AI Chiller And Pump Control for KPI Setpoint Optimization
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Solution Overview
Problem
Smaller entities and those without defined use for AI systems face barriers in applying AI due to lack of infrastructure and expertise, and existing AI systems are ineffective as they lack knowledge from domain experts, limiting their ability to optimize industrial process KPIs.
Innovation Solution
A system that aggregates information from end users, including KPIs, process variables, and equipment constraints, using an AI agent to optimize KPIs by determining effective process variable setpoints and evaluating optimization capability, accessible to users without AI experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing AI systems are deployed to optimize industrial processes, then prediction capabilities are provided, but decision-making capabilities and domain expertise integration are lacking
Solution Approach 1:
The patent combines prediction functionality and decision-making functionality into a single integrated AI system. The system merges the strengths of predictive analytics with actionable decision recommendations, allowing the same AI system to both forecast outcomes and suggest optimal actions based on domain expertise and business objectives.
Solution Approach 2:
The AI system is designed to perform multiple functions: it can predict future states, generate actionable decisions, and adapt to different business objectives. By making the system multi-functional, it eliminates the need for separate prediction and decision-making systems, thereby improving versatility while maintaining prediction accuracy.
2Ease of operation
If AI systems are made accessible to smaller entities, then accessibility improves, but infrastructure requirements and expertise demands increase
Solution Approach 1:
The system enables domain experts to directly input their knowledge and business objectives without requiring AI expertise. The AI system automatically processes this input and generates optimized decisions, allowing smaller entities to benefit from AI without needing dedicated AI infrastructure or expertise.
Solution Approach 2:
The patent introduces an intermediary layer that translates domain expert knowledge into AI-compatible formats automatically. This intermediary handles the complexity of AI system configuration and interaction, shielding users from infrastructure complexities while maintaining accessibility for smaller entities.
3Reliability
If domain experts configure AI systems directly, then domain knowledge is integrated, but AI system configuration complexity increases
Solution Approach 1:
The system uses templates and pre-configured structures that capture domain expertise patterns. Instead of requiring experts to build AI systems from scratch, they can copy and adapt proven configurations to their specific needs, reducing configuration complexity while maintaining reliable domain knowledge integration.
Solution Approach 2:
The patent allows domain experts to configure AI systems by adjusting high-level parameters and business objectives rather than dealing with low-level AI technicalities. By abstracting the configuration to parameter-level adjustments, the system maintains reliability through domain expertise while reducing apparent complexity for users.
Data Source
AI summary
Methods and systems are disclosed for determining a plan to optimize key performance indicators (KPIs) of an industrial process. Such a plan is determined based on generating a query for information associated with the KPIs and based on receiving user-provided object information corresponding to the KPIs. The method includes receiving, at a user interface, one or more KPIs associated with an industrial process. The method includes generating, based on the one or more KPIs, at least one query for information associated with the KPI. The method includes receiving, at the user interface, a response to the at least one query. The method includes determining, by an artificial intelligence agent, a plan for optimizing the KPI.