Virtual Offshore Plant Simulator for Condition-Based Maintenance
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Solution Overview
Problem
Current condition-based maintenance systems for offshore plants are costly and prone to human error, requiring high operation and maintenance costs, and are not adequately equipped to handle the unique challenges of deep-sea environments, necessitating a more advanced system for managing failure modes and extending the life span of offshore facilities.
Innovation Solution
A method and apparatus utilizing a distributed control system, real-time data management, and a virtual offshore plant simulator to implement condition-based maintenance, including a SCADA system, data mapping, learnable failure mode management, and a virtualization system for predictive maintenance and operation training, enabling efficient and reliable operation of offshore plants.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional condition-based maintenance systems are used for offshore plants, then maintenance can be performed based on equipment condition, but the systems are costly and require high operation and maintenance costs
Solution Approach 1:
The patent creates a virtual copy of the offshore plant through virtualization technology, where a virtual model replicates the physical plant's behavior and failure modes. This virtual copy allows maintenance simulation and prediction without requiring complex physical intervention systems, reducing operational complexity while maintaining reliability.
Solution Approach 2:
The patent replaces traditional mechanical monitoring and maintenance intervention systems with software-based virtualization and simulation. The virtual plant model substitutes physical diagnostic equipment, and automated algorithms replace manual maintenance decision-making, reducing the complexity of physical maintenance systems.
2Reliability
If conventional condition-based maintenance systems are used for offshore plants, then maintenance can be performed based on equipment condition, but the systems are prone to human error
Solution Approach 1:
The virtual plant model performs self-diagnosis and self-prediction of failure modes through automated algorithms. The system monitors its own virtual sensors, detects anomalies, and predicts maintenance needs without human intervention, eliminating human error in diagnostic decisions while maintaining high reliability.
Solution Approach 2:
The patent implements closed-loop feedback where the virtual plant continuously monitors its own state, compares it against learned failure patterns, and automatically adjusts maintenance predictions. This automated feedback mechanism eliminates human error in interpreting maintenance data while improving reliability through consistent algorithmic decision-making.
3Duration of action of stationary object
If traditional preventive maintenance methods are used, then maintenance can be performed on a scheduled basis, but the methods do not efficiently extend the life span of offshore facilities
Solution Approach 1:
The virtual plant model predicts failure modes and maintenance needs before they actually occur in the physical system. By performing preliminary analysis in the virtual environment, the system identifies potential issues early, allowing proactive maintenance planning that extends facility life span while optimizing maintenance timing to avoid unnecessary interventions.
Solution Approach 2:
The patent transitions from static scheduled maintenance to dynamic condition-based maintenance. The virtual plant continuously adapts maintenance predictions based on real-time operational data and changing failure patterns, optimizing maintenance timing dynamically to extend facility life span while maximizing productivity by performing maintenance only when truly necessary.
Data Source
AI summary
Provided is a method and apparatus for managing failure modes for condition based maintenance in marine resource production equipment. The apparatus includes a distributed control system (DCS), monitoring, and performance evaluation module that constructs a distributed control system for the systematic collection and management of maintenance data, develops a real-time data management and monitoring system, and develops an offshore plant performance monitoring level performance evaluation system, a condition based maintenance platform that maps data from a real-time sensor database of the distributed control system (DCS), monitoring, and performance evaluation module, stores the mapped data, and manages learnable failure modes based on normal mode and failure mode data, a diagnosis, prediction, maintenance, and shape management module that develops technology for automatically improving the reliability of condition based maintenance based on the learnable failure mode management according to data transmitted from the distributed control system (DCS), monitoring, and performance evaluation module to the condition based maintenance platform, develops an offshore plant diagnosis, prediction, and maintenance system, and develops a diagnosis and condition based maintenance operating platform and a shape management system, and a virtual offshore plant simulator that constructs a virtual offshore plant simulator, constructs a scenario based operation training system, and develops a condition based maintenance solution and an input and output virtualization system for interoperation with a supervisory control and data acquisition (SCADA) system for an offshore plant.