A high-accuracy Stewart–lift platform based on a programmable logic controller – comparative case studies

Programmable logic controllers (PLC) as the backbone of industrial automation adapt to each subsequent wave of technology. This is still true today, almost six decades after the first Modicon 084 programmable controller developed for General Motors. Innovations such as artificial intelligence, cloud and edge computing, IIoT, 5G networks, augmented and virtual reality are penetrating all possible areas of industry, and PLC controllers are no exception. Equipped with a modern functional arsenal, these compact industrial computer systems become the basic building block of intelligent automation, digitalization and Industry 4.0, enabling dynamic regulation and management of industrial processes based on data via real-time feedback. The global market for PLC systems is estimated at US$ 12.2 billion in 2024. It is expected to exceed 15 billion dollars by 2029. PLC controllers, which traditionally serve as the basis of process and discrete industrial automation, are becoming more widespread today adopting the principles of Industry 4.0 in various sectors. The impact on the increase in the need for them is the increased application of industrial robots in the automotive, electrical engineering and other industries. The industrial robotics sector is among the leading contributors to development of PLC systems and is becoming a key driver of the further development of the programmable controller market, and forecasts are that this trend will continue with the development of increasingly widespread robotization in factories around the world. According to the data of the IFR (International Federation of Robotics) from 2024. almost 4.3 million robots are already in operation.

Most of automation systems in industry are based on Programmable Logical Controllers (PLCs) due to its reliability and immunity to industrial environments. Besides, PLCs's flexibility and capabilities have allowed human to automate a huge number of industrial processes. In this paper a new multilevel graphical and modular approach is proposed for programming industrial PLCss. Traditional programming drawbacks, such as impossibility of exchange code or the programmer dependence, are well-known. For solve these problems, the paradigm proposed in this paper exploits several object oriented features, improving the re-use of code, develops objects to be used in a plug and play way understandable by so many developers. Hence this framework reduce the PLC brand and programmer dependence.

This article explores the widespread application and importance of the Programmable Logic Controller (PLC) in industry. PLC, as an industrial controller designed specifically for industrial environments, occupies an important position in the field of industrial automation control due to its advantages of being less susceptible to interference, high reliability, easy programming, fast installation, and small size. With the rapid development of PLC technology, great progress has been made in the development of technology, hardware, and software, resulting in increasingly powerful functionalities and significantly enhanced system development and compatibility. This paper mainly analyzes the design ideas and applications of PLC in life and industry in detail, aiming to research PLC and find more scenes in industry fields in which PLC can participate. PLC has a wide range of applications and significant importance in industry. The continuous progress and innovation of its technology will bring more opportunities and challenges to the field of industrial automation control. In the future, with the deepening development of advanced manufacturing models such as Industry 4.0 and intelligent manufacturing, PLC technology is expected to play a greater role in more fields and promote industrial automation to a higher level.

The rapid growth of robotics and automation, especially during the last few years, its current positive impact and future projections for impact on the United States economy are very promising. This rapid growth of robotic automation in all sectors of industry will require an enormous number of technically sound specialists with the skills in industrial robotics and automation to maintain and monitor existing robots, enhance development of future technologies, and educate users on implementation and applications. It is critical, therefore, that educational institutions adequately respond to this high demand for robotics specialists by developing and offering appropriate courses geared towards professional certification in robotics and automation. In order to effectively teach concepts of industrial robotics, the curriculum needs to be supported by the hands on activities utilizing industrial robots or providing training on robotic simulation software. Nowadays, there is no robotic simulation software available to the academic institution at no cost which limits educational opportunities. As part of the NSF sponsored project, team of faculty members and students from Michigan Tech are developing new, open source RobotRun robotic simulation software which will be available at no cost for adaptation by the other institutions. This will allow current concepts related to industrial robotics to be taught even in locations without access to current robotics hardware. In addition, to teach emerging concepts of robotics, automation, and controls, authors present the design and development the state-of-the-art robotic workcell consisting of 3 FANUC industrial robots equipped with robotic vision system, programmable logic controller, a conveyer and various sensors. The workcell enables the development and programing of various industry-oriented scenerious and therefore provide students with the opportunity of gaining skills that are relevant to current industry needs.

Artificial Intelligence (AI) is revolutionizing industrial process automation by introducing intelligent decision-making and adaptive control to traditionally deterministic systems. In the petrochemical and oil & gas industries where safety, efficiency, and reliability are paramount, AI technologies such as machine learning, deep learning, and digital twins enhance plant operations through predictive maintenance, process optimization, and asset integrity management. Despite challenges in certification, data quality, and cybersecurity, AI continues to evolve as an indispensable enabler of smart and self-optimizing industrial plants. This research examines the integration of AI within programmable logic controllers (PLCs), distributed control systems (DCS) and supervisory control and data acquisition (SCADA) frameworks, the improvements it brings in efficiency, energy management, and maintenance scheduling as well as examines the real-world implementations from major automation vendors such as Honeywell, Emerson, Yokogawa and Siemens.

A Programmable Logic Controller (PLC) is a very common industrial control system device used to control output devices based on data received (and processed) from input devices. Given the central role that PLCs play in deployed industrial control systems, it has been a preferred target of ICS attackers. A quick search in the ICS-CERT repository reveals that out of a total of 589 advisories, more than 80 target PLCs. Stuxnet attack, considered the most famous reported incident on ICS, targeted mainly PLCs. Most of the PLC reported incidents are rooted in the fact that the PLC being accessed in an unauthorized way. In this paper, we investigate the PLC access control problem. We discuss several access control models but we focus mainly on the commonly adopted password-based access control. We show how such passwordbased mechanism can be compromised in a realistic scenario as well as the list the attacks that can be derived as a consequence. This paper details a set of vulnerabilities targeting recent versions of PLCs (2016) which have not been reported in the literature.

The characteristics and applications of the system for welding machines based on SCM , based on PLC control system and PC-based industrial control system was introduced. It has certain significance to the design of welding machine control system.

The integration of Deep Learning (DL), MATLAB, and Advanced Computer- Aided Design (CAD) in the root cause analysis of prognostic errors in Programmable Logic Controller (PLC) systems represents a significant advancement in industrial automation and reliability. This research explores the synergistic application of these technologies to diagnose, predict, and mitigate failures in PLC systems, which are critical for controlling automated processes in various industries. By employing DL algorithms, the study enhances predictive maintenance capabilities, allowing for early detection of anomalies and reducing downtime. MATLAB is utilized as the central platform for data processing, algorithm development, and simulation, providing a versatile environment for integrating DL models with real-time data from PLCs. Advanced CAD tools are employed to model and visualize the physical systems controlled by the PLCs, offering a comprehensive view that bridges the gap between digital analysis and physical implementation. The research methodology includes data collection from PLC systems, DL model training and validation, MATLAB-based simulations, and CAD modelling. The findings demonstrate improved accuracy in identifying the root causes of PLC prognostic errors, leading to more efficient maintenance strategies and enhanced system reliability. This paper concludes that the integration of DL, MATLAB, and CAD provides a powerful approach for advancing predictive maintenance in industrial settings, ultimately contributing to greater operational efficiency and cost savings.

The purpose of this study is to provide students with a 21st century training that can be easily applied to industrial automation training, both online and in person, and that goes beyond traditional learning methods. It involves creating and programming a training package that is compatible with the Ministry of National Education (MEB) curriculum, using the project-based learning (PBL) method and a curriculum that focuses on skills acquisition. Two different brands of programmable logic controllers (PLC) have been integrated into the manufactured training set so that the set can be used to conduct various PLC trainings. In the training set, product separation can be carried out using the electro-pneumatic system with a turntable and two conveyor belts. Motor controls, sensor applications, electro-pneumatics, touch panel and various PLC controls can also be carried out with the training set. The set focuses on the grafcet diagram method and can show how to program the same scenarios in different PLC models. By using PLC software components in the training set, students also get the opportunity to develop and experience their own unique SCADA (supervisory control and Data Acquisition) software with visual programming. This study also includes a sample curriculum prepared for PBL. In this way, all on-set training can be done using the PBL method and students get a 21st century experience. They also get the opportunity to improve their skills. PBL is an innovative and process-oriented learning method and is supported by the Ministry of Education (MoE). The prepared curriculum also includes the learning plan and measurement and assessment scales (rubrics). We anticipate that this package will be effective and useful in providing students with 21st century job skills and abilities in the field of industrial automation engineering, both online and face-to-face.

For the past several decades, the programmable logic controller has been one of the major driving forces in industrial automation. Affected by COVID19 since spring 2020, teaching a Programmable Logic Controller (PLC) course has become a difficult task for both faculty and students since it involves many labs. Access to labs has been limited by campus closures and capacity limits to maintain social distancing. To overcome this problem, we developed a Virtual PLC Lab simulation software, which consists of four major components – a Soft PLC – the Runtime Engine, a Ladder Diagram Program Editor and Monitor, a Data/Tag Editor and Monitor, and an I/O Device Simulator, aimed at getting a working prototype together in the shortest period of time possible to allow us to continue to offer this course in the coming semesters. The software was designed to have a graphic user interface (GUI) similar in look and feel to those of the Allen Bradley ControlLogix PLC software RSLogix 5000 that were installed in our lab and the Lab Console (I/O Devices) Simulator was designed to mimic our lab I/O device console. Object Oriented Programming and formal model-based design methods were adopted to keep the maximum possible level of data abstraction. This software was experimentally used in our 2020 and 2021 online PLC classes and student performance and brief statistics were satisfactory and presented herein.

A stability test chamber simulates specific environmental conditions and tests a product or material in the manufacturing stage. The tested product or material is then analyzed about its shelf-life estimation related to the state and durability of the product for a certain period. The main parameter that must control accurately is temperature. Programmable Logic Controller (PLC) as an industrial computer control system has been widely used. In this paper, the temperature control system was designed based on PLC and supervisory control and data acquisition (SCADA). The PLC and SCADA would indirectly control the heater. The PLC was feeded from the temperature sensor for real-time temperature inside the test chamber. Received temperature value, compared to the temperature set point. The validation and verification of controlled temperature inside the chamber were also investigated. The system was designed on a miniaturized chamber using commercial PLC and SCADA, Stepper motor, slide regulator, heater, and the temperature sensor PT100. The temperature test point for validation and verification was performed at 35 °C, 45 °C, and 55 °C. The result showed that The PT100 successfully had an excellent response to the temperature test point. The correction value for temperature is as high as 0.6 °C with a deviation of 1 %.

Water level control and pressure control are implemented in many at several industrial processing such as water dam, petrochemical processing plant, pharmacy and food processing plant, overhead tank, waste processing plant, electricity plant, etc. This study analyses a simulation and a needed components for automatically water level control system implementation using programmable logic controller (PLC). The water level control using PLC is designed to control the water level and prevent waste the water from a water tank. PLC is one of devices of automated controller which mostly used. Use of PLCs in industries are indispensable to control parameters which required high precision. In this research studies water level control system using PLC as primary controller and human machine interface (HMI) as remote controller that could visualize state of a system work (plant) in real time on computer screen and could gather field data as well. Main device for this research is Omron PLC CP2E type and touchscreen HMI Omron. At the prototype is used a water tank and a water container (to be one with the water resource), and in the HMI is showed the pages of home, control panel, and plant. From the result of the diagram ladder and the HMI design are got the system run well. The application from this research could be learning media in the system control laboratory for the subject of industrial control system and the others, related to it.

This paper proposes a machine vision module for PLCs (Programmable Logic Controllers). PLC is the industrial controller most widely used in factory automation system. However most of the machine vision systems are based on PC (Personal Computer). The machine vision system embedded in PLC is required to reduce the cost and improve the convenience of implementation. In this paper, we newly propose a machine vision module based on PLC. The image processing libraries are implemented and integrated with the PLC programming tool. In order to interface the libraries with ladder programming, the ladder instruction set was also designed for each vision library. By use of the developed system, PLC users can implement vision systems easily by ladder programming. The developed system was applied to sample inspection system to verify the performance. The experimental results show that the proposed system can reduce the cost of installing as well as increase the ease-of-implementation.

The problem of constructing a HIL simulation stand for researching a technological process using programmable logic controller (PLC) "Baget" is described in this article. Issues of modeling technological processes are currently extremely relevant, since modeling is a mandatory stage in the automated process control systems development. An adequate model of the technological process allows debugging and verification of automated process control system algorithms without using real equipment, reducing financial costs and the probability of emergency situations. The HIL modeling method involves partial use of real equipment as part of the model. The inclusion of standard components of the original object in the model does not require detailed mathematical model and at the same time provides a more complete correspondence to the original. Due to using a computer from the original object, the stand software operates under conditions close to the real technological process, which improves the quality of the simulation results. The HIL modeling stand includes the following components: control computer of automated process control system; programmable logic controller PLC "Baget"; simulation computer. The stand for the basic element of an automated process control system allows to speed up the process of prototyping and debugging even in the case of complex systems, because it will be easier to build the entire system from correctly functioning elements. Another advantage of this approach is that the stand is not tied to a specific type of technological process or to a narrow area of production — the stand allows the use of ready-made models, the development of new models, and the inclusion of various function libraries. The simplicity of the stand design with this approach is combined with a full range of functionality. By connecting additional software, you can create more complicated and detaild model. This stand is also capable of serving both for debugging PLC algorithms and as a simulator for maintenance personnel of a real control object, because the stand operator can simulate failures and errors of standard equipment, emergency situations at the control object. Using C and JavaScript programming languages for development ensures portability and ease of expanding the capabilities of the modeling software. The development of complex systems based on HIL modeling allows saving resources and effectively solving assigned problems, therefore the proposed approach to building stands will be in demand in the process of developing an automated process control system based on the PLC "Baget".

Logic synthesis is an important step in process design and automation. Electronics witnessed tremendous improvements in the reliability of automatically designed circuits with reduced lead time with the application of logic synthesis in circuit design. Industrial process automation systems using hydraulic and pneumatic circuits need logic synthesis to obtain proper sequence of process operations. Deterministic approaches have been used for decades to aid in logic synthesis. These approaches are limited by the volume of data that could be handled because of phenomena like exponential explosion. This paper presents an approach based on hybrid intelligence for logic synthesis for industrial automation systems using pneumatic sequential circuits. The proposed logic synthesis system starts with the sequence of operations as its input and generates the truth table required for the pneumatic circuit for performing the given set of operations. The proposed system hybridizes rule based logic programming and genetic algorithms and is capable of solving considerably difficult problems through an evolutionary strategy. Case studies are presented to demonstrate the capability of the proposed approach for logic design for pneumatics based industrial automation.