Keywords
Intelligent Process Control Systems, Wastewater Treatment Plants, Interoperability, Visual workflows, Data Mining
Start Date
27-6-2018 2:00 PM
End Date
27-6-2018 3:20 PM
Abstract
One of the major problems to design and implement a control/supervision system for a process lies in the need to establish an ad-hoc system for each process installation. On the other side, an open challenge related to the deployment of Intelligent Decision Support Systems (IDSSs) is the interoperability of the different methods used, in order to allow interaction and reuse of different data mining methods and the use of methods based on a model or an expert. Thus, this paper proposes the use of visual workflows, to enable the automation of the design task and the implementation of Intelligent Process Control Systems. The framework will allow the user to specify the design and control of a concrete process as well as the required data-driven and expert-models using a graphical workflow environment. The framework is based on a three-layer architecture: first, a comprehensive data science flow description layer (dataflow layer) to produce/discover data-driven models from process data; Second, a flowchart of the different components of the process (process-design flow layer) which can be used as a GUI or/and to obtain a simulation model from the design. Finally, the on-line intelligent process control system (process control workflow layer), where the different data-driven models, expert-based models and intelligent reasoning methods interoperate to control and supervise the process. Thus, the resulting system can automatically generate both simulation models of the process and programming code to control and supervise the process, from the workflows designed for each particular installation. The case study is focused on the supervision of a Wastewater Treatment Plant (WWTP).
An Interoperable Workflow-based Framework for the Automation of Building Intelligent Process Control Systems
One of the major problems to design and implement a control/supervision system for a process lies in the need to establish an ad-hoc system for each process installation. On the other side, an open challenge related to the deployment of Intelligent Decision Support Systems (IDSSs) is the interoperability of the different methods used, in order to allow interaction and reuse of different data mining methods and the use of methods based on a model or an expert. Thus, this paper proposes the use of visual workflows, to enable the automation of the design task and the implementation of Intelligent Process Control Systems. The framework will allow the user to specify the design and control of a concrete process as well as the required data-driven and expert-models using a graphical workflow environment. The framework is based on a three-layer architecture: first, a comprehensive data science flow description layer (dataflow layer) to produce/discover data-driven models from process data; Second, a flowchart of the different components of the process (process-design flow layer) which can be used as a GUI or/and to obtain a simulation model from the design. Finally, the on-line intelligent process control system (process control workflow layer), where the different data-driven models, expert-based models and intelligent reasoning methods interoperate to control and supervise the process. Thus, the resulting system can automatically generate both simulation models of the process and programming code to control and supervise the process, from the workflows designed for each particular installation. The case study is focused on the supervision of a Wastewater Treatment Plant (WWTP).
Stream and Session
Stream B: (Big) Data Solutions for Planning, Management, and Operation and Environmental Systems
B3: Sixth Session on Data Mining as a Tool for Environmental Scientists (S-DMTES-2018)