Process Conditions For Production Research Articles

Switching control method for collaborative robots based on hybrid Petri nets

Abstract Aiming at the different working conditions of the mixed production process of collaborative robots, three kinds of controllers with the structure of sliding mode controller, backstepping controller and feedback linearisation are designed respectively, and a control structure switching method based on Petri net is proposed. The method is able to achieve better control performance by switching into different control methods to realise the relevant work tasks (tracked motion trajectories) according to the different work tasks (tracked motion trajectories) to be accomplished by the collaborative robots.

Professional education and the needs of modern Russian industry

Aim. To identify the correspondence of the level of professional training of graduates of higher and secondary educational institutions to the needs of modern industry on the example of St. Petersburg enterprises, as well as to assess the dynamics of changes in the basic competencies of new employees coming from the educational environment to the labor collectives.Objectives. To determine the quality of interaction between the educational and industrial spheres on the example of St. Petersburg; to assess the level and dynamics of changes in professional knowledge and skills, social qualities and universal competencies of graduates of St. Petersburg higher and secondary vocational educational institutions.Methods. On the basis of employers’ survey the quality of training of graduates of St. Petersburg higher and secondary vocational educational institutions was assessed by such indicators as the level of professional knowledge and skills, social qualities and universal competences. The results of the monitoring were compared and the dynamics of changes in recent years in the quality of training of young specialists according to the main requirements of employers was revealed.Results. The degree of interaction between industrial structures and the system of professional education in the conditions of increasingly complex economic situation and social transformations is determined. The role of the enterprise as an economic unit is shown, modern labor relations in the production team are characterized. The parameters of employers’ assessment of the quality of training of graduates of St. Petersburg higher and secondary vocational educational institutions are proposed. On the basis of employers’ data, the level and dynamics of changes in professional knowledge and skills, social qualities and universal competencies of graduates of St. Petersburg higher and secondary vocational educational institutions who were hired in 2014-2022 in the St. Petersburg production sphere were assessed. Conclusions. The directions of activation of interaction between the education system and industrial production, professional orientation of young people, formation of the creative component both in the educational process and in the production team have been proposed. The efficiency of measures on formation of progressive labor market on the basis of improvement of quality of preparation of graduates of higher and secondary professional educational institutions employed at enterprises, their quick adaptation in the conditions of production process and labor relations is determined.

Improvement of Process Conditions for H2 Production by Chemical Looping Reforming

A syngas production process was studied cyclically, exploiting the redox properties of Ce-based oxygen carriers. The two steps of the looping cycle were investigated through thermogravimetric analysis and fixed bed experiments. While TGA experiments were focused on the identification of the optimal temperatures ranges for methane partial oxidation (900–1000 °C) and carrier regeneration (400–900 °C), fixed bed testing was performed isothermally (at 900 or 950 °C), with a 10% CH4 feed stream in N2 to investigate material stability and cyclic performance reproducibility. The effect of the process times on carbon deposition, specific syngas yields, and selectivity was inspected, together with the investigation of best conditions to fully regenerate the carrier, adjust the syngas final ratio, and to ensure stable performances. The obtained results ensured the possibility to work in fully isothermal operations, with CH4 conversion of up to 38% and specific yields of syngas per mass of O2 carrier between 4.0–6.8 mmol∙g−1, preserved even across cycles, thus paving the path to the development of alternative and effective processes for syngas production. Under the operating conditions of the lab-scale experiment, an effective reforming time was 20 min, corresponding to 1.16 times of the characteristic time of reaction kinetics at 950 °C.

Consumer insights into the at-home liking of commercial beers: Integrating nonvolatile and volatile flavor chemometrics.

Consumer acceptability of beers is influenced by product formulation and processing conditions, which impart unique sensory profiles. This study used multivariate techniques to evaluate at-home consumer sensory acceptability of six commercial beers considering their style, fermentation type, and chemical composition. Samples included top-fermented beers (American India Pale Ale and Stout) and bottom-fermented beers (Pilsner, zero-alcohol Pilsner, Vienna Lager, and Munich Dunkel). Beer consumers (n = 50) conducted sensory hedonic, check-all-that-apply (CATA) and just-about-right (JAR) tests. Chemometric variables included iso-alpha-acids, hordenine, and volatile aromatic compounds, quantified by chromatographic methods, whereas bitterness units (IBU) were determined spectrophotometrically. Lager beers had higher acceptability than top-fermented beer (p < .05) for all attributes. Light-colored beers and medium-height foams had the highest liking scores for visual sensory attributes. Higher concentrations of bitter-tasting molecules, hordenine, and acidity decreased the liking scores of top-fermented (Ale) beers, as a sensory penalty analysis suggested. In contrast, the most favored beers (Pilsners and Munich Dunkel) contained higher fusel alcohol esters linked to fruity aromatic notes. Although a low conversion rate of fatty acids into fruity esters was noted in nonalcoholic Pilsner, its overall liking score was not statistically different from the alcoholic version. However, consumers perceived the nonalcoholic Pilsner as less bitter than its alcoholic counterpart even when IBUs were nonsignificantly different. This study emphasized the significance of understanding beer chemometrics to comprehend consumer acceptability, highlighting the crucial role of bitter molecules. Hence, hordenine, acidity, and volatile contents provided additional and valuable insights into consumer preferences.

Нейросетевое прогнозирование дефектов производства металлургической продукции

The paper is devoted to the current problem of reducing the percentage of defective products produced at serial steelmaking plants. To study the patterns of defect formation, a neural network was created that predicts the formation of defects such as “crack” in castings produced by the open-hearth method. To train the neural network, statistical data on the chemical composition of ore raw materials and the corresponding values of the percentage of defects were used. The data was taken under the conditions of an ongoing serial production process, which led to a high degree of noise in the information both on the chemical composition of the ore raw material and on the mechanical properties based on the results of its heat treatment. Outliers of statistical information were detected and removed using the original author’s neural network technique. A neural network model for controlling thermophysical and chemical-energy-technological processes of thermal processing of ore raw materials was created on the basis of a perceptron-type neural network with sigmoid activation functions. By conducting virtual computer experiments on a neural network model, some important dependences of the probability of formation of the defects under study on the content of manganese, phosphorus, silicon, chromium and sulfur were identified. Based on the identified dependencies, practical recommendations have been developed to reduce the percentage of defects by adjusting the chemical composition of ore raw materials. Despite the relatively low accuracy of the developed neural network model, the application of the practical recommendations obtained made it possible to reduce the percentage of defective products manufactured in a large-scale production process by 2.51 times.

Proceedings of the 2023 Viral Clearance Symposium, Session 2: Viral Clearance Strategy and Case Studies.

This session deals with the rational design of viral clearance studies for biopharmaceuticals including recombinant proteins such as monoclonal antibodies and, as new in scope of the symposium, also viral clearance for adeno-associated viral (AAV) vectors. For recombinant proteins, large datasets were accumulated over the last decades and are intended to be used for accelerated product process development and streamlining of viral clearance studies. How to utilize prior knowledge in viral clearance validation and how it can be used in a risk assessment tool to decide whether additional virus clearance studies are necessary during product development is being addressed by three of the presentations of this session. This also includes an a priori intended design and generation of validation data for a new kind of detergent such as CG-110, to build up a platform dataset to be used as prior knowledge in future marketing application. Another presentation investigates the virus removal mechanism of a newly developed hydrophobic interaction chromatography (HIC) resin and demonstrates for highly hydrophobic antibodies appropriate reduction for a retrovirus and impurities in a defined process range in contrast to the moderate to poor virus reduction of recent HIC resins. The last two presentations deal with virus clearance approaches for AAV, which will become mandatory with approval of the ICH Q5A revision. Appropriate virus removal and virus inactivation procedures can be implemented into the manufacturing processes of AAV vectors including viral filtration, viral inactivation (e.g., heat inactivation), affinity chromatography, and anion-exchange chromatography with which it seems possible to achieve a good clearance for helper and also adventitious viruses. The heat treatment step can be even a robust step for adenovirus helper inactivation for AAV products when product characteristics and process conditions are understood.

Study of phosphoric acid slurry rheological behavior in the attack reactor and development of a model to control its viscosity using artificial intelligence

This work aims to determine the rheological properties of the industrial phosphoric acid slurry and its behavior under the operating conditions of the phosphoric acid production process. For that, several experimental tests on the slurry were carried out, using a Rheometer (Anton Paar), which testing the effect of temperature and solid content. The results show that, for a fixed solids rate, the viscosity of the slurry decreases with temperatures from 75°C to 82°C and increases for temperatures above 82°C considered as the maximum temperature required by the process. This phenomenon is due to the morphological change of the gypsum which corresponds to the range of calcium sulfate hemihydrate formation. For a fixed temperature, the viscosity increases with increasing slurry solid content (31% to 37%). The viscosity increases with the shear gradient. Increasing the solid charge in the slurry increases its resistance to flow and movement. Thus, the slurry has a higher tendency to settle. A comparative study of four rheological models, Casson, Bingham, Ostwald and Herschel-Buckley, led to the selection of the Herschel-Bulkley model. This predicts the behavior of the phosphate slurry with a correlation coefficient of 99.9% and a MAE less than 4%. Overall, the results show that the threshold flow of the slurry is negligible, and its behavior is nonlinear. Thus, the slurry is a non-Newtonian fluid, with a dilatant rheological behavior. The various tests carried out enabled us to measure the viscosity of the phosphoric acid suspension for different solids contents and at different temperatures. The results obtained enabled us to study the rheological behavior and develop an artificial neural network model to control the viscosity of the slurry at the phosphoric acid attack tank.

Consistency Analysis of Rendement and Quality of CPO (Crude Palm Oil) Palm Oil Processing at PT. Agricinal North Bengkulu

The yield and quality of CPO is influenced by the condition of unripe and overripe FFB (fresh fruit bunches), which can cause an increase in ALB, water content and dirt content. The quality of CPO is also influenced by FFB from the community. Analysis of the consistency of the yield and quality of CPO was carried out due to the age of the plants that were too old and the performance of the factory machines decreased due to the age of the machines. Analysis of yield consistency and quality was carried out using statistical quality control methods, namely quality control using a statistical approach using control charts and causal diagrams. This study uses secondary data on the yield and quality of CPO for the past year (July 2021-June 2022). The research results show, there are data that are outside the upper control limit, yield in July 2021, free fatty acid content in May 2022 and dirt content in October 2021. While the water content is statistically controlled (in statistical control). The yield and quality of ALB are influenced by type of raw material, production capacity and oil losses. Moisture content and dirt content are affected by treatment of production process and machine conditions.

Biodiesel Production Using Catalyst Na&lt;sub&gt;2&lt;/sub&gt;O/Fly Ash from Waste Cooking Oil (WCO) with Transesterification Process

The consumption of fuel oil in all countries in the world is always increasing. Indonesia is one of the countries that are still dependent on fuel oil, especially for transportation and industry. Biodiesel is known as an alternative to diesel fuel that is believed to be able to overcome the problems of world energy needs. One of the raw materials that have the potential to be biodiesel is Waste Cooking Oil (WCO). This research aims to study the Na2O/Fly ash catalyst preparation process used for the transesterification reaction of WCO into biodiesel, study of purifying WCO as a raw material in biodiesel, analyze the effect of the methanol molar ratio to oil, catalyst loading and reaction time on the transesterification process in terms of the yield of the reaction, density, viscosity and an acid number of biodiesel product. The research method was begun preparation of Na2O/Fly ash catalyst and purification of WCO with despicing and neutralization methods. Afterwards, the transesterification process was running by varying %wt of the catalyst, the molar ratio of methanol to oil, and reaction time. The percentage weight of the catalyst used is 4% and 6% to the WCO weight, the molar ratio of methanol to oil is 6:1 and 8:1, and the transesterification reaction time used is 60, 80, 100 and 120 minutes. The results showed that the Free Fatty Acids (FFA) of WCO raw material was 3.102%, but after the despicing and neutralization processes were carried out, the FFA of WCO decreased to 2.538% and 0.282%, respectively. The optimal condition for the biodiesel production process was obtained when the catalyst weight is 6% with a molar ratio of methanol to oil by 8:1 which runs in 120 minutes. In these conditions, the obtained yield of reaction results are 99,09%, density 882 kg/m3, viscosity 11.15 cSt and an acid number of 0.2244 mg KOH/g. The results of XRD analysis on the catalyst Na2O/Fly ash is dominant by alumina (Al2O3), silica (SiO2), ferrous oxide (Fe2O3), calcium oxide (CaO), and natrium oxide (Na2O) compositions. Moreover, GCMS analysis on biodiesel showed that the methyl ester content formed was 98.13%. Based on parameters above, density and acid number has met the quality standards of SNI 7182: 2015.

Design and Implementation of Integral Ergo-Value Stream Mapping in a Metal-Mechanical Company to Improve Ergonomic and Productive Conditions: A Case Study

The Integral Ergonomic-Value Stream Mapping (Ergo-VSM) methodology is introduced in this study, which is tailored for the metal-mechanic sector and aims to assess the operational and ergonomic conditions of production processes. The methodology is designed to identify ergonomic risks and propose an improvement plan to increase productivity by integrating ergonomic measurement instruments aligned with official standards and lean manufacturing tools such as VSM and Kaizen. The study, which was conducted in a metal-mechanical MSME (micro, small and medium enterprises), resulted in an 11.8% overall improvement in psychosocial risk factors, a 4.4% increase in productivity with a 1.96-h reduction in cycle time, and a 20% decrease in reported quality rejections. Notably, the study shows that the Integral Ergo-VSM can be implemented in a variety of organizational contexts, ensuring adaptability without jeopardizing the methodology’s core objectives.

Process Prediction and Feature Visualization of Meltblown Nonwoven Fabrics Using Scanning Electron Microscopic (SEM) Image-Based Deep Neural Network Algorithms

Meltblown nonwoven fabrics are used in various products, such as masks, protective clothing, industrial filters, and sanitary products. As the range of products incorporating meltblown nonwoven fabrics has recently expanded, numerous studies have been conducted to explore the correlation between production process conditions and the performance of meltblown nonwoven fabrics. Deep neural network algorithms, including convolutional neural networks (CNNs), have been widely applied in numerous industries for tasks such as object detection, recognition, classification, and fault detection. In this study, the correlation between the meltblown nonwoven fabric production process and performance was analyzed using deep neural network algorithms for classifying SEM images. The SEM images of meltblown nonwovens produced under various process conditions were trained using well-known convolutional neural network models (VGG16, VGG19, ResNet50, and DenseNet121), and each model showed high accuracy ranging from 95% to 99%. In addition, LRP (Layer-wise Relevance Propagation) and Gradient-weighted Class Activation Mapping (Grad-CAM) models were applied to visualize and analyze the characteristics and correlation of the SEM images to predict the meltblown nonwoven fabric production process.

Selection of batch process conditions for microbiological production of lactic acid using waste whey

Selection of batch process conditions for microbiological production of lactic acid using waste whey

Fertility and Phytosanitary Qualities of Promising Raw Materials for the Formation of Artificial Soil Mixs

The use of artificial soil mixtures programmed for each specific type of plants and conditions of the agricultural production process will significantly increase the yield of crops grown in greenhouse plants. The variants of the formed artificial soil mixtures have been studied, their compliance with the optimal set of fertile components has been verified. In the future, the studied soil mixtures are able to fill the deficit of a fertile soil resource, especially in closed ground conditions.

Assessment of the content of macronutrients and microbiological safety of dry dog foods

In Europe, there are no legal regulations specifying maximum allowable limits for pathogenic bacteria or fungi and yeasts in dog food. For proximate composition, the European Pet Food Industry Federation (FEDIAF) nutritional guidelines provide minimum recommended levels for protein and fat only, not for other ingredients and no safe maximum levels. Therefore, the aim of this study was to evaluate the microbiological safety of 35 dry dog foods, taking into account the division into foods with grains as the main plant ingredient and those described as grain-free. We assumed that grain-included foods are more susceptible to the presence of the total number of aerobic bacteria. This parameter is an essential, hygienic criterion informing about the microbiological safety of the pet food. It also inform about the microbiological quality of the food ingredients used, the effectiveness of decontamination during the production process, sanitary and hygienic conditions during the acquisition, processing and marketing of pet food and its components. In the case of macronutrients, the results in some cases were multiples of the minimum recommended levels. The most important microorganisms that presence was found in the analyzed dog foods were indicator bacteria (E. coli and coliform bacteria, Clostridium perfringens), whose presence in feed constitutes microbiological contamination. They inform about sanitary and hygienic conditions during the production and storage of the pet food. The current guidelines recommend microbiological testing of food for the presence of Salmonella bacilli as the basic indicator for assessing the sanitary quality. No Salmonella spp. was detected in any of the foods. The remaining analyzed bacteria (Proteus spp., Enterococcus spp., Staphylococcus spp.) as well as molds and yeasts, were present in both grain-included and grain-free foods. The obtained results showed that in terms of microbiological safety, grain-included foods come out worse, because microorganisms were detected more frequently in this type of dry dog food.

Cloud–edge collaborative control for roaster furnace: A hybrid first-principles and data-driven method

Temperature stability control of the roaster furnace is an important yet challenging problem due to the fluctuation of feed compositions. To solve this problem, a first-principles and data-driven cloud–edge collaborative control (CECC) method is proposed. Specifically, through first-principles analysis, the influencing factors of temperature fluctuation are determined, and then the feed fluctuation is divided into two parts: the batch difference (BD) caused by changes in production objectives or process conditions, and the random fluctuation (RF) caused by uncertain factors of component content or ore source mixing process. For the problem of BD, a first-principles model of the roasting process is established by integrating multisource data in the cloud. Through timely response to the batch differences, the appropriate feed rate is sent to the edge controller to address the temperature unstable problem induced by the sudden component batch changes. For the problem of RF, a fuzzy controller based on trend analysis is adopted at the edge to fine-tune the feed rate to further reduce the negative impact of component fluctuation on the temperature. Accordingly, the proposed CECC method can realize stable control of the roaster furnace temperature synergistically. Both the numerical simulation experiment and hardware-in-the-loop platform experiment results verify the effectiveness of the proposed method.

Optimization of lactic acid bacterial starter culture to improve the quality and flavor characteristics of traditional Hurood

Hurood is a traditional fermented milk product prepared by traditional Mongolian techniques of fermenting raw milk, partial degreasing, heating, whey drainage, emulsification of curd, and molding. Currently, Hurood available in the market is generally prepared by small-scale enterprises at home or in open air. Therefore, lack of standardization of bacterial starter culture leads to variation in the flavor and sensory properties of Hurood from batch to batch. In this study, we aimed to assess the best starter culture combination obtained from 37 lactic acid bacterial strains isolated from traditional Hurood. The solidification state and sensory quality were used as indexes for determining the fermentation efficiency of the bacterial starter culture combinations. The yield and texture characteristics were used to determine the optimal ratio of bacterial strains in a combination and the processing conditions for traditional Hurood production. The most optimal bacterial culture combination was observed to be NF 9-3:NF 10-4:CH 3-1 in 5:4:1 ratio and in 3% amount. The most optimal whey temperature and heating-stirring temperature were observed to be 55°C to 60°C and 85°C to 90°C, respectively. Hurood prepared with the optimal combination of bacterial strains exhibited significantly enhanced sensory quality, flavor, and contents of AA and fatty acids. Therefore, the use of optimal starter culture of lactic acid bacteria could produce Hurood with significantly superior sensory qualities, making the product more acceptable to consumers.

Optimisation and physicochemical characterisation of a thermo-alkali stable laccase produced by wastewater associated Bacillus sp. NU2

ABSTRACT Laccase is a multicopper enzyme that plays a unique role in bioremediation of environmental pollutants. Bacteria were isolated from hospital wastewater and screened for laccase production. The laccase production process condition was optimised, and the laccase obtained was characterised. The 16S rRNA molecular analysis conducted on the best laccase producer revealed a Bacillus sp. NU2 identified. The process conditions: pH5, 45°C, 100 rpm, 5% inoculum, and growth constituents viz: tangerine peel and wheat bran agro-wastes, beef extract, ammonium persulfate, glucose, galactose, xylose, sorbitol, fructose carbon sources; and 4-aminophenol inducer optimally stimulated laccase production. The Bacillus sp. NU2 laccase was optimal at pH and temperature conditions of 8.0°C and 60°C, with a noteworthy pH and thermal stability observed. Furthermore, NU2 laccase showed a moderate/high tolerance and relative activity effect on various chemical inhibitors, halides and surfactant of triton x-100 (105 ± 0.92%), PMSF (107 ± 0.81%), and NaCl (94 ± 0.81%) at 1, 3, and 6 (mM) concentration. Additionally, NU2 laccase maintained a relative activity of 101%, 104%, and 102% for Mg2+, Zn2+, and Fe3+ at 1, 3, and 6 mM respectively. Acetone and propanol significantly upregulated laccase activity at 114 ± 0.0008% and 118.24 ± 0.35 and also at 30 and 20 (%) concentrations. Conclusively, the tolerant effect of Bacillus sp. NU2 laccase in pH, temperature, inhibitors and organic solvents suggests its potential for biotechnological application and promotion of a greener environment.

Validation of the media fill method for Cytokine-Induced killer cells manufacturing process

BackgroundMedia fills are used to demonstrate the adequacy of the aseptic conditions of a pharmaceutical production process, according to good manufacturing practice (GMP), using a growth medium in place of the product solution. For advanced therapy medicinal product (ATMP), where the final product consists of viable cells, the media fill is still a challenge, but represents the starting point for process validation.MethodsThe aim of this paper is to describe the media fill test procedure in the context of ATMP manufacturing, in particular of Cytokine-Induced Killer (CIK) cell expansion process under GMP conditions, including quality control tests and environmental monitoring. The media fill test has been designed to cover all the critical steps of the process, including worst cases and deviations.ResultsFrom July 2019 to August 2022, we performed 16 media fill tests. During these years, the media fill protocol has been gradually improved and the worst cases were designed to be closer to reality and occurring cases. Although some deviations occurred, all the media fills performed were compliant.ConclusionsA good media fill design combined with a robust environmental monitoring program provides a high degree of assurance of the microbial safety of ATMPs.

Influence of cationic surfactants on the growth of gypsum crystals

Abstract The effect of cationic surfactants on the growth of gypsum was evaluated under conditions of a simulated production process of gypsum desulfurization. We used a laser particle size analyzer and a microscope to determine the particle size and morphology. The growth rate of gypsum was determined by the equation for the rate of chemical reaction of CaSO4·2H2O. The results showed that the growth rate at a supersaturation ratio of 2.4 increased by 50% with 30 mg/L of a dodecyldimethylbenzylammonium chloride. The gypsum morphology changed from needle-like in the absence of additives to tabular in the presence of cationic surfactants, indicating that relatively thicker and larger crystals were formed. Finally, the investigated cationic surfactants were beneficial to the normal operation of the desulfurization process.

PH, the Fundamentals for Milk and Dairy Processing: A Review

The ability to measure and capture real-time unit operational data has significant benefits during dairy processing, whether it is the basics, such as measuring temperature, pressure, and flow rates, or more recent developments in the case of in-line viscosity and product-compositional measurements. This rapid data collection has helped increase profitability by reducing energy costs, minimizing product loss, and allowing automated control. Advances in technology have allowed for in-line measurements of the composition and some physical attributes such as particle size and viscosity; however, an attribute that spans both compositional and physical attributes is pH, directly influenced by composition but also environments, such as temperature and dry matter content. pH is measured for a plethora of reasons, such as a measure of milk quality (microbial spoilage), acidification of casein, cheese production, maintaining optimum conditions during protein hydrolysis, etc. However, very little is published on the fundamentals of pH and pH measurement in dairy processing; rather, it is usually a cause-and-effect phenomenon. This review visits one of the oldest analytical considerations in the dairy industry and re-examines how it is affected by product composition and processing conditions.