Industrial Production Control Research Articles

Revealing novel insights into the enhancement of quality in black tea processing through microbial intervention

Black tea is highly favored by consumers worldwide, with enzymatic reactions being recognized as a pivotal factor influencing tea quality. The role of microorganisms in shaping the composition of black tea has emerged as a focus of research due to their involvement in enzyme catalysis and metabolic processes. In this study, full-length amplicon sequencing combined with qPCR more accurately reflected microbial profile, and Pantoea, Pseudomonas, Paucibacter, and Cladosporium were identified as the main microbial genera. Moreover, by comprehensively analyzing color, aroma, and taste components over time in black tea samples, correlations were established between the dominant genus and various quality factors. Notably, peroxidase activity levels, total soluble sugar content, and tea pigments concentration exhibited significant associations with the dominant genus. Consequently, this microbiological perspective facilitated the exploration of driving factors for improving black tea quality while establishing a theoretical foundation for quality control in industrial production.

High Throughput Quality Control Tools for Carbon-Related Materials: A Raman Approach

Carbon-based materials play a pivotal role in battery technology, serving as negative electrode materials, conductive additives, and coating layers for both positive and negative electrode materials. Traditional characterization methods, such as transmission electron microscopy (TEM) and X-ray diffraction (XRD), fall short in providing comprehensive quality control, especially when distinguishing the structure of amorphous carbon materials. Raman spectroscopy as a convenient, simple tool is widely used to study the structure of carbon materials. It provides insights into the degree of crystallization, doping degree, and subtle structural differences arising from various preparation processes. By quantifying Raman spectrum testing results through statistical methods and providing relevant statistical outcomes, we demonstrate the potential of Raman spectroscopy as a quality control method for carbon material characterization. With extensive sample testing and automation, along with standardized spectral data processing and analysis software, we propose Raman spectroscopy as a suitable tool for high-throughput quality control in industrial production.

AEDN-YOLO: an efficient one-stage detection network for strip steel surface defects

Steel surface defect detection is one of the key tasks in industrial production and quality control. Research on defect detection using deep learning algorithms has shown promising results. However, due to the complex backgrounds, large differences in defect sizes, and diverse defect types present in steel strip surface defect images, existing deep learning algorithms struggle to achieve precise detection. To address these challenges, this paper proposes an efficient detection model named AEDN-YOLO. Firstly, an adaptive feature extraction (AFE) module is designed, embedded into C2f to better capture irregularly shaped objects. Secondly, the Triplet Attention module is incorporated into the bottom layer of the backbone network to enhance the model’s ability to locate defect features accurately. Additionally, replace the standard convolution in the neck network with GSConv, which not only accelerates feature fusion to improve detection speed but also enlarges the model’s receptive field to enhance detection accuracy. Finally, add a small target detection layer to enhance the detection capability for tiny defects. The model achieves mAP of 81.7% and 72.7% on the NEU-DET and GC10-DET datasets, respectively, with a detection speed of 72.1 FPS. Compared to mainstream defect detection algorithms, the proposed algorithm enables accurate and efficient detection of steel surface defects.

Lipidomic Profiling of Flammulina velutipes (Curtis) Singer (Agaricomycetes) through Ultra-Performance Liquid Chromatography Coupled with Quadrupole Time-of-Flight Mass Spectrometry: Examining Lipid Dynamics Changes during Fruiting Body Formation and Development.

Flammulina velutipes (enokitake) is widely recognized for its nutritional and medicinal properties. Understanding the biochemical processes, such as lipid metabolism during fruiting body formation, is essential for enhancing mushroom cultivation and utilization. This study aimed at elucidating the dynamic lipidomic changes during seven growth stages of F. velutipes using ultra-performance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Our results revealed significant increases in ceramides along with the growth and a sharp decline in phosphatidylinositols from mycelial to primordial stages. Fatty acid esters of hydroxy fatty acids, recently discovered for their bioactivities, showed high intensities in the mycelial and primordial stages but decreased rapidly thereafter. These findings provide profound insights into the lipid profiles associated with mushroom morphology and development. This lipidomics study establishes a foundational understanding for future research in agricultural and food chemistry applications, potentially improving industrial production and quality control of F. velutipes.

Development path of digital cultural industry by integrating proportional integral and differential algorithm from the perspective of cultural innovation

The digital culture business benefits from quick technical updates, digital manufacturing, communication networks, and customized consumption, which promotes new supply and consumption. The innovation and development of the digital cultural industry cannot be separated from the physical industry. The efficient production of the physical industry can ensure the innovative development of digital cultural industry. Therefore, to improve the production efficiency of physical industry, this research proposes a temperature control model combining whale optimization algorithm and fuzzy proportional integral differential algorithm based on the traditional temperature control in ceramic firing and wine making process. Firstly, fuzzy control theory is used to improve the proportional integral differential algorithm, and a fuzzy proportional integral differential model with adaptive adjustment function is established. On this basis, to quickly confirm the optimal parameters of the proportional integral differential model, the whale optimization algorithm is introduced to further optimize its weight factors. It was verified that the temperature control adjustment model combining whale optimization algorithm and fuzzy proportional integral differential model was 2.77 s, which was shortened by 1.11 s, 2.37 s and 3.13 s, respectively than the other three models. Therefore, the constructed temperature control model can effectively realize high-precision intelligent temperature control in industrial production, laying the cornerstone for promoting the innovative development of digital culture industry. The proposed model can improve the production efficiency of physical industries, promote digital transformation, and optimize the innovative development of digital cultural industries.

Assessment of the Conformation Stability and Glycosylation Heterogeneity of Lactoferrin by Native Mass Spectrometry.

Lactoferrin (LTF) has diverse biological activities and is widely used in functional foods and active additives. Nevertheless, evaluating the proteoform heterogeneity, conformational stability, and activity of LTF remains challenging during its production and storage processes. In this study, we describe the implementation of native mass spectrometry (nMS), glycoproteomics, and an antimicrobial activity assay to assess the quality of LTF. We systematically characterize the purity, glycosylation heterogeneity, conformation, and thermal stability of LTF samples from different sources and transient high-temperature treatments by using nMS and glycoproteomics. Meanwhile, the nMS peak intensity and antimicrobial activity of LTF samples after heat treatment decreased significantly, and the two values were positively correlated. The nMS results provide essential molecular insights into the conformational stability and glycosylation heterogeneity of different LTF samples. Our results underscore the great potential of nMS for LTF quality control and activity evaluation in industrial production.

Promotion Effect of Micro-Hole in Dielectric on Ozone Generation of Dielectric Barrier Discharge

ABSTRACT Ozone is widely used in industrial production, disinfection, and pollution control. To improve the ozone generation ability of dielectric barrier discharge (DBD), micro-holes with a diameter of about 50 µm in dielectric were introduced to optimize the discharge process. Experimental results indicate that the micro-holes in dielectric can increase the ozone concentration by lowering the inception voltage and boosting the intensity of electric discharge of the DBD device. A voltage of 16.7 kV and flow rate of 3 L/min, the DBD device with 40 micro-holes has an ozone concentration of 680 mg / L and provides an ozone yield of 320 g / kWh, while the device without micro-holes has an ozone concentration of only 150 mg/L and provides an ozone yield of only 180 g/kWh. The micro-hole in the dielectric plays the effect similar to that of micro hollow cathode, which can not only directly affect the ozone generation ability, but also affect the effect of other factors on ozone generation, such as discharge voltage, air flow rate, and gap space between dielectrics. The promotion of ozone generation by micro-hole can be used to design high-performance ozone generators and provide ideas for reusing ozone generators damaged by dielectric breakdown.

Application of sliding mode variable structure control algorithm in PMSM vector control system in complex environment.

In order to meet the increasing demand of high-performance control in industrial production, a new sliding mode variable structure control algorithm, Asymptotic Sliding Mode Control (ASMC), is designed in this study to solve the serious chattering problem of sliding mode control. Firstly, a traditional sliding mode exponential approximation law control model and a state space and control function are constructed based on sliding mode control. Secondly, by eliminating the jitter factor, ASMC algorithm is combined with sliding mode control to achieve precise control of permanent magnet synchronous motor (PMSM) and improve its performance. The experimental results indicated that in the simulation experiment, the research system tended to stabilize within 0.2-0.3 seconds, and the system chattering was significantly suppressed. And its output was smoother, the jitter amplitude was significantly reduced by 1/3, and the output torque was more stable. In addition, when the parameter H0 changed to 2H0, the overall speed curve did not change much, with only a slight overshoot. The overshoot was only 2.8%, and the change amplitude was maintained at around 25r/min, indicating that the research system had strong self stability performance. In actual experiments, the current command oscillation of the research system was significantly reduced. The local graph showed that the output fluctuation amplitude of the asymptotic approach law actual control was significantly smaller under no-load disturbance. When the H0 changed towards 2H0, the actual adjustment time was about 0.1 seconds, which was consistent with the simulation experiment. Therefore, the contribution of the research is that the ASMC algorithm can suppress the chattering problem of the system and improve the approaching speed, thus improving the speed regulation quality of the system. This new algorithm has great theoretical and practical significance for improving the performance of PMSM, and is practical in the actual vector control system of PMSM.

Use of multi-agent system for industrial production control

This paper describes specific implementation of Asset Administration Shell technology used for an industrial distributed control system. The base of this control system is a multiagent system of digital twins which was created by AAS. This multiagent system was developed for a specific platform CP Factory (mainly based on Simatic PLC) but the implementation is y portable to each common platform. Digital twin of several types of components of typical industrial production process are described in this paper with the implementation of active and passive administration shell. The main focus is on describing the way of integrating digital twins into the production system and the necessary SW tools. Industry 4.0 language was used as a common communication protocol as well as OPC UA and MQTT.

Exploration and Application of Cloud-Network Integration Control Architecture in Industry

Cloud-network integration(CNI) is an inevitable choice to enhance the supply capacity of industrial Internet. In traditional industrial control systems, there are problems such as insufficient depth of perception, insufficient connectivity and insufficient analytical predictability. Firstly, an industrial CNI control architecture is proposed in this paper. Then a software-defined PLC integrated development & runtime environment based on the cloud framework is developed and deployed on a private cloud platform. An efficient 5G private network is created to facilitate wireless omnidirectional connectivity of cloud PLC. The problems of complex industrial field circuits and difficult to unify protocols are solved through 5G intelligent terminal devices. Finally, the cloud control architecture and software platform are successfully applied to the remote centralized control of the tundish preparation system in a steel enterprise’s two steelmaking plants. The results shows that the innovative system architecture meet the requirements for high-performance access, transmission, computing and storage in industrial plants, which achieves the cloud control of entire process industrial automation production.

Identification of pressed and extracted vegetable oils by headspace GC-MS

Edible vegetable oils are produced either by mechanical pressing or extraction. Although pressing retains the inherent flavor and nutritional value of the oil, the oil yield is low and the process expensive. Extraction methods have high oil yields, low processing costs, and economic benefits; however, No. 6 solvent, which may pose potential risks to human health, is commonly used in the extraction and cleaning process. Differentiating extracted oil containing these solvents from pressed oil, for quality control, based on visual appearance is difficult. Hence, in this study, an identification method using the characteristic components of solvent No. 6 under optimized headspace Gas chromatography-mass spectrometry (GC-MS) conditions was established. It also provided a reference for quality control of industrial production by estimating the amount of solvent present in the oil. Results showed that, in addition to five main components (2-methylpentane, 3-methylpentane, and n-hexane, Methylcyclopentane, Cyclohexane), accounting for 97% of the solvent, No. 6 solvent also contains 16 types of organic substances, such as olefins, aromatic hydrocarbons, and polycyclic aromatic hydrocarbons. Under optimized headspace GC-MS conditions (headspace sampler equilibrium temperature = 150 °C), the No. 6 solvent exhibits high linearity over a concentration range of 0.05–1 mg/kg with a correlation coefficient of 0.999 and a detection limit of 0.01 mg/kg. Pressed and extracted oils can be determined as follows: If three or fewer main components of the No. 6 solvent are detected, and the total content of No. 6 solvent is less than 0.5 mg/kg, it is a pressed oil; if four or more main components of No. 6 solvent are detected, or the total content of No. 6 solvent is ≥0.5 mg/kg, it is confirmed as an extracted oil.

A versatile and customizable low-cost printed multipass microrheometer for high-throughput polymers rheological experimentation

We report the design of a multipass microrheometer that can be fully customizable at a low cost and reasonable time, which allows us to perform experiments rapidly and in a broad range of shear rates (i.e., from 0.1 to 100 s−1), using small amounts of material (i.e., just some milligrams). Additionally, the low-cost approach opens for an easy parallelization of the setup that makes it suitable for high-throughput rheological experimentation of polymer melts (HT-Rheo-E). The novel rheometer consists of a microchannel (i.e., a microcapillary or a microslit) in which the fluid flows driven by two controlled millimetric pistons (diameter of 2 mm). Two piezoelectric miniaturized pressure sensors are placed at the microchannel entrance and exit to record the pressure drop across the capillary during the motion. The current work reports the design of the rheometer with two different cross sections of the microchannel, i.e., circular and rectangular, and measurements of the shear viscosity with a Newtonian and a non-Newtonian polymer over a wide range of shear rates using less than 1 g of sample. We demonstrate that the current multipass microrheometer can measure viscoelastic properties of polymers by applying an oscillatory flow. The printed setup is of potential interest for applications in quality control in industrial production, in natural systems (such as starch-based mixtures) and academic research where rapid and repeated measurements using limited milligrams of polymer are required (e.g., biological systems).

Review of nanomaterial advances for ionizing radiation dosimetry.

There are a wide range of applications with ionizing radiation and a common theme throughout these is that accurate dosimetry is usually required, although many newer demands are provided by improved features in higher range, multi-spectral and particle type detected. Today, the array of dosimeters includes both offline and online tools, such as gel dosimeters, thermoluminescence (TL), scintillators, optically stimulated luminescence (OSL), radiochromic polymeric films, gels, ionization chambers, colorimetry, and electron spin resonance (ESR) measurement systems. Several future nanocomposite features and interpretation of their substantial behaviors are discussed that can lead to improvements in specific features, such as (1) lower sensitivity range, (2) less saturation at high range, (3) overall increased dynamic range, (4) superior linearity, (5) linear energy transfer and energy independence, (6) lower cost, (7) higher ease of use, and (8) improved tissue equivalence. Nanophase versions of TL and ESR dosimeters and scintillators each have potential for higher range of linearity, sometimes due to superior charge transfer to the trapping center. Both OSL and ESR detection of nanomaterials can have increased dose sensitivity because of their higher readout sensitivity with nanoscale sensing. New nanocrystalline scintillators, such as perovskite, have fundamentally important advantages in sensitivity and purposeful design for key new applications. Nanoparticle plasmon coupled sensors doped within a lower Zeff material have been an effective way to achieve enhanced sensitivity of many dosimetry systems while still achieving tissue equivalency. These nanomaterial processing techniques and unique combinations of them are key steps that lead to the advanced features. Each must be realized through industrial production and quality control with packaging into dosimetry systems that maximize stability and reproducibility. Ultimately, recommendations for future work in this field of radiation dosimetry were summarized throughout the review.

Effect of variable temperature levels on drying characteristics and quality indices of rice in continuous drying and multi‐stage intermittent drying

AbstractThe aim of this study was to investigate the effect of variable temperature levels on the drying characteristics and quality indices of rice in continuous drying and multi‐stage intermittent drying (MID). The quality indices of rice were assessed in terms of stress crack index, head rice yield (HRY), color, sensory characteristics, and taste value. Moreover, the microstructure of the cross‐section of rice was analyzed at different variable temperature levels. In addition, the quality indices evaluation of rice was carried out by principal component analysis. The results showed that drying temperature at the same temperature level was positively correlated with stress cracking index and total color difference, negatively correlated with drying time, HRY, whiteness index, and taste value. The MID with Δ5 (45–50°C) temperature level had the highest comprehensive score of 1.431. The results provide a reference for optimizing the drying process for rice.Practical applicationsDrying is a key control step in relation to the yield and quality of rice. A reasonable and effective variable temperature drying process can improve drying efficiency and solve the problem of the limitations of a single temperature heating method. The quality indices evaluation of rice can provide a reference for the optimization of drying parameters for different variable temperature drying processes. Moreover, the variable temperature drying method in this study can improve the adaptability of the process and provide research ideas and technical references for the industrial production and automatic control of variable temperature in rice.

Control of industrial products by microfocus radiography

X-ray methods in comparison with other control methods are characterized by high information content, clarity and efficiency. The paper presents the results of the use of microfbcus radiography in the control and diagnostics of industrial products. A distinctive feature of the microfbcus radiography method is the use of an X-ray source with a focal spot of micron sizes and a survey geometry with a direct geometric increase in the object of study. The minimum dimensions of the rendered structures in this case are not limited by the pixel size of the image receiver and can be significantly smaller. It is shown that the use of the microfbcus radiography method makes it possible to increase the information content of the resulting radiographs by at least an order of magnitude, due to an increase in spatial resolution. At the same time, the technical means for implementing the described method can be small-sized, designed for use in non-stationary and non-specialized conditions. The results obtained can be used in scientific research and industrial control in the following areas: electronics, additive technologies, instrumentation and others.

Automation of Non-Destructive Evaluation of Casting Parts based on Computed Tomography and Machine Learning

The development of digital tools exploiting computed tomography (CT) data intelligently, in their entirety and in a simple manner is a major challenge for the full deployment of this technology in industrial production control environment. This work aims at developing a pipeline able to detect material discontinuities in metallic parts, in an automated way without human analysis, to classify them according to their nature and to apply criteria resulting from specifications to rule on the acceptance or not of the parts. It exploits the last advances in artificial intelligence data treatment, and it is based on a dedicated processing and visualisation platform that optimizes the handling of large volumes of data.

The principles of ergodesign in products from composite materials

The article is devoted to the possibilities of applying the principles of ergodesign in products made of composite materials. Composites with such characteristics as high strength and high quality, in addition to the use of various technological techniques in their manufacture, require solving problems of effective user interaction, that is, ergonomics and aesthetics (design). The general task of ergonomics and design (ergodesign) includes user and visual testing (VT or VI) and shirography (speckle interferometry) with direct adjustment to the user. The article also discusses the main methods of quality control of industrial and technical products made of composite materials. The advantages and disadvantages of quality control methods, the recorded parameters of CM products and their application areas are considered.

Redesigning industrial composite production planning and control for energy awareness

The European Union's requirement for eliminating greenhouse gas emissions from all value chains by 2050 affects most of the manufacturing activities all over the continent. The industrial production of composite parts, favored for new designs throughout the aerospace industry, does not constitute an exemption. For securing global competitiveness, CFRP manufacturers need to adapt to increasing fluctuations in energy supply and prices, induced by a growing share of renewable energy sources. Besides employing more efficient production technologies, decoupling of labor and energy intensive tasks will play a key part. Thereby, energy intensive tasks can be performed while general energy supply is high and demand is low, leading to comparatively lower prices. The perspective of energy supply and price becomes a crucial part in the design of modern production planning and control systems, not only for smokestack businesses, but for small and medium load energy consumers as well. In this contribution, a mathematical representation for modeling industrial scale composite manufacturing is proposed. Beside manufacturing's fundamental production planning and control constraints, CRFP manufacturing's very own peculiarities are outlined and considered as well. It is shown how the virtual mathematical representation of a CFRP manufacturing environment can assist in its energy aware redesign and optimization.

Insight into the aroma dynamics of Dongpo pork dish throughout the production process using electronic nose and GC×GC-MS

In this study, the aroma dynamic changes throughout the manufacturing process of Dongpo pork dish (DPD) model were investigated with electronic nose and two-dimensional gas chromatography coupled with mass spectrometry (GC × GC-MS). The results of both electronic nose and GC × GC-MS studies were consistent in that the frying and steaming stages had the greatest effect on the aroma composition of DPD. A total of 111 volatiles were detected, 59 of which were key volatiles. The odor activity analyses further revealed that pentanal, hexanal, 1-octen-3-ol, 2,3-pentanedione and (E)-2-octenal as key aroma contributors during the frying stage, while 3-methylbutyraldehyde were mainly formed during the steaming stage. These aromas were mainly generated through the thermal degradation of lipids and the Maillard reaction. Hence, this study, for the first time, provided some profound insights for the industrial production and flavor control of DPD products.

A conceptual framework for smart production planning and control in Industry 4.0

This article aims to introduce the challenge (i.e., integration of new collaborative models and tools) posed by the automation and collaboration of industrial processes in Industry 4.0 (I4.0) smart factories. Small- and medium-sized enterprises (SMEs) are particularly confronted with new technological and organisational changes, but a conceptual framework for production planning and control (PPC) systems in the I4.0 context is lacking. The main contributions of this article are to: (i) identify the functions making up traditional PPC and smart production planning and control in I4.0 (SPPC 4.0); (ii) analyse the impact of I4.0 technologies on PPC systems; (iii) propose a conceptual framework that provides the systematic structuring of how a PPC system operates in the I4.0 context, dubbed SPPC 4.0. Thus SPPC 4.0 is proposed by adopting the axes of the RAMI 4.0 reference architecture model, which compiles and contains the main concepts of PPC systems and I4.0. It also provides the technical description, organisation and understanding of each aspect, which can provide a guide for academic research and industrial practitioners to transform PPC systems towards I4.0 implementations. Finally, theoretical implications and research gaps are provided.