Factory Equipment Research Articles

Corrosion protection of steel equipment operating in an aggressive environment (on the example of technological equipment in sugar factories)

Corrosion protection of steel equipment operating in an aggressive environment (on the example of technological equipment in sugar factories)

Circuit Design for Predictive Maintenance

Industry 4.0 has become a driver for the entire manufacturing industry. Smart systems have enabled 30% productivity increases and predictive maintenance has been demonstrated to provide a 50% reduction in machine downtime. So far, the solution has been based on data analytics which has resulted in a proliferation of sensing technologies and infrastructure for data acquisition, transmission and processing. At the core of factory operation and automation are circuits that control and power factory equipment, innovative circuit design has the potential to address many system integration challenges. We present a new circuit design approach based on circuit level artificial intelligence solutions, integrated within control and calibration functional blocks during circuit design, improving the predictability and adaptability of each component for predictive maintenance. This approach is envisioned to encourage the development of new EDA tools such as automatic digital shadow generation and product lifecycle models, that will help identification of circuit parameters that adequately define the operating conditions for dynamic prediction and fault detection. Integration of a supplementary artificial intelligence block within the control loop is considered for capturing nonlinearities and gain/bandwidth constraints of the main controller and identifying changes in the operating conditions beyond the response of the controller. System integration topics are discussed regarding integration within OPC Unified Architecture and predictive maintenance interfaces,providing real-time updates to the digital shadow that help maintain an accurate, virtual replica model of the physical system.

Начало научно-организаторской деятельности Савелия Вольфовича (Владимировича) Вольфсона

The author aims to draw the attention of historians to the personality of Savely V. Volfson, and also to reconstruct the history of his first major scientific project. At the same time, she occasionally calls Savely Volfovich, who for many remains still Savely Vladimirovich, just SV. (The fact that in the middle of his life he returned to the patronymic received at birth was an additional incentive to this). Savely Vladimirovich was born in the family of one of the first engineers of the Stalingrad Tractor Plant. 4 days before the breakthrough of the German units to the Volga, along with part of the factory equipment, the family was loaded into a train sent to Siberia - to Rubtsovsk. After graduating from the Faculty of History and Philology (IFF) of Tomsk University (TSU) in 1955, SV worked in Novosibirsk at a school, in the district committee of the Komsomol and, finally, as an assistant at the Department of General History of the Pedagogical Institute. Already an active lecturer, he wanted to study the history of the United States, on which (as well as the USSR) the entire post-war world politics was tied. In 1962 he entered the postgraduate course at TSU to the assistant professor Grigortsevich. Becoming in 1966 an assistant to “his” department of modern and contemporary history, after defending his dissertation in 1967, Volfson was an assistant professor of this department since 1968, and only in 2021 transferred to the department of oriental studies. The teaching work did not leave time to continue the active development of the previous scientific topic. But most importantly, it seems, it undermined the SV's interest in it. Possessing by nature an amazing intuition, he acutely felt the pulse of the times, which suddenly made itself felt by the “youth revolution” that broke out in the Western countries. The first major student riots occurred in the United States in the fall of 1964, and already in June 1968, under the leadership of Volfson, a graduate work on the history of the American student movement was defended. In early 1968, with the support of the Tomsk Regional Committee of the Komsomol and the Committee of Youth Organizations of the USSR (KMO), Volfson and his colleague associate professor N.S. Cherkasov held a student scientific conference dedicated to the riots of foreign students. Meanwhile, in April 1968, a ministerial order appeared on the opening of the Problematic Research Laboratory of History, Archaeology and Ethnography of Siberia (PNIL INPP) at Tomsk University. To speed up the implementation of the order, the dean of the IFF, Professor Mogilnitsky, sent Volfson to Moscow. SV negotiated with the State Committee on Science and Technology not only to speed up the opening of the laboratory. After his talks at the KMO about the organization of the study of the history of the international youth movement at TSU, the KMO turned to the State Committee for Science with a corresponding request. And in the summer of 1969 TSU received the first 4 additional rates for the creation of one more sector in the PNIL INPP. Thus, in the fall of 1969, for the first time in a Soviet university an “academic” structure appeared which engaged in foreign- general, world - history, albeit only as part of a laboratory for the study of the history of Siberia.

Factory Equipment Optimization Solution based on Data Science

日本は，2020年10月に2050年カーボンニュートラルを目指すことを宣言した。カーボンニュートラルの実現は，使用エネルギーの低炭素化と徹底した省エネルギーの実行が必須である。その中で日本国内のエネルギー消費で約4割と高い比率を占める製造業の省エネルギー対策の必要性は，今後ますます高まっていくと考えられる。日本の省エネルギー技術は世界の中でも高い水準であり，製造業ですでに取り組んでいる設備の高効率化や廃熱回収技術の採用などにより，ハード面での省エネルギー対策はなされており，現状以上の省エネルギーは策が尽きたと考える企業が多い。また，製造業における最重要課題は，品質の向上・確保であり，品質を優先したオペレーションが省エネルギーの障壁となっている。つまり，オペレーションにおいては，品質を確保するためには多少のエネルギーロスは仕方が無いと言った風潮がある。そこで本報では設備からの取得データや外気温湿度等の外部データを活用し，品質を確保しながら省エネルギーオペレーションをサポートする仏国METRON社が開発したエネルギー管理プラットフォームについて紹介する。システムの概要，提供するサービスメニューに加え，コロンビアの大手製紙会社において年間4.5％の蒸気消費量，年間22％の化学薬品使用料を削減した事例について紹介する。

A Study on the PLC-Based Pre-Validation Simulation Design Method for Smart Factory

Cyber-physical systems (CPSs) are considered as the main technology in smart factories. In a CPS environment, it is important to monitor the operational processes to detect abnormal conditions and respond to them via real-time comparisons between real-world and virtual models implementing identical real-world factories. The main purpose here is detecting abnormalities in an actual factory and finding quick responses through a simulation model reflecting these abnormalities. This study demonstrates modeling of the key components, such as process equipment and production results, placement of virtualized equipment in virtual factories, synchronization of data between actual and virtual facilities to design digital twins corresponding to the physical assets, and confirming their utilities.

DWT-LSTM-Based Fault Diagnosis of Rolling Bearings with Multi-Sensors

Bearings are widely used in many steam turbine generator sets and other large rotating equipment. With the rapid development of contemporary industry, there is a great number of rotating equipment in various large factories, such as nuclear power plants. As the core component of rotating machinery, the failure of rolling bearings may lead to serious accidents during the industrial production operation. In order to accurately diagnose the fault status of rolling bearings, a novel long short-term memory (LSTM) model with discrete wavelet transformation (DWT) for multi-sensor fault diagnosis is proposed in this paper. The main purpose of this paper is to use the DWT-LSTM model to diagnose the health of rolling bearings. Firstly, the DWT is used to obtain detailed fault information in both different frequency and time scales. Then, the LSTM network is employed to characterize the long-term dependencies hidden in the time series of the fault information. The proposed DWT-LSTM method makes full use of the advantages of feature extraction based on expert experience and deep network learning to discover complex patterns from a large amount of data. Finally, the feasibility and efficiency of the proposed method are illustrated by comparison with the existing methods.

Entire system of wages and rewards to increase productivity in factory

One of the latest tests to see whether one day or an industrial organization is functioning successfully or less successfully is the product units of that system. This assessment is not directly about the physical equipment, technology, or products of Japanese factories or about capital expenditures, and the stage of the companies being studied. However, there is a close relationship between social organization and the special attention currently paid to the question of productivity, apparently considering some special consideration of the problems which increase the effort to increase productivity in the large Japanese factories. Productivity - of course - is a relative measure, and the standard commonly used by Japanese executives is the output and cost of American factory production. In general, Japanese executives do not flatter their company when it comes to making such comparisons. Estimates need to be rough, and it can be difficult to mislead them to try to get an exact value. However, in comparing their factories to American factories producing the same goods, very few Japanese executives would speculate on a measure of productivity.

Research on the Biofilm Formation of Staphylococcus aureus after Cold Stress.

Staphylococcus aureus is a common food pathogen and has a strong tolerance to environmental stress. Here, the biofilm formation of S. aureus strains after cold stress for 24 weeks were investigated. It was found that the biofilm formation of S. aureus CICC 21600, CICC 22942, W1, W3, and C1 cells was enhanced after cold stress for 20 weeks. What is more, the mRNA levels of the clfA, icaA, icaB, icaC or icaD genes in these strains were increased for >2-fold. The increased gene transcription levels were consistent with the increase in the polysaccharide content in the biofilm matrix of these S. aureus strains after cold stress. Meanwhile, hydrophobicity and the adhesion proteins also played a role in the formation of biofilms. The biofilm of S. aureus cells can be effectively degraded by snailase and proteinase K (125 µg/mL + 20 µg/mL) mixture. In summary, S. aureus frozen at −20 °C for 12 to 20 weeks is still a potential hazard. Food factory equipment should be cleaned in a timely manner to avoid outbreaks of foodborne pathogenic bacteria due to contamination.

SCIENTIFIC DISCUSSION ON NORMATIVE ISSUES OF OCCUPATIONAL HEALTH, SANITARY AND HYGIENIC EPIDEMIOLOGICAL DEMANDS IN PHARMACY ESTABLISHMENTS DURING COVID DISEASES IN THE REPUBLIC OF GEORGIA

Protecting safe working conditions involves the use of ineffective and reliable means of preventing industrial injuries and occupational diseases, technologies, equipment and others. It is natural that the fields, technological processes, etc., are characterized by their specifics and the safety rules should be different for them. In pharmacies, laboratories, training and scientific research laboratories, warehouses, production equipment are subject to daily cleaning. Cabinets in storage rooms should be cleaned as needed, but at least once a week. Wet cleaning of the pharmacy, laboratory/ factory (floor and equipment) before starting work. Only dry cleaning of laboratory / production using disinfectants is not allowed. Waste and rubbish should be collected in special containers with a moving lid and should be removed at least once a day. Hand-washed sinks, toilets and garbage containers should be cleaned, rinsed and disinfected daily. Personnel are required to follow the rules of personal hygiene and industrial sanitation, to carry out the relevant personnel to perform food, smoking, as well as storage of food, tobacco and personal medicines in pharmacies, training and scientific research laboratories and departures. Pharmaceutical establishments do not comply with the hygienic norms of the internal and external environment, physical, chemical and biological factors of the labor process. The facility also does not take into account psychosocial factors related to safety (stress, communication, post-traumatic stress, etc.); Most pharmaceutical establishments (50-60%) do not have a fire board with appropriate equipment, evacuation exit and scheme. Also has no person responsible for the matter; Disobsibility and specialist protection/separation facility prior to pandemic were minimal (increased by 99%) during pandemic; The state should create an appropriate legislative and institutional framework; We think this will help transform the existing department into an effective labor inspectorate. The possibility will be created of the institutional capacity of its independence and efficiency, and the law will also provide guarantees for the individual independence of inspectors. Also, the bill should directly refer to the Labor Inspectorate as the body responsible for law enforcement.

Implementation of MQTT protocol based network architecture for smart factory

The core concept of smart manufacturing is based on digitization to construct intelligent production and management in the manufacturing process. By digitizing the production process and connecting all levels from product design to service, the purpose of improving manufacturing efficiency, reducing production cost, enhancing product quality, and optimizing user experience can be achieved. To digitize the manufacturing process, IoT technology will have to be introduced into the manufacturing process to collect and analyze process information. However, one of the most important problems in building the industrial IoT (IIoT) environment is that different industrial network protocols are used for different equipment in factories. Therefore, the information in the manufacturing process may not be easily exchanged and obtained. To solve the above problem, a smart factory network architecture based on MQTT (MQ Telemetry Transport), IoT communication protocol, is proposed in this study, to construct a heterogeneous interface communication bridge between the machine tool, embedded device Raspberry Pi, and website. Finally, the system architecture is implemented and imported into the factory, and a smart manufacturing information management system is developed. The edge computing module is set up beside a three-axis machine tool, and a human-machine interface is built for the user controlling and monitoring. Users can also monitor the system through the dynamically updating website at any time and any place. The function of real-time gesture recognition based on image technology is developed and built on the edge computing module. The gesture recognition results can be transmitted to the machine controller through MQTT, and the machine will execute the corresponding action according to different gestures to achieve human-robot collaboration. The MQTT transmission architecture developed here is validated by the given edge computing application. It can serve as the basis for the construction of the IIoT environment, assist the traditional manufacturing industry to prepare for digitization, and accelerate the practice of smart manufacturing.

Mobile mecavision: automatic plant monitoring system as a precision agriculture solution in plant factories

Precision agriculture (PA) is an approach in farming systems based on information and technology to enhance agricultural production. PA is applied in plant factories to produce high-quality vegetables in a controlled environment by implementing an automatic crop growth monitoring system. Optimization of the observation process carried out with computer system techniques used in the monitoring process and assessment of the plant condition. Individual observation of cultivated plants requires a monitoring system and numerous equipment. Therefore, a monitoring system equipped with a mobile mechanism is needed to support the monitoring process of crops individually by a single observer. The objective of this study was to design and implement an automatic plant monitoring system based on mobile mechanisms and computer vision using simple equipment in plant factories. The Mobile Mecavision, a monitoring system consists of a mobility system and an image acquisition system controlled by Raspberry Pi. The components are A4988, NEMA 17, and Logitech C270 HD Webcam. The evaluation for system performance carried out using the extreme point shift system and t-test. The aspect of image functionality evaluated using the Structural Similarity Measure test and the result was obtained an image similarity value of 89% to 92% with a 90% level of confidence. The result of the performance test on the mobility aspect obtained that the system shifted numerically but not statistically. The overall performance of the system indicated that the monitoring system could be applied to monitor the crop growth in plant factories.

A privacy-preserving resource trading scheme for Cloud Manufacturing with edge-PLCs in IIoT

With the development of industrial Internet of things (IIoT), Cloud Manufacturing has been increasingly popular to the manufacturing industry. It can provide resource-sharing and on-demand manufacturing services as well as automatic collaborative manufacturing with the help of edge Programmable Logic Controllers (edge-PLCs). In such a system, there is a high risk of exposing user privacy and trading secret, due to exposure of sensitive transaction data to public servers. We propose a new privacy-preserving resource-trading scheme (PRTS), which leverages the concept of homomorphic cryptography and asymmetric searchable encryption, to simultaneously protect the privacy of the equipment factory and parts factories, while supporting best matching results in terms of parts parameters and price. Furthermore, a random forest-based method is applied to identify abnormal participants. The experimental results and security analysis show that the proposed scheme is accurate, effective, and secure, even under Off-line Keyword Guessing Attacks. Finally, encrypted data can resist analysis from mainstream machine learning techniques.

Overview of Physical and Chemical Factors in Fertilizer Companies

Introduction: Fertilizer companies are companies that use large amounts of chemicals, natural gas as raw equipment and assist in the production process, as well as the use of factory equipment with high temperatures and pressures, making companies with high levels of risk. The purpose of this study is to determine the general picture of physical and chemical factors in the work environment and the risks that can occur to workers and companies in fertilizer companies in Indonesia. Methods: This research was conducted using descriptive methods, the object observed in this study is the physical and chemical factors that exist in fertilizer companies. Results : Lighting intensity in all areas of the operational departments of fertilizer companies in Indonesia is only 12%, which is in accordance with the Threshold Limitation Value (TLV). Intensity of noise in the area of the company, as much as 17% is above the Threshold Limitation Value (TLV). The level of dust in this fertilizer company is 33% of the area that exceeds the Threshold Limitation Value (TLV). These three things can increase the risk to health, even increase the intelligence of the workers themselves. In addition to the risks to the workers, these three things can also benefit a company's productivity. Conclusion: All areas of fertilizer companies have risks originating from physical and chemical factors. So it needs to be carried out appropriate control in order to reduce the risks that can occur both for workers and companies.Keywords : dust, ferilizer plant, lighting, noise

RECLAIM: Toward a New Era of Refurbishment and Remanufacturing of Industrial Equipment.

Refurbishment and remanufacturing are the industrial processes whereby used products or parts that constitute the product are restored. Remanufacturing is the process of restoring the functionality of the product or a part of it to “as-new” quality, whereas refurbishment is the process of restoring the product itself or part of it to “like-new” quality, without being as thorough as remanufacturing. Within this context, the EU-funded project RECLAIM presents a new idea on refurbishment and remanufacturing based on big data analytics, machine learning, predictive analytics, and optimization models using deep learning techniques and digital twin models with the aim of enabling the stakeholders to make informed decisions about whether to remanufacture, upgrade, or repair heavy machinery that is toward its end-of-life. The RECLAIM project additionally provides novel strategies and technologies that enable the reuse of industrial equipment in old, renewed, and new factories, with the goal of saving valuable resources by recycling equipment and using them in a different application, instead of discarding them after use. For instance, RECLAIM provides a simulation engine using digital twin in order to predict maintenance needs and potential faults of large industrial equipment. This simulation engine keeps the virtual twins available to store all available information during the lifetime of a machine, such as maintenance operations, and this information can be used to perform an economic estimation of the machine's refurbishment costs. The RECLAIM project envisages developing new technologies and strategies aligned with the circular economy and in support of a new model for the management of large industrial equipment that approaches the end of its design life. This model aims to reduce substantially the opportunity cost of retaining strategies (both moneywise and resourcewise) by allowing relatively old equipment that faces the prospect of decommissioning to reclaim its functionalities and role in the overall production system.

Multipath TCP Meets Transfer Learning: A Novel Edge-Based Learning for Industrial IoT

We consider a fifth-generation (5G)-empowered future Industrial IoT (IIoT) networking problem where IIoT machines are capable of communicating and sharing their data networking knowledge gained (and experiences) with other neighboring devices/tools. For such an IIoT setting, deep-learning (DL)-based communication protocols are known to be highly efficient but having a computationally complex training procedure in terms of both time/space and volume of data sets. One solution for such training is to be completed offline for each equipment and machines of IIoT before deployment. A better approach would be to replicate the model from the expert existing machine and implant it into new machines. Such training for the transfer of knowledge can be done by manufacturers using high computational power, even for large-scale DL models. After sufficient training and the desired level of accuracy, the trained machines can be deployed in the smart factory equipment to perform life-long collaborative learning. We design a novel distributed transfer learning (TL) framework to maximize multipath communication networking performance for Industry 4.0 environment. To conduct seamless sharing of knowledge gain by the multipath TCP (MPTCP) agents and tackle retraining issues of DL-based approaches, we investigate TL for MPTCP from the IIoT networking perspective. With relevant insights from transfer and collaborative learning, we develop a distributed TL-MPTCP framework to accelerate the learning efficiency and enhance the performance of newly deployed machines. Our approach is validated with numerical and emulated NS-3 experiments in comparison with the state-of-the-art schemes.

A Review on SECS/GEM: A Machine-to-Machine (M2M) Communication Protocol for Industry 4.0

Industry 4.0 has imminently emerged as the fourth industrial revolution. It garners emphasis primarily on the interaction between factory equipment and machines involved in entire value-chain activities for boosting efficiency and production with limited human intervention. The M2M communication protocols have gained significant prominence amidst sage minds in recent years, particularly in the manufacturing industries. Several M2M communication protocols have been developed for the industry, such as SECS/GEM, OPC UA, DDS, and MQTT. Among these protocols, SECS/GEM is a semiconductor’s equipment interface protocol for equipment-to-host data communications. It is not a modern, but decades-long protocol, and has been again brought to the fore by Industry 4.0. Thereupon, it was imperative to review amenability of SECS/GEM protocol in the context of adaptation of features depicted by industry 4.0, and limelight plethora of shortcomings and limitations. In this paper, comparisons of prominent features and limitations of the aforementioned M2M communication protocols in general and review of the SECS/GEM protocol in particular, have been made. Findings include deficiencies in security, point to point communication, discovery mechanism, fixed message format, interoperability, extendibility, and manual integration.

Organizational and economic processes of Ukrainian film production in the 1920’s

The article examines the formation of the material and technical base of Ukrainian film production based on the wide range of little-known publications in the Ukrainian and Russian periodicals of the 1922-1930s. The influence of the technical equipment of film factories on the quality indicator of film production in the 1920s is analyzed. The All-Ukrainian Photo and Film Administration did not receive the necessary state funding for the development of film production and had to independently seek the possibility of such funding. Initially, the main investments were directed to the development of the Odessa and partly Yalta film factories. In the second half of the 1920s, it was decided to build the largest cinema factory in the USSR in Kyiv, and therefore all funds were directed to this construction. However, after the transition to the production of sound films, the Kyiv Film Factory turned out to be completely unadapted to such processes. The article also discusses the negative consequences associated with the uneven distribution of funding for the development of three film factories.

Analysis of business interruption risk factors of Chinese enterprises during flood disasters based on social network analysis

Global warming has led to frequent flood disasters, which pose great uncertainty and risk to the normal operation of enterprises. To identify the key risk factors of business interruption for Chinese enterprises because of flood disasters, this study proposes an analysis framework based on social network analysis. We consider 248 cases of enterprises affected by floods reported since 2001 in China as the dataset, and quantitatively analyze the key risk factors and important factor combinations of enterprise business interruption because of floods through multiple indicators. These include the core-periphery, node centrality, and note pairings in social network analysis. The analysis results show that “factory building damage,” “production equipment damage,” and “power supply interruption” are the key risk factors of business interruption during flood disasters. The three most likely combinations of risk factors to occur simultaneously are “production equipment damage and factory building damage,” “production equipment damage and raw material damage,” and “production equipment damage and power supply interruption.”

Characterization of Switching Transients in Low Voltage Power Systems of Tea Factories in Sri Lanka

Voltage transients caused by various motors and electrical equipment of tea factories in Sri Lanka have been observed and analyzed. While reporting the major components of transients, this work extends it aspires to investigate the risk of having faults in a three-phase induction motor by monitoring and analyzing the transient voltage waveforms during the starting period. Therefore, common mode transient investigations have been followed. Transient voltage signals have been obtained from high end test setup and altogether 588 waveforms have been analyzed in both the time and frequency domains. In DOL and Star-Delta starting, highest transient amplitude of 688.2 V and 572.1 V have been observed respectively. Highest transient amplitude of 976.4 V and 980.5 V were observed in DOL and Star-Delta switching respectively. Withering and rolling sections dominates over other stages, generating high amplitude transients in average, reflecting same endangerment in energy calculations as presented in voltage integral. DOL starting transients carries fast rise times as 14 ns and in Star-Delta it is 28 ns. In order to assist with the exegesis of these data, transient parameters like rise time, duration, highest peak, etc.… have also been presented in statistical basis.

The challenges of solar hybrid PVT systems in the food processing industry

This paper assesses the challenges of alternative solar systems based on hybrid PVT collectors coupled with an absorption chiller (AbCH, single-stage NH3-H2O) in the food-processing industry, from the technical, economic and environmental points of view. This type of industry is usually characterised by a constant cooling demand throughout the year, hot water demand for production processes and electricity consumption for factory equipment and lighting. To the authors’ knowledge, this work constitutes one of the first studies to address the integration of PVT-water collectors with a single-stage NH3-H2O AbCH for industrial applications. Two alternative PVT-water collectors are analysed, covered and uncovered. A biomass boiler is proposed as an auxiliary heater. To compare the proposed solar solutions, a vegetable and fruit processing and canning factory is considered as a representative case study. Hourly transient simulations considering the real factory demands and real weather data are performed over a year. Two main challenges are found for the solar systems based on the covered PVT collectors, an AbCH and a biomass boiler: the overlapping of the cooling and hot water demands of the food-processing industry, and the high hot water temperatures required. If, alternatively, the current electrical chillers are retained, the system based on uncovered PVT collectors has a reasonable-to-attractive payback time (14.3 years). When the potential environmental benefit is quantified (through carbon pricing), all the proposed solar systems become economically attractive, i.e., with positive total cost savings at the end of the system lifetime. Still, the high cost of PVT collectors, along with the considerably lower price of fuels compared to electricity, hinder the potential of systems that displace fossil fuels.