Tucson, AZ – Eclipse Data Innovations, the company behind the innovative SourceOne® Enterprise Knowledge Performance System (EKPS), has unveiled a significant expansion to its platform. This update empowers operations teams in large industrial organizations to effortlessly build custom, AI-powered workflow applications using natural language and their own operational data.
This groundbreaking enhancement means companies can now rapidly create specialized operational tools to tackle unique business challenges without the lengthy and complex traditional software development cycles. Eclipse highlights that this release significantly boosts SourceOne’s advanced analytics and Operations Research capabilities, making sophisticated optimization, simulation, and decision-support tools more accessible across critical sectors like mining, manufacturing, and construction.
Addressing High-Cost Operational Challenges
The new functionalities are specifically designed to help organizations overcome costly operational hurdles. These include optimizing equipment and labor, implementing predictive and prescriptive maintenance strategies, streamlining supply chain coordination, enhancing materials flow visibility, improving quality and yield, and boosting energy and resource efficiency. Eclipse emphasizes that while operational environments vary by industry, the core analytical and decision-making problems often share structural similarities across large-scale operations.
Karin Boan, COO of Eclipse Data Innovations, commented on the release: “For decades, operations teams have had to adapt their workflows to the limitations of enterprise software. With this release, the people who understand an operational problem best can now create practical tools around their own workflows and data, without waiting on lengthy development cycles.”
A Unified Knowledge Framework for Modern AI
Unlike rigid conventional enterprise systems, SourceOne integrates disparate operational information into a cohesive knowledge framework. This framework supports advanced analytics, optimization, simulation, and AI-assisted decision-making, all while seamlessly complementing and extending existing infrastructure.
Boan added, “Most industrial organizations already have decades of valuable systems and operational data. The challenge is that those systems were never designed to work together with shared operational context. SourceOne preserves and extends those investments by creating the context that modern AI and advanced analytics require to succeed.”
Enhanced Optimization and Accessibility
A central feature of this release is the expanded Operations Research capabilities. This provides broader access to advanced optimization modeling, sophisticated simulation workflows, and in-depth operational scenario analysis. These powerful tools can now be applied directly to daily business decisions with unprecedented speed and confidence.
Sean Hunter, Director of Product Development at Eclipse Data Innovations, explained: “Optimization and analytical tools have traditionally been difficult to use, isolated within specialized teams, or disconnected from operational workflows. SourceOne makes these capabilities more accessible by combining operational context, integrated data, and AI-assisted workflows so organizations can rapidly build and refine tools around their specific operational requirements.”
Hunter noted that while this latest release shares similarities with other innovative technologies, it stands out with more powerful analytic engines specifically tailored for heavy industry.
Model-Based Architecture for Real-World Impact
SourceOne’s model-based architecture leverages Data Ontology and Knowledge Graph technologies to organize fragmented enterprise information into a rich operational context. This foundation supports advanced analytics, AI systems, and decision-support models, enabling organizations to develop workflow-specific applications that accurately reflect real-world operational conditions and complex relationships across the entire enterprise.
Visualizing the Future of Industrial AI
To illustrate the power of SourceOne EKPS, consider the following examples of how data and AI are transforming industrial operations:
AI-Powered Manufacturing Dashboard
An AI dashboard provides real-time insights into manufacturing processes, displaying critical metrics like temperature, pressure, humidity, and overall equipment effectiveness (OEE). It can also monitor sensor data for vibrations and detect anomalies, issuing alerts for potential issues. This allows for proactive maintenance and optimization of production.
Data Analytics in Smart Factories
Smart factories leverage data analytics to optimize production. This involves collecting data from various sources, processing it to gain actionable insights, and visualizing it to make informed decisions. This approach leads to improved efficiency, reduced downtime, and better resource utilization.
Knowledge Graphs for Operational Context
Knowledge graphs are crucial for organizing fragmented enterprise information into a unified operational context. They map relationships between different data points, enabling advanced analytics and AI systems to understand complex operational conditions and make more accurate predictions and recommendations.
Real-time Manufacturing Dashboards
Real-time dashboards are essential for monitoring and controlling manufacturing processes. They provide a comprehensive overview of key performance indicators, allowing operators and managers to quickly identify trends, detect issues, and make timely adjustments to optimize production flows.
Manufacturing Analytics Workflow
The process of manufacturing analytics typically involves collecting data from operators or machines, summarizing and calculating insights in real-time, and then analyzing and improving operations based on these insights. This continuous feedback loop drives efficiency and innovation.