Industrial Production Control Research Articles

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.

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.

SOFTWARE INTEGRATION TYPE CAD-CAM-CAE IN PRODUCT LIFECYCLE MANAGEMENT


 Abstract: Using the CAD-CAM-CAE type programs, case studies can be carried out to analyze some industrial tasks that may occur in the realization, manufacture, and operation of certain industrial components, before they are manufactured and put into operation under normal conditions. operation. Computer programs that perform a virtual modeling and an analysis of them based on the finite element method, help reduce launch and production times, control, and review of industrial products, before making the physical model. All this information resulting from simulations with specialized programs will be analyzed in detail, and the design team within the company can take the right measures to improve the final product.

Title: production planning and control in industry 4.0 environment: a morphological analysis of literature and research agenda

Title: production planning and control in industry 4.0 environment: a morphological analysis of literature and research agenda

Study on the Flavor Compounds of Fo Tiao Qiang under Different Thawing Methods Based on GC-IMS and Electronic Tongue Technology.

“Fo Tiao Qiang” is a famous dish with Chinese characteristics. It is delicious, rich in materials, and high in nutritional value. Through physical and chemical analysis, electronic tongue, gas chromatography–ion mobility spectroscopy, and other technologies, the present study explored the quality characteristics and flavor differences of Fo Tiao Qiang by using different thawing methods (natural thawing, ultrasonic thawing, microwave thawing, and water bath thawing). The results show that the protein content was slightly higher in Fo Tiao Qiang with ultrasonic thawing than others. The fat content of the microwave-thawed Fo Tiao Qiang was significantly lower than the other three kinds of samples. After ultrasonic thawing, the number of free amino acids in the samples were the highest and the umami taste was the best. Compared with natural thawing, most of the flavor substances decreased in ultrasonic thawing, microwave thawing, and water bath thawing. However, several substances increased, such as alpha-terpineol, beta-phenylethyl alcohol, phenylacetaldehyde, cis-rose oxide, isobutyl acetate, and 2–3-pentanedione. This study revealed the changing laws of different thawing methods on the quality characteristics and flavor characteristics of Fo Tiao Qiang. It provides theoretical guidance for the industrial production and quality control of Fo Tiao Qiang.

SCL—Segmentation–Classification combined Loss for surface defect detection

Deep learning for surface defect detection has recently received increased attention in relation to quality control of industrial products. In this paper, we present a combined loss function called Segmentation–Classification combined Loss (SCL). It exploits the binary information (normal/anomalous sample) implicit in the segmentation masks to reduce false positives and false negatives in surface defect detection tasks. We evaluate the method on images in three different domains: defects in electrical commutators, defects in a weakly labeled synthetic dataset, and defects of glass bottles.Our combined loss function outperforms the state of the art in the Kolektor (electrical commutators) dataset and significantly improves the classical Dice segmentation loss function in terms of both average precision, false positives, and false negatives. Moreover, the combined loss function introduced in this paper can be applied in a straightforward manner to any loss-based segmentation model. Finally, in this work we introduce and publish a new dataset for the still poorly explored task of surface defect detection of glass bottles.

Empirical findings for the usage of 5G as a basis for real time locating systems (RTLS) in the automotive industry

The digitalization of processes and integration of a digital twin are key factors for a successful system design to realize optimization and control in industrial production. The usage of positioning data is essential to achieve these goal - knowing where tools, products, and parts are in real-time. It enables processes to become intelligent, automated, and logged throughout production. Current radio real-time-locating-systems (RTLS) in manufacturing are often using Ultra-Wideband (UWB) solutions requiring individual infrastructure resulting in high costs. 5G technology is turning its focus from mobile-communication to become a globally standardized industry solution - now including high accuracy positioning. Development shows that the infrastructure already used for communication can potentially be utilized for positioning. This contribution aims to determine the industrial maturity of 5G positioning by performing guided empirical expert interviews based on a structured literature review with 28 experts. Topics such as state-of-the-art, comparison to UWB-RTLS and safety are discussed. Results show that industrial interest in 5G positioning is high and centimeter-level accuracies are pursued. However, practical tests show hardware is in early development, and tests are only performed in controlled environments. Concluding, 5G positioning shows great potential - but industrial pilots are required to validate characteristics in complex scenarios.

Collaborative Apportionment Noise-Based Soft Sensor Framework

Recently, feature extraction based soft sensor techniques have developed rapidly in the control, optimization, and detection processes of industrial production. However, the raw data obtained from the complex industrial processes are often contaminated by noise, which significantly impacts the results of soft sensor models. We introduce the collaborative apportionment noise (CAN) method based on the density peaks clustering (DPC) theory, based on which, we have proposed a CAN-based soft sensor framework (CAN-SSF) and designed an example model called the CAN-based convolutional neural networks (CAN-CNN) model for industry data prediction. In the CAN method, we determined the magnitude and direction of the noise by the bias degree and deviation of the data. And then the noise is collaboratively apportioned by the credibility degree of the data. Finally, to further explore the feasibility of the CAN method, we added a hyperparameter called reduction degree and conducted two groups of independent experiments for the example model CAN-CNN. The results have shown that the adaptability and stability of the CAN method are higher than the traditional wavelet transform denoising (WT) and denoising autoencoders (DAE). In addition, the prediction performance of the proposed CAN-SSF is better than the traditional CNN and Stacked autoencoders (SAE) models to solve the industrial soft sensor problems.