Industrial Automation Systems Research Articles

An engineering methodology to assess the economic viability of edge-cloud automation systems in manufacturing

The migration of industrial automation systems (IASs) to an edge-cloud hosted on factory premises can reduce the operation costs of a manufacturing line and increase its flexibility thanks to computation scalability and use of cloud-native operation concepts. However, the unclear assessment of costs of an edge-cloud automation system (ECAS) is a significant concern for manufacturing experts, which disincentives its adoption. An ECAS is expected to generate different costs than a traditional IAS, which depends on the requirements of the automation functions hosted in the edge-cloud. Because of this, methods to evaluate various realization concepts of an ECAS concerning their economic viability are required to support its engineering. In this paper, we provide a methodology that helps practitioners to define design specifications for an ECAS and assess their life-cycle costs (LCCs). To provide a robust and transparent LCCs assessment, we leverage the Monte Carlo method, which is a well-affirmed technique to address costs uncertainties. To do so, a cost model has been developed and implemented in a discrete-event simulator to calculate upfront and running costs of an ECAS. The application of the methodology is shown through an exemplar case study and its results are discussed. The presented work helps practitioners to evaluate whether an ECAS is economically viable for a manufacturing scenario, thus increasing the acceptance for this technology and fostering the transition towards flexible and smart manufacturing systems.

Medium-Voltage Seven-Level Multiplexed Converter for AC Applications

After several decades of technological evolution, power electronics applications have become extremely important for electric/hybrid propulsion systems, smart grids, renewable energy systems, energy saving, and bulk energy storage, besides the typical applications in industrial automation and high-efficiency energy systems. In all these applications, a power conversion system with high efficiency and power density is required without sacrificing the system's power quality. The paper describes the specific characteristics and the scalar modulation strategy of a new multi-level multiplexed inverter topology for medium-voltage AC applications. The proposed power converter configuration is intended for high-power applications aiming to reduce the active device's voltage rating and losses exhibiting a resulting low switching frequency of the power switches. The proposed modulation strategy aims to reduce the computational burden and simplify the implementation process, which are at the basis of any possible industrial adoption. Simulation results and full Hardware-In-the-Loop verification support the analysis. The Hardware-In-the-Loop assessment has enabled the development of a suitable modulation strategy, and the testing of the power converter is a safe environment.

Analysis of the automated production management systems market in Russia

This article is devoted to the problem of industrial automation and corporate information systems used in this field. Consumer surveys were conducted on the parameters that characterize information systems. Foreign and domestic information systems were considered, and their comparative analysis was carried out. A number of conclusions on the use of corporate information systems in production management are formulated.

Literature Review and Model Proposal on the Machine Life Cycle in Industrial Automation from Different Perspectives

The life cycle model of machines as idealistic subsequent phases is often used to analyze industrial automation systems. Depending on their focus, literature holds a number of different state of the art approaches for the machine life cycle with various phases. However, the consideration is mainly from the perspective of machine manufacturers. Often, the life cycle of the product, that is manufactured with the corresponding machine or the life cycle of the components installed in the machine are thoroughly considered. The development, production and operation of these assets can also be divided into corresponding phases. The aim of this paper is to provide an overview of existing approaches of machine life cycles based on a structured literature review. This will also address the differences in the life cycle phases for the typical stakeholders of the industrial value chain. Since the life cycles of the individual stakeholders of the industrial value chain are coupled, a chronological classification of the individual life cycle models based on the product creation process is presented one above the other.

Quality Analysis Framework based on Complexity for Change Management Using Intelligent Digital Twin

Software attributes analysis in industrial automation systems due to the higher proportion of using software-defined systems is highly significant. The requirement of higher flexibility, adaptivity, quality, less cost, and time to market as main classes of manufacturing attributes in dynamic and heterogeneous environments induce a large amount of complexity, which directly deteriorates the external software quality attributes. Complexity is a comprehension of quality management factor that influences the quality attributes of an asset such as testability, reusability, reliability, and maintainability. In order to manage the continuous requirement of software-defined systems’ updating efficiently, an automatic method for estimating these quality attributes is required. This paper proposes a novel approach for quality attributes analysis with the factor of complexity estimation. The proposed approach is realized in a framework that exploits the operational simulation capability of the intelligent Digital Twin concept to decrease the cost of untoward consequences of complexity increase on software external attributes by using operational data. It uses the simulated asset to predict how complexity due to applying new changes would impact the software quality attributes. The quality analysis process contains the intelligence process of monitoring the complexity metrics vector and quality attributes vector, the analysis of training models, the prediction of attributes, and the evaluation of measurements to enhance the quality attributes in advance. A comprehensive evaluation using the example of a Robotino 3 Premium from Festo, an autonomous mobile robot, is used to show the consequences of changes in software quality attributes for validation of the proposed framework.

Validation of Industrial Automation Systems Using a Timed Model of System Requirements

Validation of industrial automation systems is the process of checking that commissioner requirements are successfully implemented. Formal approaches are needed when the considered system is critical. The method presented in this article relies on a model-based approach that exploits the compactness and graphical representation of time-interpreted Petri nets, which adds input–output interpretation to transitions/places and embeds time information. These nets are here used with multiple-server semantic to allow effective modeling of typical automation system requirements. The key idea of the system validation approach is to compare the observed behavior of the automation system with the expected behavior, as generated by updating online the model of system requirements using a state estimation algorithm. Also, an off-line procedure is provided to evaluate the evolutions admitted by the model but not observed. Both procedures yield useful data to the validation engineer, allowing to speed up the validation process. Technological issues due to the synchronous nature of controllers and the implications of their programming are considered.

Predicting the Force Map of an ERT-Based Tactile Sensor Using Simulation and Deep Networks

Electrical resistance tomography (ERT) can be used to create large-scale soft tactile sensors that are flexible and robust. Good performance requires a fast and accurate mapping from the sensor’s sequential voltage measurements to the distribution of force across its surface. However, particularly with multiple contacts, this task is challenging for both previously developed approaches: physics-based modeling and end-to-end data-driven learning. Some promising results were recently achieved using sim-to-real transfer learning, but estimating multiple contact locations and accurate contact forces remains difficult because simulations tend to be less accurate with a high number of contact locations and/or high force. This paper introduces a modular hybrid method that combines simulation data synthesized from an electromechanical finite element model with real measurements collected from a new ERT-based tactile sensor. We use about 290 000 simulated and 90000 real measurements to train two deep neural networks: the first (Transfer-Net) captures the inevitable gap between simulation and reality, and the second (Recon-Net) reconstructs contact forces from voltage measurements. The number of contacts, contact locations, force magnitudes, and contact diameters are evaluated for a manually collected multi-contact dataset of 150 measurements. Our modular pipeline’s results outperform predictions by both a physics-based model and end-to-end learning. Note to Practitioners–ERT-based tactile sensors use high-speed voltage measurements from electrodes distributed over a piezoresistive area to output a force map that shows where contact is occurring, and how strong each contact is. Such sensors hold promise for giving robots and other devices a sense of touch over large surfaces with low hardware complexity. However, the software problem of converting voltages to an accurate force map has not previously been solved well, requiring either extensive model calibration or extensive contact data collection. This paper suggests a hybrid approach where a straightforward physics model simulates multi-contact experiments that are too costly to acquire in reality and a practical automatic indentation setup acquires real but geometrically limited multi-contact data. Although the number of real measurements required to learn the discrepancy between the sensor and the model is still large due to the inherent inverse nature of ERT-based tactile sensors, our combination of simulation and deep networks achieves better performance than either physical modeling or learning alone. This approach can advance practical large-area tactile sensing for industrial automation systems where multiple contacts occur, such as in manufacturing and assistive robotics. It could also likely be adapted to other nonlinear inverse problems.

Trainerprogrammable Logic Controller Dilengkapi Human Machine Interface (HMI) Guna Penguatan Praktek Otomasi Industri

The learning system in vocational education is more directed to practical learning. Therefore, learning media is needed that can make students learn interactively and independently. The research aims to create an industrial automation system learning media as a learning medium for industrial automation courses. The learning media is in the form of a programmable logic controller (PLC) trainer equipped with sensors and combined with a human machine interface (HMI). PLC trainer is made because PLC devices are widely used in industrial automation systems. The PLC component has not been equipped with a display, therefore in this study PLC is combined with HMI. HMI is an interface that connects machines with humans. The Outsel PLC was chosen because the price is very affordable and developed by domestic developers. Trainers are made in a compact form, and easy to carry anywhere. Several simulations were carried out to test the function of the trainer. The test results of the PLC trainer show that the PLC trainer is able to control the process according to the logic programmed, and the HMI is able to display the ongoing process, thereby increasing the interaction between machines and humans.

ECOPOOL+++: Developing a sustainable outdoor heated swimming pool

The University of Algarve, in consortium with “Cristal Construções – Materiais e Obras de Construção Civil”, “Itelmatis Control Systems” and “Itecons – Instituto de Investigação e Desenvolvimento Tecnológico para a Construção, Energia, Ambiente e Sustentabilidade”, is developing a new concept of outdoor heated sustainable swimming pool, having a higher energy efficiency and lower environmental footprint. The main objective is to minimise energy and water consumptions, while assuring a comfortable temperature for the user, extending the utilization of the pool in the Algarve region, from the summer months, to at least 8 months of the year. In order to do it, different systems will be tested, including solar thermal and photovoltaic panels, inverted underfloor heating, heat accumulator exchanger with phase change materials and energy dissipating pipes. An innovative thermal insulation system will be included in the interior of the pool tank, together with a new system for the covering of the water plane. All these systems will be monitored and controlled by an industrial automation system that will communicate, via a programmable logic controller, using industry standard communication protocols, with a SMART platform, that will be in charge of the global operation's optimisation. This platform will support an intelligent and predictive control and monitoring module, that controls the automation system to maximize the energy usage of the renewable sources, while assuring the user preferences. One of the main outputs of this project is the construction of a smaller scale prototype of a swimming pool, with the characteristics mentioned above, in order to test and validate the proposed developments.

Supervisory Control and Data Acquisition (SCADA) Systems for Industrial Automation and Control Systems in Industry 4.0

Abstract In order to respond to the new production models specific to the fourth industrial revolution, a new paradigm of integrated industrial automation and control systems in industry 4.0 management is needed with new web, collaborative and intelligent applications to supervise production processes. The present work represents an analysis of the solutions for the management of production processes resulting from the combination of new technologies and applications conforming to the Industry 4.0 paradigms, in conjunction with SCADA technical solutions for the world of production. The solution that comes with this work is based on the synergy between two concepts, that of cyber-physical SCADA systems and human-centered production, which at first sight may seem antithetical, but which in reality are complementary to each other and actually represent a waysuitable for Industry 4.0. The research method was represented by the systematic analysis of the asynergy of the two concepts found in the specialized web of science literature, as well as corroborated with the real situation in industry 4.0.which is foreshadowed from day to day.

Research on Equipment Management Decision Model based on Semantic Analysis

In recent years, the industrial automation of cigarette enterprises has made great progress, and the underlying data acquisition, centralized control and condition monitoring systems have been established. The management has also established a large number of application systems. There are a large number of equipment data resources in these industrial automation systems and application systems, but incremental data value mining is difficult to really solve the problem. The exploration of big data and machine learning has gradually encountered bottlenecks and ceilings, Lack of integration of domain knowledge, it is difficult to mine high-value application scenarios. From the point of view of "semantic analysis" and "equipment management", it is necessary to establish a unified method of data collection and application, which is the basis of effective data collection and management. From the perspective of "semantic analysis" and "equipment management", it is necessary to establish a unified method of data collection and application.

Virtual Engineering and Commissioning to Support the Lifecycle of a Manufacturing Assembly System

Prior to the physical build of the industrial automation system, some challenges arise, such as processes’ cycle times calculations, ergonomics and safety evaluation, and the integration of separate machines to the complete production shops. This, in turn, requires reconfiguring the processes and component parameters. As a result, the lifecycle of the system development is prolonged, and the potential for erroneous performance increases. In modern digital manufacturing environments, virtual engineering (VE) and virtual commissioning (VC) serve as effective tools to tackle the aforementioned problems and their consequences. The virtual models developed for VE and VC not only assist system developers in the physical build stage but also in the following stages of the system lifecycle by providing a common virtual model, a digital twin (DT), of the manufacturing processes and the product. This developed model should possess the ability to simulate the system behaviour, e.g., the mechanics, kinematics, speed and acceleration profiles. Three stakeholders are involved in the development process: the machine builder, system integrator and end user. The current work focuses on the virtual engineering approach to support the entire lifecycle of a manufacturing system from the machine builder, system integrator and end user perspectives. For this purpose, it puts forward a systematic methodology of implementing VC and VE using a toolset developed by the Automation Systems Group at the University of Warwick within an industrial project. The suggested methodology is illustrated in a case study where a digital twin of a physical station was modelled, developed and tested in parallel with the physical machine development and build. Finally, the benefits and limitations are highlighted based on the gained outcomes and the implemented activities.

Residuals-based fault diagnosis of industrial automation systems using timed and untimed Interpreted Petri nets

The problem of detecting and isolating a fault using a discrete event model has received a lot of attention over the last two decades. Indeed, industrial automated systems can be usually modelled by a discrete event system. The problem is particularly significant if a fault-free model is used. Recently, residuals, well-known in continuous time systems context, have been proposed to obtain set of candidate faults from real time observations for discrete event system also. They have been obtained using finite state automata. In this paper, inspired by these works, residuals are formulated using Petri net models, both timed and un-timed ones. The computation of residuals for net models requires some efforts to update and predict the state, especially in timed models, but it returns to be highly efficient and scalable thanks to the local state representation and intrinsic distributed nature of the these models. A practical example, consisting of a plant simulated by using a 3D environment interfaced to a Programmable Logic Controller to simulate/emulate the closed-loop behaviour, is used to illustrate the results of the paper.

On the Hardware–Software Integration in Cryptographic Accelerators for Industrial IoT

Industrial Internet of Things (IIoT) applies IoT technologies on industrial automation systems with the aims of providing remote sensing, remote control, self-organization and self-maintenance. Since IIoT systems often constitute a critical infrastructure, cybersecurity risks have rapidly increased over the last years. To address cybersecurity requirements, we need to deploy cryptographic processing components which are particularly efficient, considering also that many IIoT systems have real-time constraints. Hardware acceleration can greatly improve the efficiency of cryptographic functions, but the speed-up could be jeopardized by a bad hardware–software integration, which is an aspect often underrated by the literature. Considering that modern IIoT devices often mount an operating system to fulfill their complex tasks, software influence on efficiency cannot be neglected. In this paper, we develop a software–hardware integration of various cryptographic accelerators with a Linux operating system, and we test its performance with two typical IIoT reference applications. We also discuss our design choices and the lessons learned during the development process.

Creating programmable 5G systems for the Industrial IoT

A steadily growing number of factories, plants, mines and ports around the world are exploring the potential of 5G technology and considering how best to deploy it. This is to be expected, since 5G has been designed with vertical use cases in mind, and industrial automation systems are one of the most promising segments.

Industrial control system risk assessment standards and leading practices in the chemical industry

AbstractThere is no simple recipe for how to secure an industrial automation and control system (IACS) and there is good reason for this. It is because security is a matter of risk management. Every IACS presents a different risk to the organization depending upon the threats it is exposed to, the likelihood of those threats arising, the inherent vulnerabilities in the system, and the consequences if the system were to be compromised. Furthermore, every organization that owns and operates an IACS has a different tolerance for risk. The new ISA/IEC standard, 62443 Part 3‐2, Security Risk Assessment for System Design, strives to define a set of engineering measures that will guide an organization through the process of assessing the risk of a particular IACS and identifying and applying security countermeasures to reduce that risk to tolerable levels. This paper provides an overview of the purpose and objectives as well as an overview of the workflows and requirements defined in this standard.

OPC-UA Agent for Legacy Programmable Logic Controllers

Open platform communications (OPC) unified architecture (UA) is a communication standard increasingly used in industrial automation systems to enable the exchanging of control and management data between distributed entities. This paper proposes the design of an OPC-UA agent to enable UA information service and client functionalities in legacy programmable logic controllers (PLCs). The agent runs on a separate machine connected to the PLC using a dedicated link and maintains shared memory for certain variables in the PLC. Based on the periodically synchronized variables, the agent services the OPC-UA information model and executes client function blocks on behalf of the PLC. One important design feature is the remote procedure call of IEC 61131-3-based function blocks using synchronized variables. This allows the standard OPC-UA client functions to be used in existing PLCs which only support numeric types and do not support strings or complex structures. To validate the proposed design, we implement an agent prototype and demonstrate the successful monitoring and control of an industrial robot controller via OPC-UA. Through experiments, we evaluate the performance of UA functions in terms of the latency of read services for an increasing number of items. The evaluation results are believed to provide useful insights into agent-based approaches for integrating legacy PLCs into the OPC-UA framework.

Design and Implementation of a Reliable and Secure Controller for Smart Home Applications Based on PLC

Programmable logic controllers (PLCs) are increasingly being used to realize modern safety-critical instrumentation and control (IC) applications. Examples of these applications are industrial automation and control systems, plant process safety protection systems, smart home systems and digital IC systems embedded in nuclear power plants (NPPs) that require high levels of performance, reliability, and flexibility. The PLC is a flexible, programmable, and robust digital device that can execute all logical and mathematical runtime functions of the IC application and operate in harsh-critical environments. This paper proposes a PLC-based home security controller based on the ladder logic programming model. The design, analysis, and hardware implementation of this controller are presented in this paper. The designed system consists of three basic modules which are a sensing module used for reading the data of the input field devices for the smart home application, a computation-based decisional module used for executing the programming model, and an actuating module used for sending the control commands to the output field devices. The proposed home security system utilized different types of sensors such as a laser photoelectric sensor, a motion or proximity sensor, and a limit switch. In addition, a siren speaker, a light tower including three lights red, yellow, and green, two push-pull switches and emergency push-pull buttons were used as control inputs and output indicators in the implementation of this work This designed system is implemented on the Allen-Bradley CompactLogix PLC controller and Human Machine Interface (HMI) panel programmed as the graphical user interface. The experimental simulation results of the real hardware connection demonstrate that the proposed system is reliable, safe, and feasible for smart home security applications.

An Automated Machine Learning Approach for Real-Time Fault Detection and Diagnosis.

This work presents a novel Automated Machine Learning (AutoML) approach for Real-Time Fault Detection and Diagnosis (RT-FDD). The approach’s particular characteristics are: it uses only data that are commonly available in industrial automation systems; it automates all ML processes without human intervention; a non-ML expert can deploy it; and it considers the behavior of cyclic sequential machines, combining discrete timed events and continuous variables as features. The capacity for fault detection is analyzed in two case studies, using data from a 3D machine simulation system with faulty and non-faulty conditions. The enhancement of the RT-FDD performance when the proposed approach is applied is proved with the Feature Importance, Confusion Matrix, and F1 Score analysis, reaching mean values of 85% and 100% in each case study. Finally, considering that faults are rare events, the sensitivity of the models to the number of faulty samples is analyzed.

Testing AGV mobility control method for MANET coverage optimization using procedural simulation

In industrial applications continuous wireless connectivity of mobile clients can rarely by guaranteed. Lack of communication negatively impacts the performance of industrial automation systems, e.g. Automated Guided Vehicle (AGV) fleets. Utilizing industrial Mobile Ad-hoc NETworks (MANETs) and an adaptive positioning scheme can reduce the number of disconnections in AGV fleets. Therefore, the performance of the mobile system (e.g. AGV fleet) is improved and factory efficiency increased.In this work procedural simulation is used to examine wireless communication in industrial applications. This method enables the observation of the interaction of mobility control system, network status and robotic system performance independently from a specific environment or scenario. Novel insights on the effectiveness of ad-hoc communication in industrial applications and the correlation of AGV fleet connectedness and AGV fleet transport performance are presented. Additionally, a control method is proposed, which improves the network coverage of an industrial MANET and efficiency of AGV fleets.