Faster “time-to-value” with small form factor edge data acquisition and pre-built analytics.
Wi-NEXT enables manufacturers to drive positive ROI by leveraging our advanced machine learning and analytics platform which includes not only traditional statistical process control (SPC), but also sophisticated pre-built algorithms that help companies to predict earlier where, when and why assets will fail as well as flag early identification of poor quality issues.
We provide a best-of-breed, stand-alone IIoT solution, available as On-Premise, In-Cloud or Hybrid.
Starting with an advanced data pipeline creation system that continuously ingests data from different sources, our platform performs analysis in real-time with powerful and pre-built algorithms, presenting a sophisticated decision management system on a simple to understand dashboard.
The Wi-NEXT machine learning and advanced analytics platform performs aggregation from different data sources and executes data conversion of unstructured data into a contextualized production scenario.
AND ADVANCED ANALYTICS
The Wi-NEXT platform applies machine learning and advanced analytics to parse data streams, either from one single machine or entire plant floors.
Thanks to pre-built algorithms and data models tailored to OEE best practices, our customers need time and resources are reduced to a fraction of what was required before: from setting up the analytics to addressing every possible asset and quality issue fast and timely.
Why process and perform analysis of massive amounts of data if you do not have the capability to present the results in an actionable and easy-to-comprehend, contextualized way?
Wi-NEXT’s machine learning and advanced analytics uses a responsive dashboard to display the right recommendations to the right people (plant manager, operations manager, aftermarket operators, corporate managers, etc.).
It represents a unique tool that helps customers make the right decisions in real-time without the need for lengthy and expensive results interpretation.
Machine learning and advanced analytics main features :
Simple and friendly user interface for master data entry and modification
Easy-to-install, pre-configured software and content stack
Out-of-the-box data source connectors and models, dashboards, and reports to reduce the need for additional services
Expansion capability to quickly include content for specific industry and business applications
Data streams from many sources for data aggregation
APIs for integration and customization
Expansion of the included content for specific industry and business applications
Integrated Enterprise Asset Management systems, Business Process Management, or other services
Descriptive, predictive, and prescriptive analytics as well as data and text mining
Menu-driven interfaces (no programming required) to create predictive models
Asset health modeling based on real-time event data – measurements, logs, alarms, repair history
Product anomaly detection for product uniformity issues and outliers provides lot inspection recommendations
Decision Management methodology optimizes decisions at the point of impact, balancing resource and costs constraints
Asset and process business rules of the organization combine to enhance decision making
“What-if” simulations accommodate changing operational conditions
Optimized decisions sent directly to decision-makers
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