Causality analysis methods are initiated by multivariate statistics used in other fields. Due to its strong capability to identify the relationship between the variables and also the prediction, many efforts have been spent to run these methods in the chemical industry field. Nearest neighbor method, with its simplicity to understand and implement, has been applied in this research to analyze the root-cause in the chemical plant. Simulation based on simple relationship between 2 variables has shown that nearest neighbor method is able to analyze the relationship between 2 variables in term of influence. It is able to analyze the root-cause in industrial case study. However, there is still minor error with regard to the identification of th...
Modern process industries are large and complex. Their units are highly interconnected with each oth...
While the field of nanocatalysis has benefited from the application of conventional machine learnin...
Better understanding of process phenomena is dependent on the interpretation of models capturing the...
Causality analysis methods are initiated by multivariate statistics used in other fields. Due to its...
In modern industrial plants, process units are strongly cross-linked with eachother, and disturbance...
In modern industrial plants, process units are strongly cross-linked with each other, and disturbanc...
In large-scale chemical processes, disturbances can easily propagate through the process units and t...
Industrial systems often encounter abnormal conditions due to various faults or external disturbance...
Industrial systems are often subjected to abnormal conditions due to faulty operations or external d...
The thesis is concerned with the development of data-driven methods for fault diagnosis of plant-wid...
In continuous chemical processes, disturbances in the process conditions can propagate widely and ca...
Disturbances that spread plant-wide in a chemical process pose challenges to maintenance staff. Conn...
This brief reviews concepts of inter-relationship in modern industrial processes, biological and soc...
Finding the source of a disturbance in complex systems such as industrial chemical processing plants...
2014-08-06A typical industrial process or plant operates with hundreds of control loops and those pr...
Modern process industries are large and complex. Their units are highly interconnected with each oth...
While the field of nanocatalysis has benefited from the application of conventional machine learnin...
Better understanding of process phenomena is dependent on the interpretation of models capturing the...
Causality analysis methods are initiated by multivariate statistics used in other fields. Due to its...
In modern industrial plants, process units are strongly cross-linked with eachother, and disturbance...
In modern industrial plants, process units are strongly cross-linked with each other, and disturbanc...
In large-scale chemical processes, disturbances can easily propagate through the process units and t...
Industrial systems often encounter abnormal conditions due to various faults or external disturbance...
Industrial systems are often subjected to abnormal conditions due to faulty operations or external d...
The thesis is concerned with the development of data-driven methods for fault diagnosis of plant-wid...
In continuous chemical processes, disturbances in the process conditions can propagate widely and ca...
Disturbances that spread plant-wide in a chemical process pose challenges to maintenance staff. Conn...
This brief reviews concepts of inter-relationship in modern industrial processes, biological and soc...
Finding the source of a disturbance in complex systems such as industrial chemical processing plants...
2014-08-06A typical industrial process or plant operates with hundreds of control loops and those pr...
Modern process industries are large and complex. Their units are highly interconnected with each oth...
While the field of nanocatalysis has benefited from the application of conventional machine learnin...
Better understanding of process phenomena is dependent on the interpretation of models capturing the...