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New systems, software and processes are replacing so-called islands of automation with seamless, automated manufacturing lines that boost overall equipment effectiveness (OEE) from 30 to 80% or more. Like a chess master, these systems think multiple moves ahead on the factory floor to ensure continuing production when circumstances change.

A team of researchers from UC Berkeley, led by Pieter Abbeel, is working on the creation of smart robots that are teachable and can learn new skills without pre-programming. Abbeel and his team also formed a startup called Embodied Intelligence with the aim of developing artificial intelligence (AI) software to enable robots to learn from humans to perform complex tasks.

While cameras and motion control have worked in tandem for at least 15 years, their integration has improved because networks have gotten faster, more reliable, and more deterministic (i.e., nothing will interfere with a function that’s a priority).

In today’s booming software landscape, you see highly dynamic teams quickly iterating to develop and improve their products. Yet while the world’s software creators have learned to “move fast and break things,” hardware developers are still (slowly) moving to adopt a more agile product development methodology.

Efficient manufacturing calls for coordinated systems of shop personnel, equipment and software. These systems increasingly include robotic technology, as manufacturers recognize the reliability, repeatability and flexibility that robots provide. According to the International Federation of Robotics, the number of industrial robots in use worldwide will increase to around 2.6 million by 2019, about one million more than in 2015. Approximately 70% of industrial robots are used in the automotive, electrical/electronics and metal and machinery industries.

Manufacturers must wrestle with the “Black Hats” of the cyberworld in order to keep processes secure

An eternal truth is that manufacturing will always push the limits on cost, performance, and especially quality. “Tolerances never get looser, they always get tighter,” remarked Gene Hancz, product specialist, CMM of Mitutoyo America Corp. (Aurora, IL).

Parker Hannifin’s Marissa Tucker talks with Senior Editor Patrick Waurzyniak

A conversation between Smart Manufacturing Editor in Chief Brett Brune and Sridhar Kota, professor of mechanical engineering at the University of Michigan and Executive Director of MForesight. 

Within manufacturing, a shift has begun to extend big data analytics and condition monitoring beyond the factory door to both ends of the supply chain—to customers, other end users and to second-and third-tier suppliers.