ChiAha™ offers a Digital Twin toolkit that utilizes high-fidelity simulation and prescriptive analytics to model production operations with 1% accuracy. This technology enables manufacturers to optimize Overall Equipment Effectiveness (OEE) and enhance decision-making by evaluating multiple production scenarios in real-time.
Funding
Funding not disclosed
Founders
Product
Problem
Manufacturers often struggle to optimize production line performance due to the complexity of interconnected processes and the difficulty of predicting the impact of changes. Traditional methods for evaluating production scenarios are time-consuming, require specialized expertise, and may not accurately reflect real-world conditions. This leads to suboptimal Overall Equipment Effectiveness (OEE) and missed opportunities for improvement.
Solution
ChiAha provides a Digital Twin toolkit that enables manufacturers to model their production operations with high-fidelity simulation and prescriptive analytics. The toolkit uses line event data to create accurate virtual models, allowing users to evaluate the impact of various OEE optimization options in real-time. By simulating hundreds of scenarios, ChiAha helps users identify the optimal machine speeds, assess the effects of close-coupling, and predict production increases resulting from system changes. The software's user-friendly interface allows users to quickly adopt and implement Digital Twin technology without extensive technical knowledge.
Target Audience
The primary users are plant managers, analysts, production designers, engineers, and operations personnel working in high-speed/high-volume production operations in industries such as food and beverage, consumer products, electronics, pharmaceutical, bulk material handling, pulp and paper processing, and oil and gas.
Features
- High-fidelity simulation of production lines with statistically modeled, data-driven behavior
- Prescriptive analytics to evaluate the impact of OEE optimization options
- Ability to model production operations in minutes
- Real-time data integration for monitoring and analysis
- Prediction of production line performance and OEE within 1% accuracy
- User-friendly interface for quick adoption and implementation