Industrial Control Environment Research Articles

Strategies for Software and Hardware Compatibility Testing in Industrial Controllers

Mass customization, small batch sizes, high variability of product types and a changing product portfolio during the life cycle of an industrial plant are current trends in the industry. Due to an increasing decoupling of the development of software and hardware components in an industrial context, compatibility problems within industrial control systems arise more and more frequently. In this publication, a strategy concept for compatibility testing is derived and discussed by means of a literature review and applied research. This four-phase strategy concept identifies incompatibilities between software and hardware components in the industrial control environment and enables test engineers to detect problems at an early stage. By automating the compatibility test on an external I-PC, the test can be run both when new software is installed on the industrial controller and when the controller is restarted. Thus, changes to the components are constantly detected and incompatibilities are avoided. Furthermore, early incompatibility detection can ensure that a system remains permanently operational. Based on a discussion, additional strategies are identified to consolidate the robustness and applicability of the presented concept.

A Lightweight Unsupervised Intrusion Detection Model Based on Variational Auto-Encoder.

With the gradual integration of internet technology and the industrial control field, industrial control systems (ICSs) have begun to access public networks on a large scale. Attackers use these public network interfaces to launch frequent invasions of industrial control systems, thus resulting in equipment failure and downtime, production data leakage, and other serious harm. To ensure security, ICSs urgently need a mature intrusion detection mechanism. Most of the existing research on intrusion detection in ICSs focuses on improving the accuracy of intrusion detection, thereby ignoring the problem of limited equipment resources in industrial control environments, which makes it difficult to apply excellent intrusion detection algorithms in practice. In this study, we first use the spectral residual (SR) algorithm to process the data; we then propose the improved lightweight variational autoencoder (LVA) with autoregression to reconstruct the data, and we finally perform anomaly determination based on the permutation entropy (PE) algorithm. We construct a lightweight unsupervised intrusion detection model named LVA-SP. The model as a whole adopts a lightweight design with a simpler network structure and fewer parameters, which achieves a balance between the detection accuracy and the system resource overhead. Experimental results on the ICSs dataset show that our proposed LVA-SP model achieved an F1-score of 84.81% and has advantages in terms of time and memory overhead.

Recent Advances in Integrating 1D Nanomaterials into Chemiresistive Gas Sensor Devices

AbstractThere is rapid growth in the global gas sensor market driven by new regulations for industrial emission control and residential environments and increasing demand for portable devices. Nanosensors promise to be the next generation gas sensors for the direct detection of chemical species due to their ultrahigh sensitivity, fast response, ultralow weight, and low power consumption. However, transitioning nanosensors from basic research or prototype projects to commercial products encounters two major technical challenges: difficulty in scale up and inability to demonstrate real‐world use in changing humidity and temperature conditions. The advances in addressing these two technical challenges in recent literature are surveyed. The most common 1D nanomaterials in R&D for gas sensing, metal oxides, and carbon nanotubes, as well as less common metal nanowires and psudo‐1D crystals made from charge‐transfer complexes (CTCs) are included. This review delves into the specifics of each of these 1D nanomaterials for gas sensing applications, their synthesis and deposition, sensing performance, and commercial development in the last 5 years. It highlights the scalability of one‐step electrodeposition of CTC nanowires on prefabricated electrodes, at room temperature, and from solution in making gas nanosensors.

Automation of Non-Destructive Evaluation of Casting Parts based on Computed Tomography and Machine Learning

The development of digital tools exploiting computed tomography (CT) data intelligently, in their entirety and in a simple manner is a major challenge for the full deployment of this technology in industrial production control environment. This work aims at developing a pipeline able to detect material discontinuities in metallic parts, in an automated way without human analysis, to classify them according to their nature and to apply criteria resulting from specifications to rule on the acceptance or not of the parts. It exploits the last advances in artificial intelligence data treatment, and it is based on a dedicated processing and visualisation platform that optimizes the handling of large volumes of data.

A cyber resilience analysis case study of an industrial operational technology environment

Cyber resilience is an active research area offering a novel approach to Cyber Security. The term appeared due to the concerning number of cyber-attacks on critical infrastructure. The National Institute of Standards and Technology (NIST) developed a framework to assist organisations with techniques and approaches to improving cyber resilience. However, there are a sparsity of case studies that speak to the adoption or measurement of these novel approaches within a complex industrial control environment. This paper presents a case study analysis of a manufacturing plant assessment drawing on key themes from the NIST literature. The paper presents how well NIST constructs can be adopted to find cyber-resilient enhancement opportunities and to decide if an evaluation of the results could supply a quantitative baseline measure of an organisation’s overall resilience. Conclusions drawn show that although the framework did partially aid with the analysis process, the frameworks ease of adoption assume an organisation has a conventional cyber security foundation; NIST should make this clear within their guidance. Furthermore, the accompanying evaluation process was not sufficient to quantitatively measure the overall cyber resilience maturity for this case study.

Impact of urban innovation ability on industrial pollution governance in Chinese cities: taking the Yangtze River Economic Belt as an example.

This paper uses spatial measurement method, by selecting panel data from a total of 106 cities in 11 provinces and municipalities in the Yangtze River Economic Belt from 2006 to 2018, to conduct an empirical study on the impact mechanism of urban innovation ability on industrial pollution governance. The results show that there is a significant negative correlation between urban innovation ability and the degree of industrial pollution, and cities in the Yangtze River Economic Belt have a significant spatial connection. Specifically, this paper finds that urban innovation ability can have a positive impact on urban industrial pollution governance through industrial selection, production technology innovation, pollution discharge technology innovation, and environmental pollution treatment, which will help cities reduce industrial pollution; The industrial pollution governance level of individual cities is not only affected by the innovation ability of the city, but also by the innovation spillover of the surrounding cities. Area surrounded by cities with high urban innovation ability will benefit from the spillover of the surrounding cities. The industrial pollution governance level of individual cities is not only affected by the innovation ability of the city, but also by the innovation spillover of the surrounding cities. Areas surrounded by cities with high urban innovation ability will benefit from the spillover of the surrounding cities, thus improving the industrial pollution control and regional ecological environment. Based on this, this paper proposes relevant policy recommendations for urban industrial pollution governance from the perspective of improving urban innovation ability.

Adaptive anomaly detection system based on machine learning algorithms in an industrial control environment

Technology has become an integral part of contemporary society. The current transition from an industrial society to an information society is accompanied by the implementation of new technologies in every part of human activity. Increasing pressure to apply ICT in critical infrastructure resulted in the creation of new vulnerabilities. Traditional safety approaches are ineffective in a considerable number of cases. Therefore, machine learning another evolutionary step that provides robust solutions for extensive and sophisticated systems. The article focuses on cybersecurity research for industrial control systems that are widely used in the field of critical information infrastructure. Moreover, cybernetic protection for industrial control systems is one of the most important security types for a modern state. We present an adaptive solution for defense against cyber-attacks, which also consider the specifics of the industrial control systems environment. Moreover, the experiments are based on four machine learning algorithms (artificial neural network, recurrent neural network LSTM, isolation forest, and algorithm OCSVM). The proposed anomaly detection system utilizes multiple techniques and processes as preprocessing techniques, optimization techniques, and processes required for result interpretation. These procedures allow the creation of an adaptable and robust system that meets the need for industrial control systems.

Assessment of CE-based baseline disturbances using simulation and targeted experimental evaluation-impact on the purity determination of therapeutic proteins.

The baseline instability for capillary electrophoretic analysis is an intrinsic feature of the technique, which has not been thoroughly examined for its impact on therapeutic protein purity analysis with the capillary electrophoresis-sodium dodecyl sulfate (CE-SDS) applications. For the particular CE-SDS application, this phenomenon was manifested through peak migration time shifts and sliding of the superimposed baseline profile. These dual phenomena are closely associated so that experimental assessment alone may not shed enough light to the underlying drivers. In the current study, both experimental and simulation approaches were employed to assess the systematic drifts. Computer simulation was used to decipher the two underlying factors and test their contributions toward purity and impurity peak determination inaccuracies. The data generated in this study demonstrated that the electrophoretic baseline disturbance had more pronounced impact on the purity data than the migration time shift. In addition, the potential contributing factors to the baseline disturbances were assessed experimentally which indicated that the source is related to thermal disruption during a sample run and the unique baseline patterns came from the background electrolytes. To improve data reproducibility for drug purity testing in the industrial setting and quality control (QC) environment, it is recommended to run shorter injection sequences including fewer samples and closely monitor the baseline drift for accurate integration. Those methods would help reduce the impact of systematic drift and disturbances. Graphical abstract.

A framework for Operational Security Metrics Development for industrial control environment

ABSTRACTSecurity metrics are very crucial towards providing insights when measuring security states and susceptibilities in industrial operational environments. Obtaining practical security metrics depend on effective security metrics development approaches. To be effective, a security metrics development framework should be scope-definitive, objective-oriented, reliable, simple, adaptable, and repeatable (SORSAR). A framework for Operational Security Metrics Development (OSMD) for industry control environments is presented, which combines concepts and characteristics from existing approaches. It also adds the new characteristic of adaptability. The OSMD framework is broken down into three phases of: target definition, objective definition, and metrics synthesis. A case study scenario is used to demonstrate an instance of how to implement and apply the proposed framework to demonstrate its usability and workability. Expert elicitation has also be used to consolidate the validity of the proposed framework. Both validation approaches have helped to show that the proposed framework can help create effective and efficient ICS-centric security metrics taxonomy that can be used to evaluate capabilities or vulnerabilities. The understanding from this can help enhance security assurance within industrial operational environments.

Glyphosate: Surfactant herbicide poisoning - Is it mild?

Glyphosate Surfactant is a nonselective widely used herbicide in agriculture, forestry, industrial weed control, lawn, garden and aquatic environments. They have favorable toxicity with occupational and accidental exposures. The toxicity in humans is mucosal and gastrointestinal irritation, hypotension, metabolic acidosis, pulmonary insufficiency, and oliguria. Patient may appear asymptomatic for many hours before slowly lapse into a hypotensive, apparently nonhypovolaemic shock that can often ends fatally. We hereby report a case of a 25-year-old male patient who was admitted to our tertiary care hospital following suicidal consumption of around 250-300 ml of herbicide containing glyphosate (glypho ; ). Initially, gastric lavage done and the patient was managed with intubation and mechanical ventilation. He also developed acute renal failure, and renal function reverted to normal after four sittings of hemodialysis. Patient was successfully treated and discharged home. This case report emphasizes on timely systemic supportive measure as the sole method of treatment since this poison has no specific antidote.

Application of the OPC Technology in the No-Load Test Platform of the Metro Bogie

The generation of the OPC technology makes each data source communicate flexibly in the industrial control environment. This paper takes the no-load test platform of the metro bogie as an example to design a lower and upper computer measurement and control system which is consist of IPC and PLC by the OPC technology. The OPC client is developed based on the platform of Visual Basic. By using the different communication mode, it is realized to access the OPC server data.

Acute toxicity and sublethal effects of the mixture glyphosate (Roundup Active) and Cosmo-Flux 411F to anuran embryos and tadpoles of four Colombian species.

Glyphosate is the most widely used herbicide in the world with application in agriculture, forestry, industrial weed control, garden and aquatic environments. However, its use is highly controversial for the possible impact on not-target organisms, such as amphibians, which are vanishing at an alarming and rapid rate. Due to the high solubility in water and ionic nature, the glyphosate requires of surfactants to increase activity. In addition, for the control of coca (Erythroxylum coca) and agricultural weeds in Colombia, formulated glyphosate is mixed and sprayed with the adjuvant Cosmo-Flux 411F to increase the penetration and activity of the herbicide. This study evaluates the acute toxic and sublethal effects (embryonic development, tadpole body size, tadpole swimming performance) of the mixture of the formulated glyphosate Roundup Active and Cosmo-Flux 411F to anuran embryos and tadpoles of four Colombian species under 96h laboratory standard tests and microcosms, which are more similar to field conditions as they include soil, sand and macrophytes. In the laboratory, embryos and tadpoles of Engystomops pustulosus were the most tolerant (LC50 = 3904 microg a.e./L; LC50=2 799 pg a.e./L, respectively), while embryos and tadpoles of Hypsiboas crepitans (LC50=2 203 microg a.e./L; LC50=1424 microgg a.e./L, respectively) were the most sensitive. R. humboldti and R. marina presented an intermediate toxicity. Embryos were significantly more tolerant to the mixture than tadpoles, which could be likely attributed to the exclusion of chemicals by the embryonic membranes and the lack of organs, such as gills, which are sensitive to surfactants. Sublethal effects were observed for the tadpole body size, but not for the embryonic development and tadpole swimming performance. In microcosms, no toxicity (LC50 could not be estimated), or sublethal responses were observed at concentrations up to fourfold (14.76 kg glyphosate a.e./ha) the highest field application rate of 3.69 kg glyphosate a.e./ha. Thus, toxicity was less in the microcosms than in laboratory tests, which may be attributed to the presence of sediments and organic matter which rapidly adsorb glyphosate and surfactants such as POEA. It is concluded that the mixture of glyphosate (Roundup Active) and Cosmo-Flux*411F, as used in the field, has a negligible toxic effect to embryos and tadpoles of the species tested in this study.

Extending the RPL Routing Protocol to Agricultural Low Power and Lossy Networks (A-LLNs)

The routing protocol for low power and lossy network (RPL) started to be designed by the ROLL working group of IETF since the year of 2008. Until the RFC6550 was released, this standard with its routing algorithms and four application scenarios, such as home and building automation, industrial control, and urban environment, have been grounded. As a main jigsaw of the paradigm of the Internet of Things (IoT), RPL plays the major role and has become an impressed technical tendency in the field of wireless communication. However, it is still very difficult to find effective approaches to simulate and evaluate RPL’s behaviors and other extensions of its applicability, especially in the domain of precision agriculture. Notice that wireless sensor network (WSN) has been deployed a wide variety of wireless sensing devices, and should be one valued supported part of the promising IoT ecosystem. In this paper, first the authors provide a brief presentation of the related protocols including their standardization, the existing implementations, and a group of simulation experiment results obtained from the RPL capable COOJA simulator with its developed modules. Second, the authors then focus on the utilization of this protocol in the agricultural low power and lossy network (A-LLN) area and propose their dedicated instances hybrid network architecture to meet its specific requirement. Moreover, the Web of things (WoT), a trend and new vision of IoT, is appended in the authors’ proposal to provide a novel dimension in design of A-LLN since it enables a full interoperability with current web application and higher efficiency of development. As a conclusion, the authors summarized their ongoing work and future solutions of the current technology issues.

Research and Implementation of Time Synchronization Protocol Based on the ZigBee

ZigBee technology is more and more used in complex and bad industrial monitoring and control environment. At the same time, ZigBee nodes are usually powered by batteries, so prolonging the working time and reducing the power consumption of the nodes is very important. If the wireless nodes can turn into sleep mode in spare time of communication, it will further reduce the node power consumption. But in sleep period, the node can't communication with other node, we need to synchronous awaken and dormancy, so precise time synchronization for wireless sensor network application is particularly important. This paper will apply FTSP algorithm in the ZigBee network and realize the network time synchronization. At the same time, it doesn't increase power consumption of the network.

Reliability Modeling of Embedded Nodes in Real Time Wireless Systems

Nowadays there is an increasing trend of applying wireless technologies in industrial automation. However, the industrial control environment is harsher and noisier posing more stringent requirements on real-time communication. The variation in wireless signal strength with time and location, and power limitation due to battery usage make the problem even worse. Accordingly, availability and reliability of such system should be seriously analyzed before deployment. Modeling the reliability of these distributed real-time systems with nodes having embedded software has become an integral part of the design process. The time constraints that real-time systems must meet directly affect the reliability measure itself irrespective of the nature of the measure. A metric for calculating system reliability is proposed in this paper and a Monte Carlo simulation based algorithm for calculating the same is presented here. The results show that system reliability stabilizes with time even with increasing network size.

Analysis of the security of VPN configurations in industrial control environments

Virtual private networks (VPNs) are a popular approach for protecting otherwise insecure industrial control protocols. VPNs provide confidentiality, integrity and availability, and are often considered to be secure. However, implementation vulnerabilities and protocol flaws expose VPN weaknesses in many industrial deployments. This paper employs a probabilistic model to evaluate and quantify the security of VPN configurations. Simulations of the VPN model are conducted to investigate the trade-offs and parameter dependence in various VPN configurations. The experimental results provide recommendations for securing VPN deployments in industrial control environments.

The Impact of Temperature on Outdoor Industrial Sensornet Applications

Wireless sensor networks are being considered for use in industrial process and control environments. Unlike traditional deployment scenarios for sensor networks, in which energy preservation is the main design principle, industrial environments stress worker safety and uninterrupted production. To fulfill these requirements, sensor networks must be able to provide performance guarantees for radio communication. In this paper, we consider as a case study the deployment of a sensornet in an oil refinery in Portugal, where sensor nodes are deployed outdoors and might experience high temperature fluctuations. We investigate how the variations of ambient temperature influence data delivery performance and link quality in low-power radio communications. We also study the impact that specific implementation requirements, such as the ATEX fire-safety regulations, can have on the design of the overall network. Our experiments show that temperature directly affects the communication between sensor nodes, and that significantly less transmission power is required at low temperatures. We further illustrate that it is possible to save up to 16% energy during nights and cold periods of the year, while still ensuring reliable communication among sensor nodes. In view of these experimental results, we elaborate on how the temperature influences both the design and the deployment of wireless sensor networks in industrial environments.

Evaluating the Prometheus methodology through a case study on designing an agent-based holonic control system

An agent-based manufacturing system is a new breed of industrial control environment where autonomous software entities, called agents, cooperate to manage the hardware in a factory in a decentralised and intelligent manner. These control systems allow new product families to be introduced on the fly and empower the machinery to late-customise products. This paper analyses the applicability of Prometheus, one of the popular methodologies for designing general-purpose agent-based systems. The paper examines how useful Prometheus is for designing agent-based industrial control systems. An industrial-strength, flexible material-handling environment provides the experimental test-bed for this analysis. The key conclusion is that this methodology is very suitable for developing static interactions between agents, but lacks sufficient power to handle several of the requirements associated with a real-world industrial environment, e.g., openness of new agent types and services, system development using bottom-up design approaches and dynamic reconfiguration of the manufacturing processes.

The oscillatory squeeze flow rheometer: comprehensive theory and a new experimental facility

In this paper, we give detailed attention to a relatively recent method for the determination of the linear dynamic properties of viscoelastic systems, namely, the so-called oscillatory squeeze flow (OSF) technique. We provide a comprehensive theory for the OSF rheometer, which includes a full discussion of the influence of fluid inertia. In the process, it is argued that, fortuitously perhaps, fluid inertia is more easily accommodated in the OSF rheometer than in the corresponding torsional-flow techniques. A new version of the OSF rheometer is described and experimental results on a set of viscoelastic systems are used to demonstrate the versatility of the technique. In the process, the potential use of the instrument within an industrial quality control environment is stressed.

Time‐triggered Ethernet based on IEEE 1588 clock synchronisation

In industrial distributed control environments for automation technology, Ethernet network based solutions are gaining prominence in the traditional fieldbus application areas with the promise of standardised solutions that can support real‐time operation to a resolution of less than 1 μm. However, there are no formal standards for a real‐time Industrial Ethernet. This paper looks at some of the emerging de facto solutions and describes a novel project where clusters of real‐time transducer networks are developed and the control is tightly synchronised using the IEEE 1588 clock synchronisation standard, realising a “Time‐triggered Ethernet” solution.