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3D PRINTING


Speaking to the need, Jim Fendrick, vice president, North America, at SLM Solutions (Novi, MI), said: “One of the fi rst things I get asked when I visit a vendor is do you know of any good technicians?” The problem is widespread in manufacturing in general, as millennials and others that will make up the future work- force view manufacturing as old school. Training a qualifi ed workforce will likely require collaboration between industry and academia, not to mention convincing the younger generations that manufacturing jobs are worth aspiring to.


“Skillsets aside, there’s no pool of people to pull from,” he said. “When CNC machining came around, at least you had a pool of experienced machinists to pull from.”


A look inside the build chamber of the SLM500, equipped with four lasers to make complete engines.


Tackett’s UL colleague, Chris Krampitz, director of strat- egy and innovation for digital manufacturing technologies (Chicago, IL), agrees that assembling a workforce is a big challenge—and puts numbers to the problem: “When we look at the workforce that’s required for additive, we’re facing a large shortage. By 2025, we’ll see a worker shortage of 2 million across manufacturing (in the United States), and it’s even more diffi cult with additive because of specialization.” There are at least two major problems with fi nding


qualifi ed workers for metal AM: skillset and the pool of potential workers. Tackett noted it takes a very broad set of skills to work ef- fectively in a metal AM operation. Workers need knowledge of and skills in computer science, metallurgy, coordinate measur- ing systems, mechanics, gas fl ow, heat and lasers, for starters. “The list goes on and on,” he said. Design is another skill that’s lacking in today’s metal AM operators, Krampitz added.


“In traditional manufacturing, you designed a part for injection molding; nowadays if you’re running a plastics ad- ditive machine and you design a part as you did for injection molding, you have no competitive edge,” Tackett said.


56 AdvancedManufacturing.org | May 2016


Optimization on the Shop Floor Also challenging is automating production to get the most out of a shop’s investment in machinery, and integrating metal AM into production work. Andy Snow, senior vice president of development for EOS North America (Novi, MI), said one of the biggest challenges the metal AM industry as a whole faces is automation. His company’s solution has been to partner with other companies already expert in automation with the use of robotics, palletized chucks and other technology. In June 2015, EOS partnered with GF Machining Solutions (Schaffhausen, Switzerland) to develop solutions for moldmakers. EOS’ machines are well suited for making metal inserts with cooling close to the surface, speeding up mold cooling and hastening the plastic injection cycle. GF will contribute software and link the EOS machines downstream with its EDM and high-speed milling tools, and measuring devices. Other types of software are also needed. When additive machines were used strictly for


making quick prototypes, their manufacturers gave little thought to equipping them with the technology that would make it possible to connect them to each other, to other production machines, or to the Industrial Internet. Now that AM machines are moving to the factory fl oor, manufacturers will have to play catch up.


“One of the big things right now that is very desirable is to


have process controls,” Krampitz said. “If something goes wrong, there’s nothing to bring it back. We need control loops so the machine can sense what’s going on with the part build and take corrective actions if necessary.” Organizations like America Makes (Youngstown, OH) and companies such as 3DSIM (Park City, UT) are working on soft- ware for a logic controller for AM machines, Krampitz said. Experts at the University of Louisville are also working on algorithms that would tell an operator there’s a problem, Tackett said. “It’ll be six to eight months before we see that transition to machine manufacturers,” he said. Tackett said the lack of feedback built into the machines makes them incapable of interfacing with the Internet of Things. “We’re only right now at the phase of getting these machines smart enough to correct errors,” Tackett said.


Photo courtesy of SLM Solutions


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