Datanomix and Caron Engineering Partner to Deliver Real-Time Performance Intelligence for Precision Manufacturers
Datanomix, the leading automated production intelligence platform, and Caron Engineering, the leader in manufacturing tool optimization technologies, announced a partnership to jointly develop data-driven solutions that leverage the companies’ manufacturing domain expertise in real-time production monitoring and machine tool optimization. This integration adds a new dashboard in the Datanomix platform that aggregates and displays the metrics for all Caron devices deployed in a factory. At Eastec they will show a single visualization for the job performance data from Caron Engineering’s adaptive tool monitoring system, TMAC, helping accelerate continuous improvement efforts across all jobs.
The data generated by today’s manufacturing machines offers tremendous opportunities to drive production insights, and Datanomix is using advanced analytics and machine learning to empower manufacturers to understand the state of their production in real time. Caron Engineering uses advanced sensors and signal processing techniques to improve machine performance, optimizing how CNC machines produce parts and measure tool usage to track tool wear and prevent costly repairs. This partnership and its resulting technology will help manufacturers proactively optimize whole-factory performance and profitability.
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“Manufacturers are demanding an integrated solution that delivers a rich visual experience around real-time job performance, predictive machine parameters, and cutting tool behavior over time,” said John Joseph, CEO and co-founder of Datanomix. “The combination of Caron Engineering and Datanomix delivers more real-time data for production than any other solution, providing incredible opportunities to apply data science to an industry segment in need of contextualized production intelligence. Together we will build the next generation of analytics solutions for precision manufacturers that covers the entire machine and production workflow.”
“There is a symbiotic fit between the tooling expertise at Caron and the data science capabilities at Datanomix,” said Rob Caron, founder and president of Caron Engineering. “This partnership lets us offer our installed base of thousands of customers worldwide an analytics and intelligence solution that spans from the cutting tools and machine health all the way to the executive suite. Data is at the heart of Caron’s strategy, and with Datanomix, we will be able to leverage our combined data into actionable insights that will help transform manufacturing at a practical level.”
Development efforts have been focused on integrating data from Caron systems for analysis and visualization through the Datanomix platform in the following ways:
- TMAC (Tool Monitoring Adaptive Control): A new Datanomix dashboard will display the status of every TMAC-enabled machine in the factory for a consolidated view of performance that accelerates job-level continuous improvement. Datanomix will present Caron performance parameters, including horsepower, vibration, pressure, strain, and coolant information for each TMAC machine. Users will be able to create alerts for out-of-tolerance conditions for rapid responses. Other Datanomix production charts and graphs for associated machines will include an active Caron Engineering icon that will let users drill down to Caron tool performance for that machine.
- DTect-IT (Machine Condition Monitoring): DTect-IT combines high-precision sensor technology with advanced analysis to monitor, detect, and correct anomalies in the machining process. Datanomix enables customers who need deeper analytics and optimization strategies for cutting unique parts to visualize DTect-IT data in the Datanomix platform. Existing Datanomix customers will be able to schedule installation of DTect-IT on any machine by clicking a purchase button in the Datanomix platform.
- AutoComp (Automatic Tool Wear Compensation Software): AutoComp processes measurement data from any electronic gauging device and automatically calculates and compensates tool offsets in the control, without any operator intervention. Datanomix can compare this part quality data with cutting data from the above systems.
- ToolConnect: (Tool Data Management System): ToolConnect automates the process of loading tools into the machine by automatically transferring tool offset data directly from the presetter to the CNC control, via RFID tags embedded in tool holders and 2D presetter-printed barcodes. The system is completely customizable to meet the users’ tool load specifications and records every step, action, and data exchange. This data is valuable as Datanomix analyzes how variations in tool geometry affect cutting data.
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“With Caron’s focus on data, it was a natural fit to collaborate on advanced analytics and visualizations,” said Greg McHale, CTO and co-founder of Datanomix. “Customers who implement Caron or Datanomix are looking to understand exactly what’s happening with every part they manufacture. We envision a data-driven future that visualizes production starting with raw materials, to machining, to the finished part, leaving manufacturers with insights into productivity, continuous improvement, maintenance, and business optimization. We couldn’t ask for a better partner than Rob Caron and his team to accelerate this future for our customers and theirs.”
Both Caron and Datanomix put customers first, and feedback and suggestions from customers have been a critical aspect of designing and developing solutions that deliver added value for users of both companies’ solutions.
“At Nikel Precision Group, data and analytics are core value drivers, helping us meet our customers’ exacting requirements and demanding production schedules,” said James Bell, vice president of operations at Nikel Precision Group LLC. “As a customer of both Caron and Datanomix, Nikel Precision Group is getting tremendous value from the real-time data driven by each of their solutions. We’re excited about the potential enabled by the depth of experience in manufacturing and data science of these two teams.”
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