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Inobvious Automation

Improvement to manufacturing will come from addressing inefficiencies we do not currently see. Until then, we underestimate manufacturing’s potential.

Peter Zelinski
Peter Zelinski
Former Editor-in-Chief, Additive Manufacturing

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Think “machining automation,” and the image that comes to mind might resemble this month’s cover (image at right). Using a robot to load parts and an indexer to reorient them represent two obvious cases of automation within machining. This picture was taken at Straitline Components, subject of this article.

 
Other varieties of automation are not as obvious. Indeed, the idea of “automation” encompasses far more than loading parts. It might even involve the streamlining of certain steps that it never occurred to us to automate.
 
This article describes such a case. We soon can expect that a software utility might seamlessly present us with appropriate tools for particular machined features, including tools the shop hasn’t used or considered before. The engineering step of searching out cutter selections is not something we might have thought of as a candidate for automation. Instead, seeking the right tool (and sometimes not finding it) seems like an inescapable fact of production.
 
However, the largest part of the drag on any production process is probably found in disconnects such as this one. That is, the places where a human being has to act or make a judgment in order for the process to proceed. We take a lot of these human roles for granted—until we don’t. Lean manufacturing sometimes shocks a manufacturing staff into seeing that an effort or step performed for a long time is no longer necessary. Technology sometimes does the same thing.
 
Edwin Gasparraj, founder of digital manufacturing consulting firm Six Digma, recently described to me a technology change that he expects. White-light scanners are reaching the point at which they could provide a precise 3D picture of a machine’s work zone, he says—including every clamp. Meanwhile, technology within graphics cards already used in gaming could compare this 3D snapshot with the rendering of an NC program. Thus, collision avoidance could be an automatic part of the machine tool. Gone would be much of the simulation, program prove-out, scrupulous setups and other steps we take for fear of crashes. All that time and attention would be saved.
 
Whenever we imagine processes getting better, we tend to imagine low-hanging fruit. We envision the most obvious inefficiencies changing for the better. What we cannot envision nearly as well are the inefficiencies that are less apparent—the fruit still hidden in the branches. Last month, I wrote about the industry’s challenge in finding skilled manufacturing labor. This is a serious challenge that will entail serious solutions. Yet there is also this other factor in play. Namely, tomorrow’s talent gaps will not apply to today’s shops and processes. Instead, they will apply to tomorrow’s shops and processes, which will be different. Technology will advance, individual facilities will advance in individual ways, and both types of advances will trend toward making manufacturing more seamless. As a result, the capabilities of manufacturing employees might need to be even greater in the years to come, but the number of employees needed will be fewer. 
 

 

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