NASCAR champion Brad Keselowski has joined the ranks of entrepreneurs in the metalworking industry while continuing his successful racing career.
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We all know the buzzwords circulating around digital data and the factory. You have heard them—Industry 4.0, smart factories, data analytics, and artificial intelligence (AI). The question we all have is how will this impact workers in the long term? What do these terms really mean? Nevertheless, both traditional software suppliers and makers of advanced manufacturing equipment are offering digital solutions.
For machine shops in a competitive global marketplace, keeping spindles running and making product is the only way to stay in business. Still, adding a new piece of equipment, even with the promise of improving the efficiency of your existing ones, may be a difficult sell to management.
Changes in health care are driving more innovative tooling, including new machining strategies and complex cutting tools that help deliver more patient-centered solutions.
One of the key advantages of additive manufacturing is its digital thread, which allows for rapid communication, iteration, and sharing of a design model and its corresponding physical representation. While this enables an efficient design process, the flow of data opens vulnerabilities to cyber-attack.
The U.S. auto industry has been automated for decades. Production of cars and trucks is associated with large, hulking robots fenced off from human employees. Inside those fenced off areas, tasks such as welding are performed. The industry, though, is advancing on the automation front.
The world of additive manufacturing (AM), commonly referred to as 3D printing, is quickly changing. The technology allows companies to manufacture products faster, with greater variation, and often with entirely new forms and functions.
The state of manufacturing is always a combination of tried and true methods; improvements (sometimes dramatic) in traditional processes; and brand new technology few people even conceived of a few years ago.
The bane of modern engineering is complexity. One promise of artificial intelligence and machine learning is helping engineers to use complex tools and harness vast data sets effectively.
My involvement in SME and its AeroDef event began in 2014, when I first presented an Adaptive Machining Overview at AeroDef 2014 in Long Beach, Calif. At the time, the conference was relatively small in terms of attendees and exhibitors in comparison to the explosion of other engineering conferences that began around that time.