Dr. Sudarsan Rachuri, Federal Program Manager for the Clean Energy Smart Manufacturing Innovation Institute, presented the goals and focus for CESMII and smart manufacturing.

Dr. Tony Schmitz, professor at UNC Charlotte, provided an overview of the team-building that led to the workshop, including planning grant support from the UNC Research Opportunities Initiative (ROI). He also provided the opportunity for collaboration with the upcoming research grant submission.

2017 UNC ROI research grantCenter for Manufacturing Data Science (C4MDS): Achieving Data-Driven Improvements in Manufacturing Processes

The TeamUNC Charlotte: Dr. Moutaz Khouja, Dr. Tony Schmitz, Dr. Scott Smith, Dr. Antonis Stylianou, Dr.

Kexin Zhao, Dr. John ZiegertUNC Chapel Hill: Dr. Noel Greis, Dr. Ashok KrishnamurthyNC State: Dr. Russell King, Dr. Gracious NgaileNC A&T: Dr. Cynthia WatersGeneral Electric: Dr. Jaydeep Karandikar, Mr. Mark TakacsArmy ARDEC: Dr. John SnyderTech Manufacturing: Mr. Jerry Halley

GoalThe research will build on the manufacturing digital thread by leveraging new discoveries in both “big data” and manufacturing science to achieve data-driven improvements at multiple levels.

Dr. Bin Wei, Manufacturing technology leader at GE’s Global Research Center, presented his view of smart manufacturing and highlighted current efforts and research directions at GE.

Dr. Noel Greis, professor at UNC Chapel Hill, provided an overview of manufacturing data science and presented a new concept for operator assignment to computer-controlled machines in factories.

Michael JonesManager, Generator Manufacturing DevelopmentSiemens Energy, Inc.Charlotte, NC

Tanya ScottDean, Business and Public Services Technologies DivisionWake Technical Community College

Brian SummersCNC Software, Inc. MastercamTolland, CT

Jerry HalleyEVP/Chief EngineerTech Manufacturing, LLC Wright City, MO

Phil MintzInterim Executive DirectorNCSU IESDirectorNorth Carolina Manufacturing Extension Partnership

Dr. John Ziegert, professor at UNC Charlotte, moderated a panel to discuss the current status of manufacturing data science.

A road mapping activity was completed. Attendees were separated into five groups. For each group, the participants were asked to: 1) list aspects of their future vision for manufacturing data science; 2) vote on those capabilities that were most important to improved productivity; 3) identify the current gaps that limit the implementation of manufacturing data science; and 4) vote on those gaps that are most critical. The results from the five groups were then compiled by the research team.

Future vision capabilities (votes) Future vision gaps (votes)Standard data format that enables full spectrum sharing and traceability (64)

Data collection, accessibility, and security (60)

Cybersecurity for small to large businesses (30)

Standard data format and data certification (33)

Optimization through automated data collection, software monitoring, and closed-loop control (29)

Connectivity from machine to enterprise including legacy machine upgrades (24)

Unification of new and legacy equipment (27)

Trained workforce (18)

Training to raise employee capabilities (24)

App-based platform for real-time data use (11)

Results of road mapping activity. Top five capabilities and gaps are listed.

The morning concluded with UNC Charlotte manufacturing and metrology laboratory tours.