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Conveyor belts serve as the primary mode of ore transportation in mineral processing plants. Feeders, comprised of shorter conveyors, regulate the material flow from silos to longer conveyor belts by adjusting their velocity. This velocity manipulation is facilitated by automatic controllers that gauge the material weight on the conveyor using scales. However, due to positioning constraints of these scales, a notable delay ensues between measurement and the adjustment of the feeder speed. This dead time poses a significant challenge in control design, aiming to prevent oscillations in material levels on the conveyor belt. This paper contributes in two key areas: firstly, through a simulation-based comparison of various control techniques addressing this issue across diverse scenarios; secondly, by implementing the Smith predictor solution in an operational plant and contrasting its performance with that of a single PID controller. Evaluation spans both the transient flow rate during step change setpoints and a month-long assessment. The experimental results reveal a notable increase in production by 355 t/h and a substantial reduction in flow rate oscillations on the conveyor belt, evidenced by a 55% decrease in the standard deviation. [ABSTRACT FROM AUTHOR]

To evaluate the suitability of an analytical instrument, essential figures of merit such as the limit of detection (LOD) and the limit of quantification (LOQ) can be employed. However, as the definitions k nown in the literature are mostly applicable to one signal per sample, estimating the LOD for substances with instruments yielding multidimensional results like electronic noses (eNoses) is still challenging. In this paper, we will compare and present different approaches to estimate the LOD for eNoses by employing commonly used multivariate data analysis and regression techniques, including principal component analysis (PCA), principal component regression (PCR), as well as partial least squares regression (PLSR). These methods could subsequently be used to assess the suitability of eNoses to help control and steer processes where volatiles are key process parameters. As a use case, we determined the LODs for key compounds involved in beer maturation, namely acetaldehyde, diacetyl, dimethyl sulfide, ethyl acetate, isobutanol, and 2-phenylethanol, and discussed the suitability of our eNose for that dertermination process. The results of the methods performed demonstrated differences of up to a factor of eight. For diacetyl, the LOD and the LOQ were sufficiently low to suggest potential for monitoring via eNose. [ABSTRACT FROM AUTHOR]

The continuous manufacturing of biologics offers significant advantages in terms of reducing manufacturing costs and increasing capacity, but it is not yet widely implemented by the industry due to major challenges in the automation, scheduling, process monitoring, continued process verification, and real-time control of multiple interconnected processing steps, which must be tightly controlled to produce a safe and efficacious product. The process produces a large amount of data from different sensors, analytical instruments, and offline analyses, requiring organization, storage, and analyses for process monitoring and control without compromising accuracy. We present a case study of a cyber–physical production system (CPPS) for the continuous manufacturing of mAbs that provides an automation infrastructure for data collection and storage in a data historian, along with data management tools that enable real-time analysis of the ongoing process using multivariate algorithms. The CPPS also facilitates process control and provides support in handling deviations at the process level by allowing the continuous train to re-adjust itself via a series of interconnected surge tanks and by recommending corrective actions to the operator. Successful steady-state operation is demonstrated for 55 h with end-to-end process automation and data collection via a range of in-line and at-line sensors. Following this, a series of deviations in the downstream unit operations, including affinity capture chromatography, cation exchange chromatography, and ultrafiltration, are monitored and tracked using multivariate approaches and in-process controls. The system is in line with Industry 4.0 and smart manufacturing concepts and is the first end-to-end CPPS for the continuous manufacturing of mAbs. [ABSTRACT FROM AUTHOR]

Process control is widely discussed in the manufacturing process, especially in semiconductor manufacturing. Due to unavoidable disturbances in manufacturing, different process controllers are proposed to realize variation reduction. Since Reinforcement Learning (RL) has shown great advantages in learning actions from interactions with a dynamic system, we introduce RL methods for process control and propose a new controller called RL-based controller. Considering the fact that most existing run-to-run (R2R) controllers mainly rely on a linear model assumption for the process input–output relationship, we first discuss theoretical properties of RL-based controllers based on the linear model assumption. Then the performance of RL-based controllers and traditional R2R controllers (e.g., Exponentially Weighted Moving Average (EWMA), double EWMA, adaptive EWMA, and general harmonic rule controllers) are compared for linear processes. Furthermore, we find that the RL-based controllers have potential advantages to deal with other complicated nonlinear processes. The intensive numerical studies validate the advantages of the proposed RL-based controllers. [ABSTRACT FROM AUTHOR]

Single‐layer chemical vapor deposition (CVD) graphene films are commonly transferred from their native growth substrates during characterization. However, the transfer process influences their intrinsic material properties and growth substrate‐related material information is lost. Herein, an in situ method is presented to suspend CVD graphene films directly on their growth substrate. The approach makes the sample compatible for characterization across the widely used optical and electron microscopy techniques such as Raman spectroscopy and transmission electron microscopy. In addition, a quality matrix framework "ISCOPEM2D V1.0" is provided to support the quantification, comparison, and validation of various material properties of single‐layer graphene. The approach provides a holistic overview of various properties and facilitates quality control and reproducibility of single‐layer graphene‐based application development. Similar approaches can be useful to develop quality matrix‐based for other 2D materials. [ABSTRACT FROM AUTHOR]

Spontaneously fermented foods are consumed and appreciated for thousands of years although they are usually produced with fluctuated productivity and quality, potentially threatening both food safety and food security. To guarantee consistent fermentation productivity and quality, it is essential to control the complex microbiota, the most crucial factor in food fermentations. The prerequisite for the control is to comprehensively understand the structure and function of the microbiota. How to quantify the actual microbiota is of paramount importance. Among various microbial quantitative methods evolved, quantitative microbiome profiling, namely to quantify all microbial taxa by absolute abundance, is the best method to understand the complex microbiota, although it is still at its pioneering stage for food fermentations. Here, we provide an overview of microbial quantitative methods, including the development from conventional methods to the advanced quantitative microbiome profiling, and the application examples of these methods. Moreover, we address potential challenges and perspectives of quantitative microbiome profiling methods, as well as future research needs for the ultimate goal of rational and optimal control of microbiota in spontaneous food fermentations. Our review can serve as reference for the traditional food fermentation sector for stable fermentation productivity, quality and safety. [ABSTRACT FROM AUTHOR]

The constantly increasing challenges of production technology for the economic and resource-saving production of metallic workpieces require, among other things, the optimisation of existing processes. Forming technology, which is confronted with new challenges regarding the quality of the workpieces, must also organise the individual processes more efficiently and at the same time more reliably in order to be able to guarantee good workpiece quality and at the same time to be able to produce economically. One way to meet these challenges is to carry out the forming processes in closed-loop control systems using softsensors. Despite the many potential applications of softsensors in the field of forming technology, there is still no definition of the term softsensor. This publication therefore proposes a definition of the softsensor based on the definition of a sensor and the distinction from the observer, which on the one hand is intended to stimulate scientific discourse and on the other hand is also intended to form the basis for further scientific work. Based on this definition, a wide variety of highly topical application examples of various softsensors in the field of forming technology are given. [ABSTRACT FROM AUTHOR]

Directed energy deposition (DED), a form of additive manufacturing (AM), is gaining traction for its ability to produce complex metal parts with precise geometries. However, defects like distortion, residual stresses, and porosity can compromise part quality, leading to rejection. This research addresses this challenge by emphasizing the importance of monitoring process parameters (overlayer distance, powder feed rate, and laser path/power/spot size) to achieve desired mechanical properties. To improve DED quality and reliability, a numerical approach is presented and compared with an experimental work. The parametric finite element model and predictive methods are used to quantify and control material behavior, focusing on minimizing residual stresses and distortions. Numerical simulations using the Abaqus software 2022 are validated against experimental results to predict distortion and residual stresses. A coupled thermomechanical analysis model is employed to understand the impact of thermal distribution on the mechanical responses of the parts. Finally, new strategies based on laser scan trajectory and power are proposed to reduce residual stresses and distortions, ultimately enhancing the quality and reliability of DED-manufactured parts. [ABSTRACT FROM AUTHOR]

Copyright of BHM Berg- und Hüttenmännische Monatshefte is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

For chemical processes, dynamic optimization is employed for process transition. On the basis of the multilayer control structure, the employment of dynamic optimization is affected by the regulatory control system. To avoid the adjustment of the regulatory control system, set-point optimization is proposed. For comparison, two types of optimization models, namely direct optimization and set-point optimization, are formulated. The superiority of set-point optimization is rigorously proven. By simulating the commercial process of a throughput-fluctuating ethylene column, the integrated absolute error and maximum deviation of product quality are reduced by more than 150% with set-point optimization. The results indicate that the approach to process transition via regulatory controllers not only avoids the insecurity caused by the switching of set-point controllers but also improves the optimization performance. In conclusion, the proposed optimization structure, namely set-point optimization, is operable and stable for commercial chemical process transitions. [ABSTRACT FROM AUTHOR]

Environmental pollutants (EP) and carbon emissions (CE) generated by fossil fuel combustion have the same root and origin, but the synergistic effect of EP and CE in specific management is not clear. This study develops a systematic method to evaluate the synergistic effect of EP and CE, which combines the EP-CE synergy performance under different scenarios and the process decomposition of “source prevention-process control-terminal output” based on the construction of the EP-CE synergy performance assessment, and forms a complete chain of EP-CE synergy performance assessment under the system view of ecological civilization. Furthermore, the synergy of EP and CE in 79 prefecture-level cities of the Yellow River Basin (YRB) is evaluated as an example. Results show that: (1) The overall EP-CE synergy performance in the YRB is in the transition to high-quality development, and the EP-CE synergy performance of each reaches show the evolution of “the lower the performance, the faster the progress”; (2) The EP-CE synergy performance under the scenario of collaborative pollution control and carbon reduction is significantly higher than those of separate pollution control, separate carbon reduction, or no consideration of environmental constraints, and there are noticeable spatial differences, with the upper reaches having the highest EP-CE synergy performance; (3) The EP-CE synergy performances among the different process decomposition in the YRB needs to be strengthened. The process control had the highest overall performance level, but the inclusion of environmental factors could significantly decrease the performance level, while the opposite is exact for the terminal output. The study provides a multi-scenario and process decomposition approach to assess the synergistic effects of EP and CE, and the scenario simulation assessment, process decomposition analysis, and synergistic control recommendations can be used as references for other regions or countries suffering from both EP and CE to formulate environmentally synergistic management development strategies and improve ecological quality according to local conditions.

Background: Most existing chemical experiment teaching systems lack solid immersive experiences, making it difficult to engage students. To address these challenges, we propose a chemical simulation teaching system based on virtual reality and gesture interaction. Methods: The parameters of the models were obtained through actual investigation, whereby Blender and 3DS MAX were used to model and import these parameters into a physics engine. By establishing an interface for the physics engine, gesture interaction hardware, and virtual reality (VR) helmet, a highly realistic chemical experiment environment was created. Using code script logic, particle systems, as well as other systems, chemical phenomena were simulated. Furthermore, we created an online teaching platform using streaming media and databases to address the problems of distance teaching. Results: The proposed system was evaluated against two mainstream products in the market. In the experiments, the proposed system outperformed the other products in terms of fidelity and practicality. Conclusions: The proposed system which offers realistic simulations and practicability, can help improve the high school chemistry experimental education.

To achieve successful 3D concrete printing, meticulous control of the digital manufacturing process is essential, involving the precise management of mechanical components and the use of high-quality materials. Various evaluation methods have been employed in 3D printed concrete manufacturing to ensure high-quality products. This study proposes a nondestructive evaluation method for assessing unbonded interlayers during 3D printing. Two types of electrical resistivity measurements, Wenner and square array, were performed using four electrodes located in different layers. Eight square-shaped printed samples comprising ten layers were fabricated, including sound and unbonded cases along the directions of the interlayer length and depth. Based on the multi-points measurements, both nondestructive methods were compared to identify the optimal approach for unbonding the interlayer. The measured electrical resistivity was correlated with the obtained flexural strength, and a relationship between destructive and nondestructive results was proposed. Consequently, reproducible measurements of the electrical resistivity on the surface of layered concrete filaments allow the evaluation of interlayer bond properties in the freshly 3D printed concrete.

Natural fiber insulation materials can offer a sustainable alternative to mineral and petrochemical-based insulation materials when suitable raw materials and appropriate production processes are considered. Within the scope of our research, natural fibers like cotton, flax, hemp, wool, and coir, as well as regenerated cellulose fiber, were processed into insulation materials and examined concerning their thermal conductivity. We demonstrate that simple test methods for fiber fineness measurement with air-flow methods such as Airflow and Shirley can facilitate incoming inspection and process monitoring for insulation manufacturers. Based on these measurements, a simple model was developed to estimate the thermal conductivity based on the fineness measurements of the raw materials. The model developed on the natural fibers for lower densities was tested on a glass fiber insulation material to check its suitability. The slight deviations achieved between the experiment and the calculation verify the practicability of the concept.

In this paper, a dispersion of glass beads of different sizes in an ammonium nitrate solution is investigated with the aid of Raman spectroscopy. The signal losses caused by the dispersion are quantified by an additional scattered light measurement and used to correct the measured ammonium nitrate concentration. Each individual glass bead represents an interface at which the excitation laser is deflected from its direction causing distortion in the received Raman signal. It is shown that the scattering losses measured with the scattered light probe correlate with the loss of the Raman signal, which means that the data obtained can be used to correct the measured values. The resulting correction function considers different particle sizes in the range of 2–99 µm as well as ammonium nitrate concentrations of 0–20 wt% and delivers an RMSEP of 1.952 wt%. This correction provides easier process access to dispersions that were previously difficult or impossible to measure. [ABSTRACT FROM AUTHOR]

A 1D model describing the dynamics of an injection moulding machine and the injection process is presented. The model describes an injection cylinder actuated by a dual-pump electro–hydraulic speed-variable drive and the filling, holding and cooling phases of the injection moulding process utilising amorphous polymers. The model is suggested as the foundation for the design of model-based pressure controllers of, e.g., the nozzle pressure. The focus is on using material, mould and machine properties to construct the model, making it possible to analyse and design the dynamic system prior to manufacturing hardware or conducting experiments. Both the presented model and the developed controller show good agreement with experimental results. The proposed method is general in nature and enables the design, analysis and evaluation of the machine, material and mould dynamics for controller design based solely on the physical properties of the system. [ABSTRACT FROM AUTHOR]

Objective: This research aims to elucidate critical impurities in process validation batches of tacrolimus injection formulations, focusing on identification and characterization of previously unreported impurity at RRT 0.42, identified as the tacrolimus alcohol adduct. The potential root causes for the formation of new impurity was determined using structured risk assessment by cause and effect fishbone diagram. The primary objective was to propose mitigation plan and demonstrate the control of impurities with 6 month accelerated stability results in development batches. Methods: The investigation utilizes method validation and characterization studies to affirm the accuracy of quantifying the tacrolimus alcohol adduct. The research methodology employed different characterization techniques like rotational rheometer, ICP‒MS, MALDI-MS, 1H NMR, 13C NMR, and DEPT-135 NMR for structural elucidation. Additionally, the exact mass of the impurity is validated using electrospray ionization mass spectra. Results: Results indicate successful identification and characterization of the tacrolimus alcohol adduct. The study further explores the transformation of Tacrolimus monohydrate under various conditions, unveiling the formation of Tacrolimus hydroxy acid and proposing the existence of a novel degradation product, the Tacrolimus alcohol adduct. Six-month data from development lots utilizing Manufacturing Process II demonstrate significantly lower levels of alcohol adducts. Conclusions: Manufacturing Process II, selectively locates Tacrolimus within the micellar core of HCO-60, this prevent direct contact of ethanol with Tacrolimus which minimizes impurity alcohol adduct formation. This research contributes to the understanding of tacrolimus formulations, offering ways to safeguard product integrity and stability during manufacturing and storage. [ABSTRACT FROM AUTHOR]

For single crystal diamond (SCD) to gain practical use in technical applications including solid state electronics, thin (< $1 ~\mu \text{m}$), doped epitaxial SCD layers with very low (<1 nm) surface roughness are required. Conventional SCD chemical mechanical polishing (CMP) processes are insufficient to meet the requirements of such applications because the material removal rate (MRR) is often characterized inappropriately, and the material removal uniformity is seldom considered. In this study, chemical vapor deposition (CVD) growth of two lightly boron doped (p-) epilayers was performed on 3° misoriented (100) high pressure high temperature substrates of 4.5 x $4.5 mm^{2}$ area. A subsequent 8-hour oxidative CMP process utilizing potassium permanganate and a novel self-leveling holder design decreased the average surface roughness from 3.83 nm and 1.57 nm to 0.20 nm and 0.16 nm for the two samples, respectively. MRRs were determined by evaluating five circular wear monitor structures in each sample by atomic force microscopy before and after the CMP process. The average MRRs were found to be 38.6 nm/hr and 37.3 nm/hr for the two samples. The purpose of this study is to demonstrate a CMP process suitable for polishing thin SCD epilayers to meet the needs of solid-state electronics applications. [ABSTRACT FROM AUTHOR]

Semiconductor industry is experiencing a rising demand for environmentally friendly processes with the emphasis on green policies and worldwide environmental sustainability. Nitrogen trifluoride (NF3), the most common plasma chamber cleaning agent gas, poses a significant concern as a potent greenhouse gas since it has global warming potential (GWP), 740 times and 6 times higher than that CO2 and N2O. This study investigated the exhaust gas using quadrupole mass spectroscopy (QMS) and analyzed the change in cleaning speed and the type of exhaust gas through plasma monitoring using optical mass spectroscopy (OES). The objective is to lower the use of the amount of NF3 gas in chamber cleaning process to partially contribute the environmental sustainability in the point of semiconductor manufacturing. When a small amount of N2 was added to NF3 whose ratio of 7:23, the cleaning efficiency reached to 90% compared to NF3 gas alone. Addition of N2 positively affected electron density and temperature to increase the F-radical in remote plasma system. In conclusion, 18% of NF3 usage amount was reduced during the Sio2 deposition chamber cleaning process. [ABSTRACT FROM AUTHOR]

The coupled systems with numerous interdependent variables pose considerable control and stability issues in commercial chemical processes. These systems exhibit complex interactions, time delays, parameter uncertainties and disturbances, which can lead to poor performance and reduced productivity. Conventional single-loop controllers struggle to effectively manage the interactions between variables, leading to poor disturbance rejection and tracking accuracy. A more robust and efficient control strategy is essential to tackle these limitations. Hence, a robust decentralized PID controller design is proposed to address the shortcomings of coupled industrial chemical processes. The aim is to enhance control system performance by achieving better disturbance rejection and tracking accuracy, thereby improving process efficiency and product quality. The complementary sensitivity function is exploited to attain this, and a novel graphical tuning method is proposed for obtaining optimal PID controller parameters. The use of the H ∞ robust criterion ensures robust stability and minimizes the influence of external disturbances. The proposed approach offers an efficient means to design robust decentralized controllers for complex chemical processes. The simulation results demonstrate the effectiveness of the method compared to existing controllers. Numerically, the proposed controller is able to attain almost a 20 % reduction in integral absolute error and a 30 % decrease in the settling time for all cases compared to existing controllers. The graphical tuning method enables efficient parameter optimization, resulting in faster response times and reduced settling time. This work represents a significant step toward achieving enhanced control system performance and stability in coupled industrial chemical processes. [ABSTRACT FROM AUTHOR]

This paper explores the integration of intelligent digital twin technology with PID regulators in industrial process control utilizing smart meter data. It presents a novel approach involving the creation of mathematical models to simulate real-time system behavior, thereby enhancing the PID control loop. The focus is on the development of specialized IT infrastructure to support this integration, which includes data acquisition, processing, and control optimization. This integration aims to not only improve control system efficiency but also introduce a robust predictive maintenance framework, offering significant benefits across a wide range of industrial applications. [ABSTRACT FROM AUTHOR]

The move to integrated continuous bioprocessing (ICB), while providing a means for process intensification, can put added strain on process analytics when conventional methods are used. For instance, traditional microbial methods provide minimal value to ICB processes given that the time required for data to become available is much longer than a typical full cycle of the manufacturing process. Although rapid microbial detection has been in discussion for over 30 years, it is still not routinely deployed in commercial biopharmaceutical manufacturing. One contributing factor is the ability to integrate this technology into a process control strategy and existing quality systems. An understanding of the capability of microbial detection technology available today can be leveraged to implement a control strategy for bioburden monitoring in real time for process intermediates. One key tenet of this proposed control strategy is the use of a "two‐tiered approach" wherein a fast (but possibly less sensitive) test is used to monitor the process and trigger further action for a second, longer duration test which is used to confirm and quantify the presence of bioburden and identify the organism. This approach, presented here alongside several case studies for microbial monitoring, can have broader application for other process analytical technologies where fit for purpose methods could be employed to establish process control alongside real time continuous processes. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Aeronautical Materials is the property of Editorial Board of Journal of Aeronautical Materials and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Revista Foco (Interdisciplinary Studies Journal) is the property of Revista Foco and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Chemical Engineering (China) / Huaxue Gongcheng is the property of Hualu Engineering Science & Technology Co Ltd. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)