Edge Computing for MTConnect Machine and Process Monitoring for AI-Based PHM
Project Lead: TechSolve, Inc.
Partners: Spirit Aerosystems, Caron Engineering
Member % Cost Share: 100%
CESMII % Cost Share: 0%
Duration: 18 Months
Problem Statement
Across many industries, 15%-40% of manufacturing costs are typically attributable to maintenance activities. Unscheduled or frequent breakdowns create significant obstacles to the development of a sustainable factory floor with robust infrastructure. Therefore, predicting the future state of manufacturing assets and processes.
Project Goal
This project aims to develop a PHM system that will demonstrate the ability to conduct monitoring and prognostics for manufacturing assets through the use of an edge computing solution for sensor signals, the MTConnect standard, cloud data storage and IA techniques.
Technical Approach
The solution will be developed, evaluated, validated and demonstrated using spindle bearings degradation data and cutting tool degradation tests from TechSolve’ s spindle test-bed and machining centers, respectively.
Deliverables/Outcomes/SM Marketplace
- CNC Machine SM Profile
- Spindle Test-Bed SM Profile
Potential Impact
This project will support the current industrial needs for a more accurate and predictive approach to manufacturing asset health condition evaluation. Considering that the combination of vibration, electrical current/power and temperature can be used to assess the condition of various systems, the solution will be applicable to a wide range of applications from multiple industries for discrete and continuous manufacturing. The project will leverage and demonstrate the benefits of SM Platform not only to CESMII membership but also to the manufacturing community in general, and the small and medium size manufacturing in particular.
Benefits
The proposed solutions contributes to energy efficiency and productivity improvements (estimated to 20% or higher), reduction in cost and time to deploy smart manufacturing technologies. A successful completion of this project will provide to CESMII member companies an example of how MTConnect and CESMII’s Smart Manufacturing Platform can be integrated to monitor and predict the health of manufacturing assets and processes.
