Datanomix Announces Automated Downtime Insights
Datanomix, maker of the industry’s only Automated Production Intelligence software platform, announced a major new capability, Automated Downtime Insights. This capability furthers the company’s mission to deliver the next generation of production monitoring and expands its lead as the industry’s only hands-free production monitoring platform.
The Datanomix Platform is known for automating the collection and analysis of manufacturing data and delivering deep insights into production performance, both in real-time and over-time. Designed for growth-oriented precision manufacturers, the Datanomix platform delivers industry-leading innovation of manufacturing productivity with no operator input required, and without burdening the end user with cumbersome analysis or data crunching.
Recommended AI News: IXL Learning Acquires Language Learning Software Developer Curiosity Media
Many first-generation monitoring systems require operators to enter reason codes when a machine has gone down, an approach that has resulted in the broad failure of many monitoring projects. The combination of labor shortage challenges, operator apathy towards manual data entry, and the general lack of utility of downtime reason codes has caused widespread industry frustration.
Automated Downtime Insights are a significant capability that Datanomix has added to an already impressive platform. Using advanced analytics techniques, Datanomix can automatically determine expected and unexpected downtime events and derive reasons for those downtime events during live production.
While the Datanomix platform has never required operator input or downtime reason codes to provide valuable insights, this functionality offers additional process improvement opportunities for companies that need to increase performance in the current labor-constrained and demand-heavy environment.
“Automated Downtime Insights are yet another significant feature that is the direct result of deep customer collaboration, an approach that has been core to our identity since day one,” said Greg McHale, Co-Founder and CTO of Datanomix. “Automatically determining expected vs. unexpected downtimes and annotating those with reasons that are derived from the machine data inside of the Datanomix platform is a major accomplishment for our team and provides a clear target for our customers on not just which processes to improve, but which steps in those processes provide the greatest opportunities for consistency and margin improvement.”
Simply visualized and annotated within the Datanomix platform, Automated Downtime Insights offer a clear picture both real-time and over-time as to the sources of variance within critical processes. Existing Datanomix customers receive this capability via routine updates the company provides as part of its subscription service.
The Datanomix platform distances itself from first-generation production monitoring by offering a solution that focuses on the user experience with the following innovations:
- No Operator Input: Stop pulling operators away from machines for data entry—data is pulled directly from machine controllers to deliver contextual insights automatically
- Benchmarks, Scores & KPIs: Automated job performance data for every single part made on every machine, with no configuration—just insights based on derived benchmarks
- Visualizes Existing Workflows: Production meetings, continuous improvement, margin opportunities, and more—matches the way manufacturers work
- Reports & Dashboards: From day one, standard reports and dashboards provide actual insights and direction—not raw data that still needs processing
- Best-of-Breed Integrations: Work with top partners to provide solutions to real problems—not just simple data connections that may offer value
- Elevate Company Communication: Consistent, accurate metrics provide a common data language for the entire team—everyone is on the same page
- Workforce Training: Datanomix reports and trend charts show work cell improvement over time – it tells the complete story
[To share your insights with us, please write to firstname.lastname@example.org]