduates about 450-500 students a year in mechanical engineering.
The Penn State TLT program invests in new technologies that improve learning and teaching, he said. “We have 32 MakerBots now that anybody at Penn State can access for free, and it’s not just at University Park—any student at any campus can basically print from their dorm room or their classroom. The other cool thing is if you’re here, when your part’s done you just go to the library and pick it up,” Simpson said. “But if you’re on another campus, the library here will ship it via inter-library loan, just like a book, and you go to your local Penn State campus library in Philadelphia or Pittsburgh or wherever and pick up your 3D-printed part.”
Penn State’s engineering research programs run the gamut, from basic R&D to applied research. CIMP-3D has approximately 100 employees including faculty researchers and staff, plus undergraduates, graduate students and post-docs, Simpson said. “I liken it [CIMP-3D] to a joint venture between Penn State and the Applied Research Lab [ARL], which is a Navy-affiliated university research center. ARL oversees CIMP-3D, and I help integrate it into Penn State. Working together, we have created a ‘one-stop-shop’ for all your AM needs.”
The university’s research into AM technology includes a successful spin-off company, Pan Computing, later acquired by Autodesk Inc. (San Rafael, CA) for its simulation software technology, which is used in Autodesk’s Netfabb software. Simpson notes “Pan Computing was a huge advantage for CIMP-3D when they launched; now everyone has access to their tools.”
Simpson, who is active on Twitter as @PSUMakerProf, last year gave a TEDx talk where he described AM technologies’ design advantages over subtractive manufacturing. His TEDx, “Disrupting Manufacturing One Layer at a Time,” which is a locally organized TED-style discussion, is available on YouTube (https://www.youtube.com/watch?v=Tzx9Ux9Be9E).
“As a design guy, I think the biggest bottleneck is now our design software and the workflow,” Simpson said. “If you want to do fancy lattices or topology optimization for lightweighting, you’ve got three, four, five, six different programs that you might need to pull together to be able to do all your structural and engineering analysis. So that’s a headache for everybody.”
Other obstacles are AM’s material properties and design allowables, he said. “We just don’t have the data yet [for AM] like we do with casting, forging and machining,” Simpson stated. “What’s my part actually going to do, and is it as strong as I designed it to be? That also, of course, relies on having good standards on how we’re building, orienting, and heat treating parts—all the things we take for granted with traditional manufacturing processes.”
Metal porosity issues in AM have largely been solved, Simpson noted. “I think we’ve figured out ways to solve that, doing both good laser processing so you’re scanning patterns to give you fully dense parts, and by doing hot isostatic pressing on the post-heat treatment side. But interestingly, the other thing I push back on is do we need the part to be fully dense? Are there applications where porosity might actually be a good thing?” A good example is a medical application, he noted, where fully dense metal implants may not be needed, or even desirable. “Our bones are porous structures; so, why aren’t our implants? With AM, they can be,” he said.
To help industry meet the workforce needs of AM, the university launched what it calls the world’s first multidisciplinary graduate-level program in additive manufacturing and design last fall, according to Simpson, director of the program. Leveraging PSU’s extensive AM efforts, the new Penn State Master of Science in Additive Manufacturing (MSAMD) and online Master of Engineering in Additive Manufacturing (MEngAMD) programs are 30-credit graduate degrees aimed at building students’ analytical and practical skills in digital design, development, analysis, optimization, fabrication and inspection of AM components.
These summaries, excerpts, and web links are from recent papers published in the SME Journal of Manufacturing Systems, Journal of Manufacturing Processes, and Manufacturing Letters, which are printed by Elsevier Ltd. (www.elsevier.com) and used here with permission.
In their paper, “Error compensation and accuracy improvements in 5-axis machine tools using the global offset method,” authors Jie Gu, John S. Agapiou, and Sheri Kurgin of General Motors R&D, detail the global offset method of error compensation for manufacturing components. This paper, which was published in Volume 44, Part 2, of the Journal of Manufacturing Systems, was presented at the 45th SME North American Manufacturing Research Conference, NAMRC 45. It is available at https://www.sciencedirect.com/science/article/pii/S0278612517300547#fig0005.
To enhance machine tool accuracy, the global offset method is developed for compensating the five-axis machine tool errors based on the measurement results of one or more identical machined parts. The machined features of a part are measured in a CMM and evaluated by a compensation processor, based on which the global offset parameters, representing the machine tool errors, are estimated. The methodology is capable of compensating the overall effect of all position-dependent and position-independent systematic errors which contribute to particular workpiece accuracy.
The developed technique and software are based on the global offset method, which interprets the computed deviations between the measured and nominal dimensions of the part through the analysis, synthesis and modeling of a fixture and rotary tables errors. The proposed model-based error compensation method is simple enough to be implemented in five-axis CNC machine tools. Production results exhibit effective compensation and remarkable improvement in the workpiece accuracy of the five-axis machine tools.
Open control architectures regain relevance with the new revolution of open source electronics. This paper, “A modular-architecture controller for CNC systems based on open-source electronics,” by authors Jorge E. Correa, Nicholas Toombs, and Placid M. Ferreira, of the Department of Mechanical Science and Engineering, University of Illinois at Urbana-Champaign, is published in Vol. 44 of the Journal of Manufacturing Systems, and is available at https://www.sciencedirect.com/science/article/pii/S0278612517300523.
The paper presents the general ideas, examples of implementation and latest advances of a new, open architecture controller for CNC systems based on open source electronics. The multiprocessor and distributed architecture of this controller leverages the power of platforms like Arduino or TI Launchpad to realize CNC systems of increased computational resources, closed-loop tool positioning, smoother motions and higher feeds. Additionally, this work demonstrates the first steps in the development of virtual machine as a new software component of the architecture. A “tight binding” between the real and virtual machines will delineate the path for a realistic machine monitoring, remote operation and process planning environment.
In their paper, “A software-defined framework for the integrated management of smart manufacturing systems,” authors Felipe Lopez, James Moyne, Kira Barton and Dawn Tilbury of the Department of Mechanical Engineering, University of Michigan (UM; Ann Arbor, MI), and Yuru Shao and Z. Morley Mao, of the Department of Electrical Engineering and Computer Science, UM, discuss the requirements for smart manufacturing systems in the age of Industry 4.0. Published in the Volume 15 January 2018 issue of Manufacturing Letters, it is available at https://www.sciencedirect.com/science/article/pii/S2213846317300767.
This paper introduces software-defined control (SDC) as a framework that enables integrated and programmatic management of smart manufacturing systems. SDC consolidates information from the production and enterprise levels in a central controller that monitors performance and detects changing conditions. The integrated view of the system provided by the central controller supports the development of applications, which supply the central controller with new information and reconfiguration recommendations.
SDC is designed to be scalable and compatible with current automation technologies. A simulation shows that the incorporation of plant-floor information in management decisions, as supported by SDC, has the potential to improve profitability. Smart manufacturing (SM) systems have been defined as “fully-integrated, collaborative manufacturing systems that respond in real time to meet changing demands and conditions in the factory, in the supply network, and in customer needs.” The vision of SM requires a higher degree of integration and agility than allowed by current industrial automation technologies. ISA-95, the standard for integration in automation, supports only limited information sharing between process control, operations management, and business planning applications, allowing data silos that prevent integrated system management. Moreover, plant floor automation equipment (e.g., PLCs, CNCs, robots) lacks the agility required to respond in real time to changing conditions; programs of typical automation equipment are thoroughly validated before deployment and are expected to operate without major modifications. Integration and agility in industrial automation must improve to make SM a reality.
The authors acknowledged Sibin Mohan and Sayan Mitra, from the University of Illinois, and Elaine Shi, from Cornell University, as co-developers of the SDC framework.
TechFront is edited by Senior Editor Patrick Waurzyniak; email@example.com.
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