Machine and Process Health Monitoring​


Project Lead: Litmus Automation

Member % Cost Share: 50%
CESMII % Cost Share: 50%
Duration: 6 Months

Problem Statement

The manufacturing customer’s CNC machine’s status are not monitored through a system and manual supervision is required to capture any machine deviations that result in the current scrap rate of 10%.

Project Goal

  • Reduce overall scrap for the CNC machine by 10%.
  • Reduce the maintenance performed on a machine by 15%.
  • Improve throughput of the CNC machine by 10%.
  • Showcase how the CESMII SM Profiles can be used to model a manufacturing process and optimize its maintenance processes and production throughput.

Technical Approach

  • Establish connectivity to CNC machines and extract data into Litmus Edge. Develop new machine drivers if necessary.
  • Develop the SM profile for maintenance and process throughput, and share data with SMIP.
  • Configure data comparison to ideal settings and take pre-emptive active to trigger alerts, capture machine metrics for visualization and anomaly detection. 

Key Tasks & Milestones

  • Document KPI’s and data sources, establish connectivity to the machines.
  • Data transmission is setup, SM Profile is created, data is reported to SMIP, KPI’s and visualizations are implemented, and solution demonstration is completed.
  • Project sign-off is completed, Implementation success story is completed, and enterprise-wide roll-out plan is delivered.

Potential Impact

The global Industrial Valve market size is valued at US$48 Billion and is expected to grow at a CAGR of 12.3% fueled by growth in Pharmaceuticals and Healthcare.  By adopting the CESMII SMIP, valve manufacturers can  reduce inefficiencies in their processes, look to grow market share by being more competitive (i.e. by having higher quality products) and reduce ongoing production costs.


  • A reusable SM Profile for an Industrial Valve CNC machine manufacturing process that can be configured and/or adopted by other manufacturers, technology providers and researchers for development of SM solutions.
  • A real-time data visualization in the SM Marketplace (for use by members under license from Litmus Automation).
  • A real-time anomaly and defect detection App in the SM Marketplace (for use by members under license from Litmus Automation).
  • An industry use case example for the use of SMIP and SM Profiles.
  • A methodology for using Edge compute within the plant floor to calculate KPI’s, monitor processes and incorporate quality criteria using real-time data. 

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