Dynamic Multi-Objective Optimization for Industrial Motorized Systems
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Solution Overview
Problem
Industrial motorized systems, such as pumping systems, often operate sub-optimally due to components being sized for maximum operational conditions, leading to inefficiencies and poor performance characteristics like energy efficiency, lifetime, and reliability at actual operating conditions, with existing methods failing to optimize these aspects effectively.
Innovation Solution
The system employs machine diagnostic and prognostic information to optimize business operations by selecting a desired operating point within an allowable range, considering performance characteristics of motorized systems, and using intelligent agents to dynamically adjust and optimize component performance based on real-time data and business objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If components are selected according to maximum operational conditions, then the system can meet peak demand requirements, but efficiency and performance characteristics deteriorate at actual operating conditions
Solution Approach 1:
The patent implements dynamic optimization that continuously adjusts system operation based on real-time conditions. The system transitions from static component selection based on peak conditions to dynamic adjustment of operating parameters, enabling the system to operate optimally across varying load conditions rather than being optimized only for peak demand.
Solution Approach 2:
The system changes operating parameters dynamically based on actual conditions. Instead of fixed parameters selected for maximum conditions, the optimization system adjusts parameters in real-time to match actual operating demands, improving efficiency across the full range of operational conditions.
2Productivity
If system operation is optimized for peak conditions, then maximum throughput is achieved, but system life and reliability deteriorate
Solution Approach 1:
The optimization system dynamically balances throughput and reliability based on real-time system state. Rather than operating continuously at peak conditions, the system adapts its operation to achieve optimal throughput while considering component wear, maintenance schedules, and reliability constraints, thereby extending system life.
Solution Approach 2:
The system performs preliminary optimization that considers future reliability implications. By incorporating maintenance schedules, component life cycles, and failure probability assessments into the optimization process, the system proactively adjusts operations to prevent excessive wear and maintain reliability while achieving throughput objectives.
3Device complexity
If traditional component selection methods are used, then design simplicity is maintained, but multi-objective optimization capability is lost
Solution Approach 1:
The patent introduces an intermediary optimization system that sits between the simple component selection and the complex multi-objective optimization requirements. This intermediary layer provides automated optimization capabilities without requiring complete redesign of the selection process, bridging the gap between simplicity and versatility.
Solution Approach 2:
The optimization system is designed to handle multiple objectives simultaneously (efficiency, reliability, cost, throughput) within a unified framework. This universal approach allows the same system to address diverse optimization goals without requiring separate specialized systems for each objective.
4Adaptability or versatility
If business objectives are integrated into system design, then operational alignment is improved, but design and operation complexity increases
Solution Approach 1:
The system introduces an intermediary optimization layer that translates high-level business objectives into specific operational parameters. This intermediary handles the complexity of aligning multiple business goals with technical constraints, shielding operators from the full complexity while achieving strategic alignment.
Solution Approach 2:
The optimization system implements feedback loops that continuously monitor both business objectives and operational parameters. This feedback mechanism automatically adjusts operations to maintain alignment with business goals, reducing the need for complex manual coordination and simplifying ongoing operations.
Data Source
AI summary
The invention provides control systems and methodologies for controlling a process having computer-controlled equipment, which provide for optimized process performance according to one or more performance criteria, such as efficiency, component life expectancy, safety, emissions, noise, vibration, operational cost, or the like. More particularly, the subject invention provides for employing machine diagnostic and/or prognostic information in connection with optimizing an overall business operation over a time horizon.