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

Metabolic flux understanding of Pichia pastoris grown on heterogenous culture media

[EN] Within the emergent field of Systems Biology, mathematical models obtained from physical chemical laws (the so-called first principles-based models) of microbial systems are employed to discern the principles that govern cellular behaviour and achieve a predictive understanding of cellular functions. The reliance on this biochemical knowledge has the drawback that some of the assumptions (specific kinetics of the reaction system, unknown dynamics and values of the model parameters) may not be valid for all the metabolic possible states of the network. In this uncertainty context, the combined use of fundamental knowledge and data measured in the fermentation that describe the behaviour of the microorganism in the manufacturing process is paramount to overcome this problem. In this paper, a grey modelling approach is presented combining data-driven and first principles information at different scales, developed for Pichia pastoris cultures grown on different carbon sources. This approach will allow us to relate patterns of recombinant protein production to intracellular metabolic states and correlate intra and extracellular reactions in order to understand how the internal state of the cells determines the observed behaviour in P. pastoris cultivations.Research in this study was partially supported by the Spanish Ministry of Science and Innovation and FEDER funds from the European Union through grants DPI2011-28112-C04-01 and DPI2011-28112-C04-02. The authors are also grateful to Biopolis SL for supporting this research. We also gratefully acknowledge Associate Professor Jose Camacho for providing the Exploratory Data Analysis Toolbox.González Martínez, JM.; Folch-Fortuny, A.; Llaneras Estrada, F.; Tortajada Serra, M.; Picó Marco, JA.; Ferrer, A. (2014). Metabolic flux understanding of Pichia pastoris grown on heterogenous culture media. Chemometrics and Intelligent Laboratory Systems. 134:89-99. https://doi.org/10.1016/j.chemolab.2014.02.003S899913

MCR-ALS on metabolic networks: Obtaining more meaningful pathways

[EN] With the aim of understanding the flux distributions across a metabolic network, i.e. within living cells, Principal Component Analysis (PCA) has been proposed to obtain a set of orthogonal components (pathways) capturing most of the variance in the flux data. The problems with this method are (i) that no additional information can be included in the model, and (ii) that orthogonality imposes a hard constraint, not always reasonably. To overcome these drawbacks, here we propose to use a more flexible approach such as Multivariate Curve Resolution-Alternating Least Squares (MCR-ALS) to obtain this set of biological pathways through the network. By using this method, different constraints can be included in the model, and the same source of variability can be present in different pathways, which is reasonable from a biological standpoint. This work follows a methodology developed for Pichia pastoris cultures grown on different carbon sources, lately presented in González-Martínez et al. (2014). In this paper a different grey modelling approach, which aims to incorporate a priori knowledge through constraints on the modelling algorithms, is applied to the same case of study. The results of both models are compared to show their strengths and weaknesses.Research in this study was partially supported by the Spanish Ministry of Science and Innovation and FEDER funds from the European Union through grants DPI2011-28112-C04-01 and DPI2011-28112-C04-02. The authors are also grateful to Biopolis SL for supporting this research.Folch-Fortuny, A.; Tortajada Serra, M.; Prats-Montalbán, JM.; Llaneras Estrada, F.; Picó Marco, JA.; Ferrer Riquelme, AJ. (2015). MCR-ALS on metabolic networks: Obtaining more meaningful pathways. Chemometrics and Intelligent Laboratory Systems. 142:293-303. https://doi.org/10.1016/j.chemolab.2014.10.004S29330314

Atomic XAFS as a probe of electron transfer within organometallic complexes: data analysis and theoretical calculations

The atomic XAFS (AXAFS) contributions in the Pt L2,3 X-ray absorption fine structure spectra (XAFS) of [PtCl(NCN)-Z] pincer complexes are shown to be a sensitive probe of changes in the electron density on the Pt atom induced by changes in a para-substituent on the neighboring benzene ring. Such electron density information is similar yet complementary to NMR data. These complexes provide a unique system for examining inductive effects on the AXAFS data, since the geometry around the Pt atom remains unchanged. An initial brief report on this work has been given previously. In this paper a more complete description of the AXAFS isolation technique and theoretical interpretation is given. The isolation of the AXAFS contributions from the XAFS spectrum is extensively described. The dependence of the AXAFS shape and intensity on the Pt atom electron density are shown and discussed in detail

AXAFS as a probe of charge redistribution within organometallic complexes

Atomic XAFS on [PtCl(NCN)-Z] pincer complexes shows it to be a sensitive probe for the determination of the electron density on the metal atom, similar yet complementary to NMR