Cloud-Based Industrial Plant Simulation System
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Solution Overview
Problem
Traditional process control simulation systems in industrial plants are often costly, complex, and difficult to maintain, with simulations becoming out of tune with actual plant operations due to separate configuration and execution from control functions, leading to inaccuracies and high operational expenses.
Innovation Solution
A cloud-based simulation system that synchronizes with real-time process control networks, using a thin client at the plant to collect data and update models periodically, allowing for accurate and cost-effective simulation without the need for extensive local hardware and expertise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional process control simulation systems are used, then simulation functionality is provided, but the systems are costly, complex, and difficult to maintain
Solution Approach 1:
The patent creates a virtual copy of the process control network in the cloud, replicating controllers, I/O devices, and process models. This virtual replica enables accurate simulation without requiring complex physical simulation hardware at the plant site, resolving the contradiction between simulation accuracy and system complexity
Solution Approach 2:
The patent introduces a cloud-based intermediary system that acts as a mediator between the plant's control network and simulation functions. The cloud platform handles the complex simulation processing remotely, allowing the plant to access accurate simulation capabilities without maintaining complex local simulation infrastructure
2Ease of operation
If simulations are configured and executed separately from control functions, then simulation operations can be performed, but the simulations become out of tune with actual plant operations
Solution Approach 1:
The patent implements continuous feedback mechanisms where the cloud-based simulation system receives real-time data from the actual control network and automatically updates its virtual models. This feedback loop ensures the simulation remains synchronized with actual plant operations while maintaining ease of operation through automated model updating
Solution Approach 2:
The patent performs preliminary configuration of the simulation environment in the cloud before plant operations begin. The virtual control network and process models are pre-configured to match the actual plant, and automatic synchronization mechanisms are established in advance to maintain fidelity without requiring continuous manual adjustment
3Measurement precision
If extensive local hardware and expertise are required, then accurate simulation can be achieved, but operational costs and complexity increase
Solution Approach 1:
The patent replaces extensive local hardware with a virtualized simulation environment in the cloud. The same simulation accuracy is achieved through software-based virtual controllers and process models, eliminating the need for expensive local simulation hardware and reducing deployment complexity
Solution Approach 2:
The cloud-based simulation platform provides universal access to simulation capabilities for multiple plants and users. A single cloud infrastructure serves multiple customers, reducing the need for each plant to maintain its own extensive simulation hardware while maintaining high simulation accuracy through shared resources
Data Source
AI summary
A system and method for operating a remote plant simulation system is disclosed. The system and method uses a light application at the plant to collect relevant data and communicate it to a remote plant simulation. The remote plant simulation uses the relevant data, including data from the actual process, to create a process simulation and communicate the display data to the light application operating at the plant where it is displayed to a user. The remote system offers the advantage of offering decreased cost and improved simulation as the equipment cost, operator cost and set up cost is shared by a plurality of users. Further, the data may be stored remotely and subject to data analytics which may identify additional areas for efficiency in the plant.