Process Control Strategies Research Articles

Antibody disulfide bond reduction and recovery during biopharmaceutical process development-A review.

Antibody disulfide bond reduction has been a challenging issue in monoclonal antibody manufacturing. It could lead to a decrease of product purity and failure to meet the targeted product profile and/or specifications. More importantly, disulfide bond reduction could also impact drug safety and efficacy. Scientists across the industry have been examining the root causes and developing mitigation strategies to address the challenge. In recent years, with the development of high titer mammalian cell culture processes to meet the rapidly growing demand for antibody biopharmaceuticals, disulfide bond reduction has been observed more frequently. Thus, it is necessary to continue evolving the disulfide reduction mitigation strategies and developing novel approaches to maintain high product quality. Additionally, in recent years as more complex molecules (such as bispecific and trispecific antibodies) emerge, the molecular heterogeneity due to incomplete formation of the interchain disulfide bonds becomes a more imperative challenging issue. Given the disulfide reduction challenges that biotech industry is facing, in this review, we provide a comprehensive scientific summary of the root cause analysis of disulfide reduction during process development of antibody therapeutics, mitigation strategies and its potential remediated recovery based on published papers. First, this paper intends to highlight different aspects of the root cause for disulfide reduction. Secondly, to provide a broader understanding of the disulfide bond reduction in downstream process, this paper discusses disulfide bond reduction impact on product stability, associated analytical methods for disulfide bond reduction detection and characterization, process control strategies as well as their manufacturing implementation. In addition, brief perspectives on the development of future mitigation strategies are also reviewed, including platform alignment, mitigation strategy application for the emerging new modalities such as bispecific and trispecific antibodies as well as using machine learning to identify molecule susceptibility of disulfide bond reduction. The data in this review are originated from the published papers.

On the Uncertainty Identification for Linear Dynamic Systems Using Stochastic Embedding Approach with Gaussian Mixture Models.

In control and monitoring of manufacturing processes, it is key to understand model uncertainty in order to achieve the required levels of consistency, quality, and economy, among others. In aerospace applications, models need to be very precise and able to describe the entire dynamics of an aircraft. In addition, the complexity of modern real systems has turned deterministic models impractical, since they cannot adequately represent the behavior of disturbances in sensors and actuators, and tool and machine wear, to name a few. Thus, it is necessary to deal with model uncertainties in the dynamics of the plant by incorporating a stochastic behavior. These uncertainties could also affect the effectiveness of fault diagnosis methodologies used to increment the safety and reliability in real-world systems. Determining suitable dynamic system models of real processes is essential to obtain effective process control strategies and accurate fault detection and diagnosis methodologies that deliver good performance. In this paper, a maximum likelihood estimation algorithm for the uncertainty modeling in linear dynamic systems is developed utilizing a stochastic embedding approach. In this approach, system uncertainties are accounted for as a stochastic error term in a transfer function. In this paper, we model the error-model probability density function as a finite Gaussian mixture model. For the estimation of the nominal model and the probability density function of the parameters of the error-model, we develop an iterative algorithm based on the Expectation-Maximization algorithm using the data from independent experiments. The benefits of our proposal are illustrated via numerical simulations.

Enhancement of biological nutrient removal process with advanced process control tools in full-scale wastewater treatment plant

One of the major challenges in existing WasteWater Treatment Plants (WWTPs) is to comply with the increasingly stringent nutrient discharge limits established by the competent authorities to enhance environmental protection, while keeping operation costs as low as possible. This paper describes the results obtained from upgrading a full-scale WWTP during seven years (2013–2020) applying five different Advanced Process Control (APC) strategies. Results show that implementation of APC and the development of ammonia-based aeration control, aeration/non-aeration cycles, improved internal/external recirculation and chemical dosage controls resulted in an improvement in nutrients removal rates (+25.48% and +9.25%, for nitrogen and phosphorus, respectively) and in a reduction (-21.79%) of the specific energy ratio. In addition, the promotion of an Enhanced Biological Phosphorous Removal (EBPR) process by APC resulted in an improvement in biological phosphorous removal (+43.90%), chemical savings (-20.00%) and nutrient recovery in the dewatered sludge. Molecular biology tools and laboratory batch tests confirmed the Polyphosphate Accumulating Organisms (PAOs) activity, specifically Tetrasphaera genera. Finally, an economic analysis was conducted, showing a rate of return for the incurred capital expenses with the implemented APC systems of about five years, being an affordable alternative to the upgrading existing WWTPs.

Recent advances in integrated process analytical techniques, modeling, and control strategies to enable continuous biomanufacturing of monoclonal antibodies

AbstractContinuous bioprocessing is significantly changing the biological drugs (or biologics) manufacturing landscape by potentially improving product quality, process stability, and overall profitability, as was similarly seen during the adoption of advanced manufacturing processes for small molecule drugs in the past decade. However, the implementation of continuous manufacturing for biological processes producing protein‐based drug molecules, such as monoclonal antibodies (mAbs), is facing several new hurdles. The barriers to continuous bioprocessing can be overcome through improved process understanding via better predictive capabilities enabled by hybrid modeling that can also lead to robust process control. This review article summarizes the recent advances and ongoing obstacles faced during the use of advanced process analytical technologies (PAT), process modeling, and control strategies to enable continuous manufacturing of mAbs. In addition, this review also discusses the process strategies and future directions of advanced continuous manufacturing approaches that have been adapted by other industries and that could be implemented for mAbs production soon. © 2021 Society of Chemical Industry (SCI).

Diagnostic Assessment of L2 Academic Writing Product, Process and Self-regulatory Strategy Use with a Comparative Dimension

ABSTRACT This research conducted diagnostic assessment of problems in first-year undergraduates’ English academic papers and tracked potential sources of the problems to the writing process and strategy use. Data collected include 339 term papers and interviews with 17 students. The samples were manually error tagged and marked against a detailed diagnostic checklist. The resultant textual features were then compared between two subgroups of Chinese students in the sample, namely, those graduating from local schools in Hong Kong (LS) and those coming from the mainland and sojourning in Hong Kong (MS). The analyses found both groups had the poorest performance in source integration and vocabulary use. LS used simpler words and made more grammatical errors, whereas MS attempted sophisticated vocabulary more successfully and used a wider variety of words and sentence structures. The difficulties they experienced, however, were rather similar, residing mainly at the researching, planning and formulating stages. Action control theory was introduced to interpret the self-regulatory strategies they adopted to cope with perceived difficulties during the writing process. Strategies to control goals, control resources, and control cognitive load were found to be the most typical. While these strategies could reduce their difficulties, only some seemed also to help with performance. A conceptual framework is proposed at the end to link writing products, process and self-regulatory control strategies as evidenced in the study. Four diagnoses are drawn with suggestions for practice and further research.

Process Modeling, Identification Methods, and Control Schemes for Nonlinear Physical Systems – A Comprehensive Review

AbstractA state‐of‐the‐art review on various identification schemes proposed for the Hammerstein, Wiener, and Volterra systems is presented with respect to the special problems arising in the identification of unknown nonlinear systems. Past and recent developments in the field of nonlinear system identification, parameter estimation, and nonlinear control schemes along with the nonlinearity issues are also deeply investigated. A comprehensive analysis on various parameter estimation approaches and nonlinear control laws are made adding credit to the noteworthy contributions, constructive arguments, and remarkable breakthroughs of researchers in various research fields. The application of most popular nonlinear control strategies for many nonlinear systems in the existing literature are presented spotlighting their merits and major shortcomings. The challenges faced in the nonlinear control field and their emergences to future directions are projected.

Soft sensor for real-time estimation of tablet potency in continuous direct compression manufacturing operation

One of the critical quality attributes of the solid oral dosage forms produced in continuous direct compression operations is the tablet potency. A novel soft sensor comprising of a combination of first principle-based and empirical models has been developed to enable real-time monitoring of blend and tablet potency, and concentrations of other excipients at various stream levels along the direct compression line. The soft sensor model has only three adjustable parameters, primarily associated with the equipment design and operation, so the model is product agnostic which is key to enable flexible manufacturing. The estimation accuracy of the soft sensor is demonstrated through a series of real time experiments which include steady state and dynamic transitions of potency during the runs, compared with offline analytically tested tablet cores. The results indicate that the proposed soft sensor can be utilized as a robust tool for real-time monitoring of potency, suggesting an extension of its utilization to higher levels of control. Two potential applications of the soft sensor are: 1. An element of a control strategy for product diversion; 2. A predictive model for advanced process control strategy to minimize the variability in tablet composition.

Simultaneous design for a complex heterogeneous wastewater separation and recovery process: process improvement, plantwide control and safety analysis

Recently, a new industrial relevant wastewater (water/Cyclohexane/sec-butyl alcohol) separation process with vapor recompression and thermal coupling was proposed as the conventional homogeneous extractive distillation. This highly integrated and interactive multivariable process presents great challenges to the dynamic controllability and process safety analysis. In this paper, based on the concept of “simultaneous design”, the newly proposed process is systematically investigated from the perspective of process improvement, plantwide control and safety analysis. Firstly, for energy conservation and CO2 emission reduction, the new complex process is further improved by applying the features of heterogeneous distillation. And a modified heterogeneous distillation process with heat pump is proposed, which can save reboiler duty about 16.8 % and save compressor electricity up to 67.7 %, while the reduction of CO2 emissions is 23.5 %. Secondly, for the efficient heterogeneous distillation process, an effective and robust plantwide control strategy is developed and tested under large throughput and feed composition disturbances. Last, with the dynamic simulation assisted HAZOP, a quantitative safety analysis is conducted, which can help experts to consider the nature, scale and response time of hazards and identify the potential propagation of deviation between different units, and then propose more specific or accurate safety recommendations correspondingly.

Control of surge tanks for continuous manufacturing of monoclonal antibodies.

Surge tanks are critical but often overlooked enablers of continuous bioprocessing. They provide multiple benefits including dampening of concentration gradients and allowing process resumption efforts in case of equipment failure or unexpected deviations, which can occur during a continuous campaign of weeks or months. They are also useful in enabling steady-state operation across a continuous train by facilitating mass balance between unit operations such as chromatography which have periodic loading and elution cycles. In this paper, we propose a design of a system of surge tanks for a monoclonal antibody (mAb) production process consisting of cell culture, clarification, capture chromatography, viral inactivation, polishing chromatography, and single-pass ultrafiltration and diafiltration. A Python controller has been developed for robust control of the continuous train. The controller has four layers, namely data acquisition, process scheduling, deviation handling, and real-time execution. A set of general guidelines for surge tank placement and sizing have been proposed together with process control strategies based on the design space of the individual unit operations, failure modes analysis of the different equipment, and expected variability in the process feed streams for both fed-batch and perfusion bioreactors. The control system has been successfully demonstrated for several continuous runs of up to 36 h in duration and is able to leverage surge tanks for robust control of the continuous train in the face of product variability as well as process errors while maintaining critical quality attributes. The proposed set of strategies for surge tank control are adaptable to most continuous processing setups for mAbs, and together form the first framework that can fully realize the benefits of surge tanks in continuous bioprocessing.

Design of Advanced Process Control Strategy for Industrial Pressure Process

In the process industry, pressure process control is important. Pressure process control systems have been refined and used in numerous implementations of in several process industries, pressure process plants are used, including chemical process industries, pharmaceuticals, wastewater treatment, and power plants. Pressure process management is essential in the process industry. Pressure process control systems have been refined and applied to a wide range of pressure process plant applications in a number of industries, including chemical manufacturing, pharmaceuticals, wastewater treatment, and power plants. The execution of such mechanism may result in remote and then the parameters can change over time.

Dynamic control of the pressure-swing distillation process for THF/ethanol/water separation with and without thermal integration

When evaluating the distillation process, it is necessary to consider its economic performance and its controllability. In this study, a strategy was developed to realize the stable control of pressure swing distillation without thermal integration in the face of 20% flow and composition disturbances. Through an exploration of the heat integration between different distillation columns, three partial and one full thermal integration processes were developed. The robust control of these processes was realized by adding reboiler heat duty and feed ratio (Q/F) control structures. Finally, the three processes were compared in terms of control and economy, and it was found that the controllability of the full thermal integration process was slightly inferior to that of the pressure swing distillation without thermal integration. However, the full thermal integration process consumed 29.48% less energy compared to process without thermal integration and resisted ±20% flow and composition disturbances. This research has a certain reference and guiding significance for the process design and control strategy design of triple column swing pressure distillation in industry.

Economic and environmental benefits by improved process control strategies in HCl removal from waste-to-energy flue gas

The control of HCl emission in waste-to-energy (WtE) facilities is a challenging flue gas treatment problem: the release of HCl from waste combustion is highly variable in time and the HCl emission standards are typically far lower in WtE than in any other industry. Traditional process control approaches in dry HCl removal processes are generally based on feeding a large excess of solid reactants to the system, to ensure robustness and a wide safety margin in the compliance to environmental regulations. This results in the production of a high amount of unreacted sorbents, strongly increasing the generation of solid wastes that need to be disposed. In the present study, an approach was developed to allow the implementation of improved control strategies for dry HCl abatement systems in operating full-scale facilities. Its objective is the reduction of the reactant feed and the waste production, while still providing an adequate safety margin for emission compliance. The approach was based on the reproduction of the behaviour of the real system in a virtual console that allows the extensive testing of alternative control strategies, limiting the need of demanding test-runs at the real plant. A test case on an Italian WtE facility demonstrated the capability of a control logic tuned in the virtual console to achieve a 13% reduction in the consumption of reactants and generation of process residues, with unchanged HCl removal efficiency. The results evidence the wide opportunities for optimisation of dry acid gas removal systems, in particular when multistage systems are implemented.

A Data-Driven Method for Online Monitoring Tube Wall Thinning Process in Dynamic Noisy Environment

Tube internal erosion, which corresponds to its wall thinning process, is one of the major safety concerns for tubes. Many sensing technologies have been developed to detect a tube wall thinning process. Among them, fiber Bragg grating (FBG) sensors are the most popular ones due to their precise measurement properties. Most of the current works focus on how to design different types of FBG sensors according to certain physical laws and only test their sensors in controlled laboratory conditions. However, in practice, an industrial system usually suffers from harsh and dynamic environmental conditions, and FBG signals are affected by many unpredictable factors. Consequently, the FBG signals have more fluctuations and are polluted by noises. Hence, the signals no longer directly follow the assumed physical laws and their proposed thinning detection mechanisms no longer work. Targeting at this, this article develops a data-driven model for FBG signal feature extraction and tube wall thickness monitoring using data analytic techniques. In particular, we develop a spatiotemporal model to describe dynamic FBG signals and extract features related to thickness. By taking physical law as guideline, we trace the relationship between the extracted features and the tube wall thickness, based on which we construct an online statistical monitoring scheme for tube wall thinning process. We use both laboratory test and field trial experiment to demonstrate the efficacy and efficiency of the proposed scheme. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —This article is motivated by the real industrial needs of inner erosion detection of tubes in harsh environment. Most of the current research works focus on designing various sensing apparatuses based on fiber Bragg grating (FBG) sensors for nondestructive erosion detection. These apparatuses prove to be able to collect signals reflecting tube wall thickness in static and controllable laboratory environment qualitatively. However, in reality, the industrial environment, which is impacted by many changing factors, is dynamic and uncontrollable. Consequently, the signals collected by these FBG apparatuses would have larger variations that mask the signals related to thickness. Furthermore, current methods have neither mentioned how to process their collected data to capture the unnoticeably slow but accumulative erosion information efficiently nor constructed online monitoring algorithms to detect the tube wall thinning process based on the collected signals quantitatively. Built upon their apparatuses but targeting at their unsolved challenges, we propose a novel data-driven approach for FBG signal analysis that can remove the environmental influence and extract features only related to tube wall thickness, and using the extracted features, we construct a statistical process control scheme to monitor tube wall thickness and detect erosion in real time efficiently.

Feed forward control of welding process parameters through on-line ultrasonic thickness measurement

Accurate control of welding parameters, such as arc power and wire speed, is critical for successful and appropriate weld joint penetration. The thickness of components being welded is a key parameter in defining optimum arc power for successful penetration, but is not always known beforehand or well controlled in manual and automated welding operations. This paper presents a novel feed-forward, sensor enabled, arc process control strategy based on ultrasonic thickness measurement. An ultrasonic wheel probe, deployed simultaneously alongside the welding torch, enables plate thickness measurement when coupled with a low-latency thickness measurement algorithm deployed on a real-time controller. An automated GTAW fusion control strategy, based on wheel probe measured plate thickness, provides direct input control of arc current, welding torch travel speed and filler wire feed rate. A parametric relationship between ultrasonically measured sample thickness and key arc welding parameters for welding S275 mild steel samples of thickness between 4.1 mm and 6.1 mm was established and verified. It is demonstrated that the system can measure and derive plate thickness while adapting arc power in real-time, with sufficiently low-latency, to allow consistent weld seam and uniform penetration on variable thickness steel samples, which under normal open-loop circumstances lead to sample burn-through and excessive penetration.

Evaluation of Process Control Schemes for Sour Water Strippers in Petroleum Refining

For the sour water strippers in petroleum refinery plants, three prediction models were developed first, including the estimators of sour water feed concentrations using convenient online measurements, the minimum reboiler duty and the corresponding internal temperature at a specific location (Tstage,29). Feedforward control schemes were developed based on these prediction models. Four categories of control schemes, including feedforward, feedback, feedback with external reset, and feedforward-feedback, were proposed and evaluated by the rigorous dynamic simulation model of the sour water stripper for their dynamic responses to the sour water feed stream disturbances. The comparison of control performance, in terms of the settling time, integrated absolute error (IAE) of the NH3 concentration of the stripped sour water and IAE of the specific reboiler duty, reveals that FFT (feedforward control of Tstage,29) and FBA-DT3 (feedback control with 3 min concentration measurement delay) are the best control schemes. The second-best control scheme is FBAT (cascade feedback control of concentration with temperature).

Potential applications of halophilic microorganisms for biological treatment of industrial process brines contaminated with aromatics.

Saline wastewater contaminated with aromatic compounds can be frequently found in various industrial sectors. Those compounds need to be degraded before reuse of wastewater in other process steps or release to the environment. Halophiles have been reported to efficiently degrade aromatics, but their application to treat industrial wastewater is rare. Halophilic processes for industrial wastewater treatment need to satisfy certain requirements: a continuous process mode, low operational expenditures, suitable reactor systems and a monitoring and control strategy. The aim of this review is to provide an overview of halophilic microorganisms, principles of aromatic biodegradation, and sources of saline wastewater containing aromatics and other contaminants. Finally, process examples for halophilic wastewater treatment and potential process monitoring strategies are discussed. To further illustrate the significant potential of halophiles for saline wastewater treatment and to facilitate development of ready-to-implement processes, future research should focus on scale-up and innovative process monitoring and control strategies.

Towards Autonomous Operation by Advanced Process Control—Process Analytical Technology for Continuous Biologics Antibody Manufacturing

Continuous manufacturing opens up new operation windows with improved product quality in contrast to documented lot deviations in batch or fed-batch operations. A more sophisticated process control strategy is needed to adjust operation parameters and keep product quality constant during long-term operations. In the present study, the applicability of a combination of spectroscopic methods was evaluated to enable Advanced Process Control (APC) in continuous manufacturing by Process Analytical Technology (PAT). In upstream processing (USP) and aqueous two-phase extraction (ATPE), Raman-, Fourier-transformed infrared (FTIR), fluorescence- and ultraviolet/visible- (UV/Vis) spectroscopy have been successfully applied for titer and purity prediction. Raman spectroscopy was the most versatile and robust method in USP, ATPE, and precipitation and is therefore recommended as primary PAT. In later process stages, the combination of UV/Vis and fluorescence spectroscopy was able to overcome difficulties in titer and purity prediction induced by overlapping side component spectra. Based on the developed spectroscopic predictions, dynamic control of unit operations was demonstrated in sophisticated simulation studies. A PAT development workflow for holistic process development was proposed.

Sequential Switching Shunt Regulator Parallel Power Processing Control for High Capacitance Solar Arrays

This paper presents a new control strategy for reducing the switching losses produced by the use of high parasitic capacitance solar arrays in the sequential switching shunt regulator. Instead of dividing the solar array into equal sections, the proposed strategy is based on two different sections types, low-capacitance and high-capacitance ones. In order to reduce the switching losses and to maintain the original closed-loop response, a novel parallel power processing control strategy is implemented. With this new technique the low-capacitance sections are the only ones that switch at high frequency to regulate the bus while the high-capacitance sections are only connected or disconnected under high load power changes. In addition, the control closed loop delay associated to the time needed to charge the parasitic capacitance has been modelled and a controller modification is proposed to reduce AC performance degradation.

Process monitoring and control strategies in extrusion-based bioprinting to fabricate spatially graded structures

Extrusion-based bioprinting is the most common printing technology used in regenerative medicine. Despite recent technological advances, a pressing challenge for extrusion printing is low spatial resolution, which limits the functionality of printed constructs. One of the reasons for the low spatial resolution is a lack of process monitoring and control strategies to monitor fabrication and correct for print errors. Few research efforts implement process control and investigate the relationship between extrusion process parameters and printing fidelity. The lack of understanding between process parameters and print results ultimately limits the complexity of the possible structures. For example, fabrication of structures whose topologies vary spatially within the part is not possible without advanced process control. Here we enable fabrication of advanced spatially graded structures by implementing process monitoring and control strategies. We develop material models to better understand the relationship between process parameters and printing outcomes. We also present an experimental procedure to generate a process map that provides insight into the regions of the processing space that produce the desired extrusion features (e.g., width of the filament). After generation of a process map and material models, we implement a process monitoring and control strategy that measures the feature error and intelligently updates the process control inputs to reduce defects and improve spatial fidelity, which will lead to better functionality of the final construct.

A New Control Strategy for the Aluminum Reduction Process Using Economic Model Predictive Control

Abstract In the Hall-Heroult process, the evolving design and operating conditions require an advance on the development of new process control strategies. Especially, with the technology of individual anode current measurement now available, it becomes possible to monitor and control the localized conditions in an aluminum reduction cell. In this paper, a new cell control strategy is developed based on the Economic Model Predictive Control method, aiming to improve the current efficiency of the aluminum reduction process and hence maximize its economic benefits through advanced control algorithms. In addition, a more balanced cell condition is achieved through reduced spatial and temporal variations of process variables, such as alumina concentration, anode cathode distance, anode current. The simulation results demonstrate the superiority of the new method by comparing its control performance with that of the traditional method.