Processes2015, 3(2), 384-405; doi:10.3390/pr3020384 - published 7 May 2015 Show/Hide Abstract
Abstract: The purpose of this study was to introduce dielectric spectroscopy and biocalorimetry as monitoring methods to follow immobilised Chinese Hamster Ovary (CHO) cell culture development. The theory behind both monitoring techniques is explained and perfusion cultures are performed in a Reaction Calorimeter (eRC1 from Mettler Toledo) as an application example. The findings of this work show that dielectric spectroscopy gives highly reliable information upon the viable cell density throughout the entire culture. On the other hand, the RC1 could only provide accurate data from day 5, when the cell density exceeded 4 × 106vcells∙mL−1 (viable cell per mL) working volume (WV). The method validation showed the limit of detection (LOD) for 1.4 L cultures to be 8.86 × 106vcells∙mL−1, a viable cell density commonly achieved in fed-batch and the early stages of a perfusion culture. This work suggests that biocalorimetry should be possible to implement at industrial scale to monitor CHO cell cultures.
Processes2015, 3(2), 357-383; doi:10.3390/pr3020357 - published 6 May 2015 Show/Hide Abstract
Abstract: Performing experiments for system identification is often a time-consuming task which may also interfere with the process operation. With memory prices going down and the possibility of cloud storage, years of data is more and more commonly stored (without compression) in a history database. In such stored data, there may already be intervals informative enough for system identification. Therefore, the goal of this project was to find an algorithm that searches and marks intervals suitable for process identification (rather than completely autonomous system identification). For each loop, four stored variables are required: setpoint, manipulated variable, measured process output and mode of the controller. The essential features of the method are the search for excitation of the input and output, followed by the estimation of a Laguerre model combined with a hypothesis test to check that there is a causal relationship between process input and output. The use of Laguerre models is crucial to handle processes with deadtime without explicit delay estimation. The method was tested on three years of data from about 200 control loops. It was able to find all intervals in which known identification experiments were performed as well as many other useful intervals in closed/open loop operation.
Processes2015, 3(2), 339-356; doi:10.3390/pr3020339 - published 6 May 2015 Show/Hide Abstract
Abstract: Continuous pharmaceutical manufacturing together with PAT (Process Analytical Technology) provides a suitable platform for automatic control of the end product quality as desired by QbD (quality by design)-based efficient manufacturing. The precise control of the quality of the pharmaceutical product requires corrective actions in the process/raw material variability before product quality can be influenced. In this manuscript, a combined feed-forward/feed-back control system has been developed for a direct compaction continuous tablet manufacturing process. The feed-forward controller takes into account the effect of process disturbances proactively while the feed-back control system ensures the end product quality consistently. The coupled feed-forward/feed-back control system ensures the minimum variability in the final product quality irrespective of process and raw material variations. The performance of the combined control strategy has been evaluated through process simulation and is found to be more effective in comparison with a feed-back only control strategy and, therefore, demonstrates potential to further improve pharmaceutical tablet manufacturing operations.
Processes2015, 3(2), 309-338; doi:10.3390/pr3020309 - published 5 May 2015 Show/Hide Abstract
Abstract: Atoms and molecules assemble into materials, with the material structure determining the properties and ultimate function. Human-made materials and systems have achieved great complexity, such as the integrated circuit and the modern airplane. However, they still do not rival the adaptivity and robustness of biological systems. Understanding the reaction and assembly of molecules on the early Earth is a scientific grand challenge, and also can elucidate the design principles underlying biological materials and systems. This research requires understanding of chemical reactions, thermodynamics, fluid mechanics, heat and mass transfer, optimization, and control. Thus, the discipline of chemical engineering can play a central role in advancing the field. In this paper, an overview of research in the origins field is given, with particular emphasis on the origin of biopolymers and the role of chemical engineering phenomena. A case study is presented to highlight the importance of the environment and its coupling to the chemistry.
Processes2015, 3(2), 286-308; doi:10.3390/pr3020286 - published 4 May 2015 Show/Hide Abstract
Abstract: The fate choice of human embryonic stem cells (hESCs) is controlled by complex signaling milieu synthesized by diverse chemical factors in the growth media. Prevalence of crosstalks and interactions between parallel pathways renders any analysis probing the process of fate transition of hESCs elusive. This work presents an important step in the evaluation of network level interactions between signaling molecules controlling endoderm lineage specification from hESCs using a statistical network identification algorithm. Network analysis was performed on detailed signaling dynamics of key molecules from TGF-β/SMAD, PI3K/AKT and MAPK/ERK pathways under two common endoderm induction conditions. The results show the existence of significant crosstalk interactions during endoderm signaling and they identify differences in network connectivity between the induction conditions in the early and late phases of signaling dynamics. Predicted networks elucidate the significant effect of modulation of AKT mediated crosstalk leading to the success of PI3K inhibition in inducing efficient endoderm from hESCs in combination with TGF-β/SMAD signaling.
Processes2015, 3(2), 257-285; doi:10.3390/pr3020257 - published 22 April 2015 Show/Hide Abstract
Abstract: This paper introduces a novel steady-state identification (SSI) method based on the auto-regressive model with exogenous inputs (ARX). This method allows the SSI with reduced tuning by analyzing the identifiability properties of the system. In particular, the singularity of the model matrices is used as an index for steady-state determination. In this contribution, the novel SSI method is compared to other available techniques, namely the F-like test, wavelet transform and a polynomial-based approach. These methods are implemented for SSI of three different case studies. In the first case, a simulated dataset is used for calibrating the output-based SSI methods. The second case corresponds to a literature nonlinear continuous stirred-tank reactor (CSTR) example running at different steady states in which the ARX-based approach is tuned with the available input-output data. Finally, an industrial case with real data of a depropanizer column from PETROBRAS S.A. considering different pieces of equipment is analyzed. The results for a reflux drum case indicate that the wavelet and the F-like test can satisfactorily detect the steady-state periods after careful tuning and when respecting their hypothesis, i.e., smooth data for the wavelet method and the presence of variance in the data for the F-like test. Through a heat exchanger case with different measurement frequencies, we demonstrate the advantages of using the ARX-based method over the other techniques, which include the aspect of online implementation.