Using warping information for batch process monitoring and fault classification

This paper discusses how to use the warping information obtained after batch synchronization for process monitoring and fault classification. The warping information can be used for i) building unsupervised control charts or ii) fault classification when a rich faulty batches database is available. Data from realistic simulations of a fermentation process of the Saccharomyces cerevisiae cultivation are used to illustrate the proposal.This research work was supported by the Spanish government (Ministry of Science and Innovation, MICINN) under project DPI2011-28112-C04-02. We gratefully acknowledge Associate Professor Jose Camacho for providing the simulation scheme of the fermentation process of Saccharomyces cerevisiae cultivation.Gonzalez-Martinez, J.; Westerhuis, J.; Ferrer Riquelme, AJ. (2013). Using warping information for batch process monitoring and fault classification. Chemometrics and Intelligent Laboratory Systems. 127:210-217. https://doi.org/10.1016/j.chemolab.2013.07.003S21021712

Real-time synchronization of batch trajectories for on-line multivariate statistical process control using Dynamic Time Warping

This paper addresses the real-time monitoring of batch processes with multiple different local time trajectories of variables measured during the process run. For Unfold Principal Component Analysis (U-PCA)—or Unfold Partial Least Squares (U-PLS)-based on-line monitoring of batch processes, batch runs need to be synchronized, not only to have the same time length, but also such that key events happen at the same time. An adaptation from Kassidas et al.'s approach [1] will be introduced to achieve the on-line synchronization of batch trajectories using the Dynamic Time Warping (DTW) algorithm. In the proposed adaptation, a new boundaries definition is presented for accurate on-line synchronization of an ongoing batch, together with a way to adapt mapping boundaries to batch length. A relaxed greedy strategy is introduced to avoid assessing the optimal path each time a new sample is available. The key advantages of the proposed strategy are its computational speed and accuracy for the batch process context. Data from realistic simulations of a fermentation process of the Saccharomyces cerevisae cultivation are used to illustrate the performance of the proposed strategy.This research work was supported by the Spanish government under the project (DPI2008-06880-C03-03). We also gratefully acknowledge Jose Camacho PhD. for providing simulated data from a fermentation process of Saccharomyces cerevisae. The authors would also like to acknowledge the valuable suggestions made by Prof. Paul Taylor.González Martínez, JM.; Ferrer Riquelme, AJ.; Westerhuis, JA. (2011). Real-time synchronization of batch trajectories for on-line multivariate statistical process control using Dynamic Time Warping. Chemometrics and Intelligent Laboratory Systems. 105(2):195-206. https://doi.org/10.1016/j.chemolab.2011.01.003S195206105

Trajectory set similarity measure: An EMD-based approach

To address the trajectory sparsity issue concerning Origin-Destination (OD) pairs, in general, most existing studies strive to reconstruct trajectories by concatenating the sub-trajectories along the specific paths and filling up the sparsity with conceptual trajectories. However, none of them gives the robustness validation for their reconstructed trajectories. By intuition, the reconstructed trajectories are more qualified if they are more similar to the exact ones traversing directly from the origin to the destination, which indicates the effectiveness of the corresponding trajectory augmentation algorithms. Nevertheless, to our knowledge, no existing work has studied the similarity of trajectory sets. Motivated by this, we propose a novel similarity measure to evaluate the similarity between two set of trajectories, borrowing the idea of the Earth Mover’s Distance. Empirical studies on a large real trajectory dataset show that our proposed similarity measure is effective and robust

A boosted segmentation method for surgical workflow analysis

Abstract. As demands on hospital efficiency increase, there is a stronger need for automatic analysis, recovery, and modification of surgical workflows. Even though most of the previous work has dealt with higher level and hospital-wide workflow including issues like document management, workflow is also an important issue within the surgery room. Its study has a high potential, e.g., for building context-sensitive operating rooms, evaluating and training surgical staff, optimizing surgeries and generating automatic reports. In this paper we propose an approach to segment the surgical workflow into phases based on temporal synchronization of multidimensional state vectors. Our method is evaluated on the example of laparoscopic cholecystectomy with state vectors representing tool usage during the surgeries. The discriminative power of each instrument in regard to each phase is estimated using AdaBoost. A boosted version of the Dynamic Time Warping (DTW) algorithm is used to create a surgical referenc

Maintenance of Machine Vision Systems for Product Quality Assessment. Part II. Addressing Camera Replacement

In the process industry, machine vision systems have been shown to be beneficial for the characterization of several products whose quality can be related to some visual features such as color, color uniformity, surface roughness, and presence of surface defects. With respect to the visual inspection traditionally carried out by a panel of trained experts, artificial vision systems can return a quick, accurate, and objective indication of the quality of the manufactured end product. However, reproducibility of the image analysis results is ensured only as long as the conditions, under which the images used for the calibration of the quality assessment model were collected, do not change during normal operation of the machine vision system. In this paper (Part II of this series following Part I, Ind. Eng. Chem. Res., 2013, 52, 12309−12318), we discuss a technology transfer problem for a machine vision system, namely the problem arising when replacing the camera, on which the system is centered, with a different one. In order to compensate for the differences between cameras, two strategies are tested. The first one, which is borrowed from the machine vision literature, aims at matching the color spaces of the two cameras through a linear or a nonlinear transformation. The second one, which was proposed in Part I to manage light alterations, aims at matching the color spaces of the cameras by synchronizing their projection onto a principal component analysis model. The superior performance of the latter strategy is demonstrated through two case studies involving images of pharmaceutical tablets and calibration standards of different colors, as well as images of film-coated tablets with different percentages of applied coating material

A high-throughput processing service for retention time alignment of complex proteomics and metabolomics LC-MS data

Warp2D is a novel time alignment approach, which uses the overlapping peak volume of the reference and sample peak lists to correct misleading peak shifts. Here, we present an easyto- use web interface for high-throughput Warp2D batch processing time alignment service using the Dutch Life Science Grid, reducing processing time from days to hours. This service provides the warping function, the sample chromatogram peak list with adjusted retention times and normalized quality scores based on the sum of overlapping peak volume of all peaks. Heat maps before and after time alignment are created from the arithmetic mean of the sum of overlapping peak area rearranged with hierarchical clustering, allowing the quality control of the time alignment procedure. Taverna workflow and command line tool are provided for remote processing of local user data