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Five-Axis CAM Slices Into Food Processing

Urschel Laboratories has come a long way since its founder William E. Urschel introduced the gooseberry snipper to Michigan canneries in 1910. Today, the company’s innovative machines are used by virtually every food processing manufacturer worldwide to slice, dice, trim, grate, and process foods that are stored in pantries and refrigerator shelves. For the record, Urschel’s gooseberry snipper machine handled the removal of a stem and thick bud appendage from the berry.

Good Times in Thermoplastic Composites

Thermoplastic composites are gaining traction in manufacturing applications, offering benefits like lighter weight, faster production times, longer shelf life and easier shipping compared with metals or other composites.

Diebold Nixdorf moves to Anaqua Platform

Anaqua, Inc., a leading provider of Intellectual Property (IP) management, today announced that Diebold Nixdorf has selected the ANAQUA platform to manage its global IP portfolio from its operations in the U.S. and Germany.

Berkeley lab hopes to birth teachable robotic systems

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.

Three perspectives converge on smart manufacturing

Manufacturers continue to be bombarded with an onslaught of technology terms, as well as different ideas on where to begin and how to proceed. This confusion has slowed the adoption of new technology. Yet a big opportunity for a huge increase in efficiency awaits.

Removing mental roadblocks to improving operations

It’s a familiar scenario at the factory. Quality issues have reared their ugly heads, requiring rework, causing backorders, delaying shipments, and driving tense daily customer calls. Meanwhile, the team works to address production issues using a mix of day-old post-mortem reports, shop-floor observations captured on notepads, and other operational data summarized on spreadsheets and sticky notes.