Automated Process Control Research Articles

Improving Process Control Through Decision Tree-Based Pattern Recognition

This paper explores the integration of decision tree classifiers in the assessment of machining process stability using control charts. The inherent variability in manufacturing processes requires a robust system for the early detection and correction of disturbances, which has traditionally relied on operators’ experience. Using decision trees, this study presents an automated approach to pattern recognition on control charts that outperforms the accuracy of human operators and neural networks. Experimental research conducted on two datasets from surface finishing processes demonstrates that decision trees can achieve perfect classification under optimal parameters. The results suggest that decision trees offer a transparent and effective tool for quality control, capable of reducing human error, improving decision making, and fostering greater confidence among company employees. These results open up new possibilities for the automation and continuous improvement of machining process control. The contribution of this research to Industry 4.0 is to enable the real-time, data-driven monitoring of machining process stability through decision tree-based pattern recognition, which improves predictive maintenance and quality control. It supports the transition to intelligent manufacturing, where process anomalies are detected and resolved dynamically, reducing downtime and increasing productivity.

A Well‐Advanced High‐Throughput Test System for Electrocatalytic Screening Applications Under Industrial Relevant Conditions – A Perspective to Accelerate Electrolysis Research and Development

ABSTRACTElectrolysis is a dynamic research area in which both mature and new promising processes, such as alkaline water electrolysis and electrochemical CO2 reduction, are under enormous development pressure due to their high relevance for the energy sector. High‐throughput (HT) technologies are efficient screening platforms that can accelerate research activities and significantly shorten development times. Over the past 25 years, various HT platforms have found their way into electrochemical research. These typically have one or more major disadvantages: they are characterized by abstract experimental conditions, designed for a specific application or process, or generate insufficiently comparable data. In this publication, we present a newly developed HT test system that enables the parallel operation of 16 electrochemical bench‐scale flow cells under industry‐relevant test conditions. The specially developed modular flow cell can be operated variably in the fully automated system and allows research into the most common applications in electrochemistry for many different processes with a focus on all relevant variants of water electrolysis and electrochemical CO2 reduction. Both the HT system and the developed flow cell are designed to accelerate the generation of reliably reproducible data with high comparability in order to strengthen scientific exchange. The fully automated process control, online analysis and programmable feedback loops of the HT test system provide great potential for the design of experiment strategies. The implementation of Design of Experiment strategies will maximize the testing efficiency of this innovative research system.

A study of automatic output power control methods for stand-alone photovoltaic power generation systems

Abstract The conventional power generation system’s output power automatic control structure is generally unidirectional, and the control coverage is small, leading to the increase in the random error obtained in the final test. Therefore, the design and research of this article are proposed. According to the current control demand, the generation system shall be stabilized first, and the power compensation shall be calculated. The multi-step mode shall be adopted to improve the control coverage and design the multi-step automatic control structure. According to this, it is constructed, and the automatic control processing is realized using jump balance. The test results show that compared with the traditional DFIG-DRWT system power output automatic control method and the traditional three-phase asynchronous generation system power output automatic control method, the random error finally obtained by the designed independent photovoltaic power station output power automatic control method is relatively effective. This indicates that the application effect and coverage of the designed power automatic control method are high, that controllability has been significantly improved, and that control flexibility has also been strengthened.

Preface

With the rapid development of global science and technology and industry, intelligence, automation and informationization have become an irreversible trend in all walks of life. This trend not only promotes the innovation and application of technology, but also puts forward unprecedented challenges and demands for precision measurement and control technology. It is against this backdrop that the 2024 4th International Conference on Measurement Control and Instrumentation (MCAI 2024) was convened, bringing together leading experts, scholars, and researchers from across the globe to share their latest insights and groundbreaking achievements. Held in Guangzhou, China from August 23rd to 25th, 2024, this prestigious event served as a pivotal platform for interdisciplinary discussions and collaborations. The MCAI conference series has a rich history of fostering intellectual exchange and promoting scientific advancements in the field. Building upon the success of its previous conferences, MCAI 2024 was created to expand the horizons of knowledge by addressing a broad spectrum of topics, including but not limited to Testing Instrument Design, Intelligent Instrumentation, Precision Manufacturing and Measurement, Welding Technology and Equipment, Electrical Control Technology, Automatic Control System, Information Detection and Processing Technology, etc. The conference attracted a diverse array of participants from around the world, reflecting the multidisciplinary nature of modern-day research in these domains and the internationalization of the conference. Moreover, a variety of programs were established, including opening ceremony, keynote speech, oral presentation, poster presentation, academic discussion, etc. Experts and scholars from different research areas including Professor Zhen Li of South China Agricultural University, China, Vice Chairman of the Professional Committee of Agricultural Mechanization and Electrification of China Agricultural Engineering Society and Member of the Youth Working Committee of China Agricultural Machinery Society, Professor Xue Li of Jinan University, China, and Professor Shifeng Guo of Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, China shared their research experiences and professional insights with us on specific topics. The oral presentations characterized a large number of academic contributions from scholars in their respective research fields around the world. Moreover, the poster sessions allowed the attendees to further showcase their researches and view others’ findings, exchanging ideas and thoughts with each other. List of Committee Member is available in this Pdf.

Biofuser: a multi-source data fusion platform for fusing the data of fermentation process devices.

In the past decade, the progress of traditional bioprocess optimization technique has lagged far behind the rapid development of synthetic biology, which has hindered the industrialization process of synthetic biology achievements. Recently, more and more advanced equipment and sensors have been applied for bioprocess online inspection to improve the understanding and optimization efficiency of the process. This has resulted in large amounts of process data from various sources with different communication protocols and data formats, requiring the development of techniques for integration and fusion of these heterogeneous data. Here we describe a multi-source fusion platform (Biofuser) that is designed to collect and process multi-source heterogeneous data. Biofuser integrates various data to a unique format that facilitates data visualization, further analysis, model construction, and automatic process control. Moreover, Biofuser also provides additional APIs that support machine learning or deep learning using the integrated data. We illustrate the application of Biofuser with a case study on riboflavin fermentation process development, demonstrating its ability in device faulty identification, critical process factor identification, and bioprocess prediction. Biofuser has the potential to significantly enhance the development of fermentation optimization techniques and is expected to become an important infrastructure for artificial intelligent integration into bioprocess optimization, thereby promoting the development of intelligent biomanufacturing.

Development of a model of the process of development of manufacturing defects in automation means

In automated process control systems, automation equipment (sensors, converters, amplifiers, etc.) with technical defects arising during their manufacture, which are one of the main causes of failures, is widely used. The paper establishes the possibility of using the laws of nonequilibrium thermodynamics as the basis for determining the relationship between the controlled parameters of automation equipment and the parameters of the displayed medium, which made it possible to build a deterministic model of the development of production defects and, ultimately, determine the directions for changing and adjusting the technological processes of production of automation equipment. A method has been developed for implementing a guaranteed forecast of changes in the parameters of automation equipment based on solving the evolution equation using optimal filtering algorithms, which is the subject of research. The purpose of the work is to improve the quality and reliability of automation equipment by improving the monitoring of defects arising in the production of instruments, functional units and sensors of automation equipment. The article solves the following problems: analysis of existing approaches to the problem of manufacturing defects and methods for their detection and setting a research task; modeling of the process of development of production defects causing changes in the technical condition of automation equipment; development of a decision-making method based on guaranteed prediction of the technical state of automation equipment. The methodology of work is based on the methods of thermodynamic description of the kinetics of processes (when developing a model of the process of development of production defects that cause a change in technical condition) and methods of assessment and forecasting based on optimal filtering algorithms (when developing a decision-making method based on guaranteed foresight of technical condition). The results of the work include a model of the process of development of manufacturing defects that cause a change in the technical condition of automation equipment, and a decision-making method based on a guaranteed forecast of the technical condition of automation equipment. Conclusions. The paper establishes the possibility of using the laws of nonequilibrium thermodynamics to determine the relationship between the controlled parameters of automation equipment and the displayed medium, and to build a deterministic thermodynamic model of the development of production defects. Disclosed is an equation of evolution of technical state of automation equipment based on a deterministic kinetic model of processes occurring in a multicomponent medium, and an observation model which takes into account errors caused by instability of external effects and measurement errors. Disclosed is a method of implementing a guaranteed forecast of change in parameters of automation equipment based on solving the evolution equation using optimal filtering algorithms, which are used to solve estimation and prediction problems.

Fuzzy automatic control of the irrigation process for the IoT-based smart farming systems

This paper is dedicated to the development and research of the advanced IoT-based fuzzy control system of the irrigation process for smart farming complexes of various types. The proposed automatic control system makes it possible to attain sufficiently high quality indicators of the soil moisture and pH control, which significantly improve the overall efficiency of irrigation processes and, as a result, the processes of growing various plants. In particular, more accurate control of soil moisture and pH allows improving soil microbial activity, optimizing nutrient uptake, increasing water utilization efficiency within the cultivated plants, which directly contribute to increased crop yields and sustainable resource management in agriculture. The designed system is created based on the principles of (a) hierarchical two-level IoT-based control, (b) simple and reliable two-channel fuzzy logic control with high performance and accuracy, as well as (c) easy customization and adaptability for various smart farming complexes. To evaluate the effectiveness of the proposed advanced system, the simulation experiments for automatic control of an irrigation process using the developed fuzzy controllers are carried out in this study at given optimal parameters (soil moisture and pH level) of growing conditions for two different crops: tomato and beet. The analysis of the obtained results of computer simulation shows that the designed system has higher efficiency and quality indicators compared to existing analogs when used for two different crops with significantly different optimal parameters of growing conditions.

Metoda pomiaru parametrów kamer termowizyjnych za pomocą zautomatyzowanego stanowiska pomiarowego

To achieve precise and repeatable measurements of thermal camera’s parameters, it is essential to eliminate human error. For this purpose, an automated test bench has been developed that allows fully automatic, semi-automatic and manual control of the measurement process. The designed stand supports remote control via Ethernet interface or USB connection. The developed software enables control, data recording and parameter determination of thermal cameras. The test bench ensures high quality and reliability of thermal measurements, enabling controlled examination of camera characteristics with minimal operator involvement.

Understanding self-control as a problem of regulatory scope.

Although the focus of research for decades, there is a surprising lack of consensus on what is (and what is not) self-control. We review some of the most prominent theoretical models of self-control, including those that highlight conflicts between smaller-sooner versus larger-later rewards, "hot" emotions versus "cool" cognitions, and efficient automatic versus resource-intensive controlled processes. After discussing some of their shortcomings, we propose an alternative approach based on tenets of construal level theory (Trope et al., 2021) that integrates these disparate models while also providing novel insights. Specifically, we model self-control as a problem of regulatory scope-the range of considerations one accounts for in any decision or behavior. Self-control conflicts occur when the pursuit of specific local opportunities threatens the ability to address motivational priorities that span a broader array of time, places, individuals, and possibilities. Whereas a more contractive consideration of relevant concerns may prompt indulgence in temptation, a more expansive consideration of concerns should not only help people identify the self-control conflict but also successfully resolve it. We review empirical evidence that supports this new framework and discuss implications and new directions. This regulatory framework not only clarifies what is and what is not self-control but also provides new insights that can be leveraged to enhance self-control in all its various forms. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Implementation of Quality 4.0 framework in the electronics sector using ANP and QFD methodologies

PurposeQuality 4.0 is essential to the Industry 4.0 framework, notably in the electronics sector. It evaluates product quality in real-time using automatic process controls, quality tools and procedures. The implementation of Quality 4.0 criteria in the electronics industry is the subject of this study’s investigation and analysis. In this study, nine Customer Requirements (CRs) and 18 Design Requirements (DRs) have been defined to adopt Quality 4.0, aiming to increase yield while reducing defects. This study has developed a Quality 4.0 framework for effective implementation, incorporating the People, Process and Technology categories.Design/methodology/approachMany CRs and DRs of Quality 4.0 exhibit interdependencies. The Analytic Network Process (ANP) considers interdependencies among the criteria at various levels. Quality Function Deployment (QFD) can capture the customer’s voice, which is particularly important in Quality 4.0. Therefore, in this research, we use an integrated ANP-QFD methodology for prioritizing DRs based on the customers' needs and preferences, ultimately leading to better product and service development.FindingsAccording to the research findings, the most critical consumer criteria for Quality 4.0 in the electronics sector are automatic systems, connectivity, compliance and leadership. The Intelligent Internet of Things (IIOTs) has emerged as the most significant design requirement that enables effective control in production. It is observed that robotics process automation and a workforce aligned with Quality 4.0 also play crucial roles.Originality/valueExisting literature does not include studies on identifying CRs and DRs for implementing Quality 4.0 in the electronics industry. To address this gap, we propose a framework to integrate real-time quality measures into the Industry 4.0 context, thereby facilitating the implementation of Quality 4.0 in the electronics industry. This study can provide valuable insights for industry practitioners to implement Quality 4.0 effectively in their organizations.

Automated process control in electric arc furnaces in the aspect of digital twin technology

An approach to managing the main modes of smelting steel in heavy-duty electric arc furnaces (EAF) using digital twin technology was defined and formulated. It was noted, that the existing power regulators do not have the function of balancing the effective power of phases and, accordingly, electric arcs because they are focused on working with a certain average value of the signal. It is proposed to use the analysis of dynamic characteristics based on instantaneous values of input parameters instead of operating ones, as it’s usually implemented in most devices. This allows us to obtain more accurate data on the arc state and reduce the amount of time and computing power required to obtain a result and form recommendations. Based on the data obtained as a result of long - term observations of the heavy-duty EAF-135 operation, the relationship of the constant component of the arc voltage (CCAV) with the metal oxidation is shown. An example of its use as a criterion for controlling the melting oxidative stage is given. This reduces the consumption of electrochemical sensors for each melting in the case of serial metal production. Based on the recorded data, it is possible to timely determine the unevenness of the arc power release between the furnace electrodes and issue recommendations on gas burners operation regulating to equalize the rate of scrap melting at electrodes with less power release. The authors propose the idea of using digital twins based on models of the active power distribution across the melting bath zones and dependence of metal oxidation on oxygen blowing for monitoring and controlling the electric mode and the oxygen blast mode at the oxidative stage of the melting process. Simplified schemes of these twins are given.

Internal combustion engine acoustic diagnostics

Introduction. To ensure stable performance of transport and technological machines, constant monitoring of their technical condition is necessary. Timely diagnosis is difficult to carry out when working in remote regions, as well as when transporting goods over long distances due to the lack of closely located maintenance centers.Materials and methods. One of the solutions to the above problem is the use of a diagnostic method based on sound parameters. In particular, this method is applicable to power plants. Its advantage is the ability to quickly assess the condition of the engine mechanisms and systems on site using a portable device (without the use of large-sized and low-mobility equipment) by non-destructive testing. Thus, the research and implementation of the acoustic diagnostic method is promising and in demand today. One of the most important areas for improving power plants today is the automation of control processes for their operation based on the use of electronics and microprocessor systems. With a positive effect on the efficiency of the engine, these complex systems expand the range of its potential malfunctions. The purpose of this study was to evaluate the fundamental possibility of determining and comparing the acoustic parameters of an engine with and without violations of the operating mode in the event of failures in electronic control systems of its operation. As an example, the Ford Focus passenger car was chosen as the object of the study. A malfunction in the electronic ignition module was used as a test fault. The obtained spectral patterns of the sound radiation of the internal combustion engine (with and without violations of the operating mode) enable to determine the nature of the engine malfunction by sound parameters.Results. A frequency range at which it is possible to identify the spectral pattern of an engine with impaired operation and an engine without impaired operation was obtained. This range was 6,000-6,500 Hz, since in this segment the sound level reaches more than 40 dB.Discussions and conclusions. The conducted experiment is the initial stage of a large-scale experimental study, the result of which will serve as a starting point for the introduction of the acoustic method into the process of diagnosing electronic control systems for internal combustion engines.

Escherichia coli Fermentation and GFP Production by using the Eppendorf BioFlo®120 Bioprocess Control Station

This article is an examination of a bioprocess experiment involving the cultivation of a GFP-expressing strain of Escherichia coli using the BioFlo®120 bioprocess control station. The BioFlo 120 is a bench-scale bioreactor/fermentor system perfectly suited for all levels of research and development. The study highlights the capabilities of the BioFlo®120 in supporting high-density growth and protein production. There is two key parameters were monitored to assess the progress of the fermentation process, the optical density (OD600) to estimate cell density and relative fluorescence units (RFU) to quantify the green fluorescent protein production. Additionally, it discusses the Auto Culture modes, which enable automatic process control of common microbial and mammalian cultures, making it accessible for users with varying levels of experience. The application note also delves into the differences between batch, fed-batch, and continuous fermentation processes, with a focus on E. coli fermentation at bench scale. It covers various aspects such as biomass and nutrient concentration analysis methods, including growth rate, productivity, yield, and process costs. This comprehensive approach provides valuable insights for bioprocess engineers in selecting the most suitable fermentation method for their specific requirements. This article explores the positive outcome for bioprocess engineers and researchers who aim to optimize bio-production systems for industrial or research purposes.

Monitoring power consumption with automated process control strategy and adjustment considering price sensitivity and multi-source collaboration

In context of demand side management, the real-time pricing is an effective method to achieve power peak-clipping and valley-filling and maintain power balance between supply and demand. However, in reality, users’ power consumption fluctuation may lead to collapse of power systems and waste of resources. In this paper, based on the cosine function for demand response program, a novel two-stage monitoring and adjustment strategy is proposed to monitor power consumption, which considers the changes of users’ sensitivity to the electricity price and power generation with multi-source collaboration in detail. When the forecast power consumption exceeds the upper or lower bound, we design a price adjustment strategy with automated process control to better guide users to modify their electricity consumption behavior in the first stage, and a generation adjustment strategy with multi-source collaboration is offered to meet the adjusted consumption demand and low-carbon development in the second stage. Simulation results indicate that the proposed two-stage strategy not only has great performance of peak-clipping and valley-filling, but also is conductive to social economy and environment. The carbon emission decreases by 7.5%. The social welfare and supplier’s profit increase by 2.42% and 31.38% after monitoring and adjustment, respectively. Compared with the linear, quadratic and logarithmic strategies, the proposed two-stage strategy is better to encourage users to consume electricity appropriately.

Automating execution of surveillance procedures for NPP main control rooms

ABSTRACT For the past 30 years, progress in the automation of control processes in the nuclear industry has been much slower compared to other industries. In the same timeframe, other complex industrial and/or high-risk processes (e.g., aviation) have been revolutionized by the exponential increase of technology capability in computing and information systems. The reason for the relatively slow trickling of technology advancements in the nuclear field is multi-faceted: i) resistance to change from a traditionally proven solution (partially due to very specific regulation requirements); ii) the cost to adopt Computerized Procedure Systems for existing NPPs, without having a quantified and proven safety benefit; iii) relatively low number of new NPPs being built following the Chernobyl and Fukushima disasters; iv) possible negative impact on the human factors aspect. After a short introduction to automation in another high-risk industry (aviation), this paper focuses on the practical approach required for automating Surveillance Procedures, and at the same time taking into consideration the human factors impact of this approach.

Optimization of the penetration testing process in automated process control systems using machine learning algorithms

Optimization of the penetration testing process in automated process control systems using machine learning algorithms

Mathematical modeling of the flat ingot casting process or solving automation problems

Aluminum alloys are widely used in the production of aircraft due to their strength, lightness, corrosion resistance, and necessary electrical conductivity. At the same time, aluminum ingots used in further processing of the space industry must be of high quality. Technological problems and defects arise when temperature, speed, and other technological parameters of casting are not observed, or when modes change. At the same time, foundry processes are partially automated; the human factor significantly affects product quality and work safety. Therefore, automation of these complex processes using mathematical models to predict casting parameters is an urgent task. The goal of the work is to create mathematical models available for use in automated process control systems (APCS), as well as for the development of a digital twin. The work presents simplified formulas for modeling the temperature distribution of an aluminum ingot during the casting process, cooling the metal when moving along a metal path, and test calculations of the temperature distribution inside the ingot when the ingot reaches a fixed length. The results of this work can be used to improve the efficiency and accuracy of controlling the process of casting aluminum ingots, to eliminate emergency situations.

WEB APPLICATION «ELECTRONIC READER’S DIARY» BY AGILE TECHNOLOGY

The article relate to the development of an reader’s electronic diary by AGILE technology. It is needed for reader competency of primary school students. The current students were born in a new information environment. They master information and software faster than adults (for example, gadgets, tablet PC, mobile devices, etc.) The disadvantage is this information environment is reluctance to read. One of the stimulation tools to reading is electronic reader’s diary technology applied in the educational process. The regular reader’s diary is a report about books read. The aim of the reader’s diary is skills reflection and development of the critical analysis skills formation. The project software is designed for primary school students (age 7-10 years). Independent reading skills form at primary school age. It improves cognitive interests of school students, enhances knowledge, and is the formation of a harmoniously developed personality. The electronic reader’s diary stimulates the knowledge interests and consolidates the reading material by AGILE technology and additional interactivity with the school students. The research relates to the architecture of the developed solution, in particular, the issue of the «automated process control system of education system resources» integration. Also, the article contains the map of the developed graphical user interface screen and describing main electronic reader’s diary screens. This research will be intended to boost cognitive and creative activity of students.

RESEARCH AND CONSTRUCTION OF A MATHEMATICAL MODEL USING DISCRETE PROGRAMMING METHODS FOR THE MIXING AND MELTING OF COPPER CONCENTRATES

This paper describes the construction of an optimal schedule for a metallurgical workshop using discrete programming, and in particular, the method of branches and boundaries. In this regard, a heuristic approach to solving this problem is proposed, which includes: building an initial graph that satisfies the constraints of the optimization problem, as well as sequential search optimization of the initial graph according to a given criterion. To test the effectiveness of using the task of forming a melting schedule as part of the operational control subsystem in the converter department, experimental studies were conducted. Considering that the creation of the automated process control system of the copper plant provides for the introduction of systems using modern software and hardware controls, cargo flow control, and an automated conversion process control system, the efficiency of using optimal melting schedules will significantly increase.

In‐mold rheology and automated process control for injection molding of recycled polypropylene

AbstractManufacturing plastic parts with secondary feedstocks has risen to the forefront of importance in recent years. However, the variation in molecular weight and rheology of secondary feedstock can lead to inconsistent part quality. This work evaluates the effectiveness of a novel closed‐loop adaptive process control system that adjusts nozzle pressure in response to in‐mold pressure data. Five different recycled polypropylene blends, with a broad distribution of flow properties, were evaluated to determine the effectiveness of the control system at reducing processing variation. The experimental results show that the process control strategy reduced the variation within the mold, as seen by in‐mold pressure curves and calculated in‐mold viscosity values. Additionally, the parameters that control the automated process adjustments were investigated, showing the importance of optimization. The analysis of the correlation between in‐mold rheology and mechanical properties showed a slight variation in the mechanical properties and parts weight with a coefficient of variation of under 5%. Overall, the results demonstrate the ability of pressure‐controlled molding and automated viscosity adjustment to reduce the variability when molding a secondary feedstock.Highlights Pressure‐controlled injection molding of recycled polypropylene. Automated closed‐loop adaptive process control methodology. Methodology resulted in a reduction in pressure variation during molding. Changes in mechanical properties and in‐mold viscosity were investigated. Results show the potential of pressure‐controlled molding at reducing variation.