scholarly journals On-Line Monitoring of Batch Process with Multiway PCA/ICA

Author(s):  
Xiang Gao
Keyword(s):  
2003 ◽  
Vol 83 (6) ◽  
pp. 668-680 ◽  
Author(s):  
Christopher Cannizzaro ◽  
Martin Rhiel ◽  
Ian Marison ◽  
Urs von Stockar

The Analyst ◽  
2002 ◽  
Vol 128 (1) ◽  
pp. 98-102 ◽  
Author(s):  
Eric N. M. van Sprang ◽  
Henk-Jan Ramaker ◽  
Hans F. M. Boelens ◽  
Johan A. Westerhuis ◽  
David Whiteman ◽  
...  

Processes ◽  
2019 ◽  
Vol 7 (2) ◽  
pp. 103 ◽  
Author(s):  
Sujit Suresh Jogwar ◽  
Shrikant Mete ◽  
Channamallikarjun Mathpati

In this paper, a novel pattern-based method is developed for the generation of optimal schedules for energy-integrated batch process systems. The proposed methodology is based on the analysis of available schedules for the identification of repetitive patterns. It is shown that optimal schedules of energy-integrated batch processes are composed of several repeating sections (or building blocks), and their sizes and relative positions are dependent on the scheduling horizon and constraints. Based on such a decomposition, the proposed pattern-based algorithm generates an optimal schedule by computing the number and sequence of these blocks. The framework is then integrated with rigorous optimization-based approach wherein it is shown that the learning from the pattern-based solution significantly improves the performance of rigorous optimization. The main advantage of the pattern-based method is the significant reduction in computational time required to solve large scheduling problems, thus enabling the possibility of on-line rescheduling. Three literature examples were considered to demonstrate the presence of repeating patterns in optimal schedules of energy-integrated batch systems. The effectiveness of the proposed methodology was illustrated using an integrated reactor-separator system.


Author(s):  
PHILIPPE CASTAGLIOLA ◽  
ARIANE FERREIRA PORTO ROSA

In some industrial situations, the classical assumption used in the batch process monitoring that all batches have equal durations and are synchronized does not hold. A batch process is carried out in sequential phases and a significant variability generally occurs in the duration of the phases such that events signifying the beginning or the end of a phase are generally misaligned in time within the various batches. The consequence is that the variable trajectories, in the different runs of the same batch process, are unsynchronized. In this case, data analysis from process for performing the multivariate statistical process control can be difficult. In this paper, we propose several innovative methods for the off-line and on-line monitoring of batch processes with varying durations, all based on the Hausdorff distance. These methods have been successfully tested on a simulated example and on an industrial case example. The conclusion is that these methods are able to efficiently discriminate between nominal and non-nominal batches.


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