MTConnect Challenge Finalists Announced
The second MTConnect Challenge tasked participants with developing software applications based on the open-source communication standard.
The National Center for Defense Manufacturing and Machining (NCDMM) and AMT–The Association For Manufacturing Technology have announced the five finalists of the MTConnect Challenge 2. All finalists will present their MTConnect-based software applications at the [MC]2 2014 MTConnect conference, to be held April 8-10 in Orlando, Fla. Attendees will vote to award $225,000 in cash prizes to three winners.
The top five entries are:
- Expanding Manufacturing's Vision: MTConnect + Google Glass, Joel Neidig, Itamco
- Promise by Shane Crandall
- MTConnect for Microsoft Visio, James Finn, International TechneGroup
- Interactive Work Instructions (IWI), Donovan Buckley and Arvind Rangarajan, GE Global Research, PARC
- MTConnect and NI Measurement Studio Integration, Valerie Pezzullo, Clemson University.
The MTConnect Challenge 2 challenged participants to develop software applications that could be easily adopted by manufacturing enterprises, especially lower-tier producers, to enhance their manufacturing capabilities and support Department of Defense supply chain management goals. Entries were judged based on their benefit to manufacturing intelligence, creativity and innovation, practicality of concept, impact on industry, and overall quality.
Related Content
-
Shop Moves to Aerospace Machining With Help From ERP
Coastal Machine is an oil and gas shop that pivoted to aerospace manufacturing with the help of an ERP system that made the certification process simple.
-
How to Scale a Job Shop for Growth with Fewer People
Front office disorganization and poor shop floor communications don’t just reduce a job shop’s efficiency; they are a barrier to growth. Having the right kind of ERP system can be the key to improving profitability and scaling for future growth
-
AI Chip Flushing Keeps the Lights Out
Swiveling, camera-guided coolant nozzles solve a CNC machining automation problem that is ideal for artificial intelligence (AI).