by Gary Mintchell | Feb 20, 2020 | Internet of Things, Manufacturing IT
The “Edge” is a hot space right now, although sometimes I’m not sure that everyone agrees what “Edge” is as they develop products and solutions. However, first thing this morning I saw this tweet from Tom Bradicich of Hewlett Packard Enterprise (@HPE) referring to an article that mentions him in CouputerWeekly.com. I’ve written about HPE at the edge and with IoT before. Looks like something’s up.
Tweet from @TomBradicichPhD Not only computing at the #edge, but also a new product category of “converging IT with #OT” systems (such as controls, DAQ, industrial protocols). Watch this space, my team’s next innovation is all this as-a-service. #aaS
Here is the rationale from the Computer Weekly article. “The benefits of edge computing have the potential to help businesses dramatically speed up their data analysis time while cutting down costs. @HPE’s Mark Potter and @TomBradicichPhD share how we can make this possible.”
In the past, all data processing was run locally on the industrial control system. But while there is industry consensus that real-time data processing for decision-making, such as the data processing needed in an industrial control system, should be run at the edge and not in the public cloud, there are many benefits in using the public cloud or an on-premise datacentre to assimilate data across installations of internet of things (IoT)-connected machines. Such data aggregation can be used to improve machine learning algorithms.
It is fascinating to see our environment described by an enterprise IT writer. The truth is that following the Purdue Model, suppliers tried to make PLCs and DCSs part of the information infrastructure in parallel to supervising or executing control functions. That proved too unwieldy for control engineers to manage within the programming tools used. It was also too slow and not really optimized for the task.
Along came IT companies. I have followed a few over the past five years. They have had trouble with figuring out how to make a business out of edge compute, gateways, networking, and the like.
In the past, data acquisition and control systems were considered operational technology, and so were outside the remit of enterprise IT. But, as Tom Bradicich, global head of the edge and IoT labs at HPE explains, IT has a role to play in edge computing.
Bradicich’s argument is that edge computing can provide a converged system, removing the need for standalone devices that were previously managed by those people in the organisation responsible for operational technology (OT). According to Bradicich, convergence is a good thing for the industry because it is convenient, makes it easy to buy devices, lowers cost, improves reliability, and offers better power consumption because all the disparate functions required by an industrial system are integrated in one device.
Bradicich believes convergence in IoT will be as big as the convergence of camera and music players into a device like the iPhone, which made Apple the biggest music and camera company in the world. For Bradicich, convergence at the edge will lead to industry disruption, similar to what happened when smartphones integrated several bits of functionality that were previously only available as separate devices. “The reason Uber exists is because there is a convergence of GPS, the phone and the maps,” he says. “This disrupts the whole industry.”
I get this analogy to converging technologies into a device such as the iPhone. I don’t know if we want to cede control over to an HPE compute platform (although it has plenty of horsepower), but the idea is tempting. And it would be thoroughly disruptive.
Forrester has forecast that the edge cloud service market will grow by at least 50%. Its Predictions 2020 report notes that public cloud providers such as Amazon Web Services (AWS) and Microsoft; telecommunication companies such as AT&T, Telstra and Vodafone Group; platform software providers such as Red Hat and VMware; content delivery networks including Akamai Technologies; and datacentre colocation providers such as Digital Realty are all developing basic infrastructure-as-a-service (IaaS) and advanced cloud-native programming services on distributed edge computing infrastructure.
HPE’s investment in a new company called Pensando, which recently emerged from stealth mode and is founded and staffed by former Cisco technologists with former Cisco CEO John Chambers installed as Chairman, Sunil believes new categories of device will come to market, aimed at edge computing, could lead to a plethora of new devices perhaps to perform data acquisition and real-time data processing.
Mark Potter recently wrote in a blog post, By becoming the first solutions providers to deliver software-defined compute, networking, storage and security services to where data is generated, HPE and Pensando will enable our customers to dramatically accelerate the analysis and time-to-insight of their data in in a way that is completely air-gapped from the core system.
These are critically-important requirements in our hyper-connected, edge-centric, cloud-enabled and data-driven world – where billions of people and trillions of things interact.
This convergence is generating unimaginable amounts of data from which enterprises seek to unearth industry-shaping insights. And as emerging technologies like edge computing, AI and 5G become even more mainstream, enterprises have an ever-growing need to harness the power of that data. But moving data from its point of generation to a central data center for processing presents major challenges — from substantial delays in analysis to security, governance and compliance risks.
That’s where Pensando and HPE are making an industry-defining difference. By moving the traditionally data center-bound network, storage and security services to the server processing the data, we will eliminate the need for round-trip data transfer to centralized network and security appliances – and at a lower cost, with more efficiency and higher performance.
Here are benefits that Potter listed:
- Lower latency to competitive solutions, as operations will be carried at a 100Gbps network line rate speed;
- Controller management framework to scale across thousands of nodes with a federation of controllers allowing scale to 1M+ endpoints; and
- Security, governance and compliance policies that are consistently applied at the edge.
by Gary Mintchell | Feb 19, 2020 | Uncategorized
While at the Hannover Messe Preview last week in Germany, I talked with the representatives of a German consortium with the interesting name of “it’s OWL”. Following are some thoughts from the various organizations that compose the consortium.
Intelligent production and new business models
Artificial Intelligence is of crucial importance for the competitiveness of industry. In the Leading-Edge Cluster it’s OWL six research institutes cooperate with more than 100 companies to develop practical solutions for small and medium-sized businesses. At the OWL joint stand (Hall 7, A12) over 40 exhibitors will demonstrate applications in the areas of machine diagnostics, predictive maintenance, process optimization, and robotics.
Prof. Dr. Roman Dumitrescu (Managing Director it’s OWL Clustermanagement GmbH and Director Fraunhofer IEM) explains: “Our research institutes are international leaders in the fields of machine learning, cognitive assistance systems and systems engineering. At our four universities and two Fraunhofer Institutes, 350 researchers are working on over 100 projects to make Artificial Intelligence usable for applications in industrial value creation. With it’s OWL, we bring this expert knowledge into practice. In 2020, we will launch three new strategic initiatives worth 50 million € to unlock the potential for AI in production, product development and the working world for small and medium-sized enterprises.”
In the initiative ‘AI Marketplace’ 20, research institutes and companies are developing a digital platform for Artificial Intelligence in product development. Providers, users, and experts can network and develop solutions on this platform. In the competence centre ‘AI in the working world of industrial SMEs’, 25 partners from industry and science make their knowledge of work structuring in the context of AI available to companies.
Learning machine diagnostics and ‘SmartBox’ for process optimization
The Institute for Industrial Information Technology at the OWL University of Applied Sciences and Arts will present new results for intelligent machine diagnostics at the trade fair. Using a three-phase motor, it will be illustrated how learning algorithms and information fusion can be used to reliably identify, predict, and visualize states of technical systems. Patterns and information hidden in time series signals are learned and presented to the user in an understandable way. Inaccuracies and uncertainties in individual sensors are solved by conflict-reducing information fusion. For example, motors can be used as sensors. Within a network of sensors and other data sources in production plants, motors can measure the “state of health” and analyze the causes of malfunctions via AI. This reduces scrap and saves up to 20 percent in materials.
The ‘SmartBox’ of the Fraunhofer Institute IOSB-INA is a universally applicable solution that identifies anomalies in processes in various production environments on the basis of PROFI-NET data. The solution requires no configuration and learns the process behavior.
With retrofitting solutions of the Fraunhofer Institute, companies can prepare machines and systems in their inventory for Industrie 4.0 applications without major investment expenditure. The spectrum ranges from mobile production data acquisition systems in suitcase format for studies of potential to permanently installable retrofit solutions. Intelligent sensor systems, cloud connections and machine learning methods build the basis for data analysis. This way, processes can be optimised and more transparency, control, planning, safety, and flexibility in production can be achieved.
Cognitive robotics and self-healing in autonomous systems
The Institute of Cognition and Robotics (CoR-Lab) presents a cognitive robotics system for highly flexible industrial production. The potential of model-driven software and system development for cognitive robotics is demonstrated by using the example of automated terminal assembly in switch cabinet construction. For this purpose, machine learning methods for environ- mental perception and object recognition, automated planning algorithms and model-based motion control are integrated into a robotic system. The cell operator is thereby enabled to perform different assembly tasks using reusable and combinable task blocks.
The research project “AI for Autonomous Systems” of the Software Innovation Campus Paderborn aims at achieving self-healing properties of autonomous technical systems based on the principles of natural immune systems. For this purpose, anomalies must be detected at runtime and the underlying causes must be independently diagnosed. Based on the localization it is necessary to plan and implement behavioral adjustments to restore the function. In addition, the security of the systems must be guaranteed at all times and system reliability must be increased. This requires a combination of methods of artificial intelligence, machine learning and biologically inspired algorithms.
Predictive maintenance and digital twin
Within the framework of the ‘BOOST 4.0’ project, the largest European initiative for Big Data in industry, it’s OWL is working with 50 partners from 16 countries on various application scenarios for Big Data in production. it’s OWL focuses on predictive maintenance: thanks to the systematic collection and evaluation of machine data from a hydraulic press and a material conveyor system, it is possible to identify patterns in the production process in a pilot company. The Fraunhofer IEM has provided the technological and methodological basis. And successfully so: over the past two years the prediction of machine failures has been significantly improved in this specific application by means of machine learning methods. The Mean Time To Repair (MTTR) has already been reduced by more than 30 percent. The Mean Time Between Failures (MTBF) is now six times longer than before. A model of the predictive production line can be seen at the stand.
The digital twin is an important prerequisite for increasing the potential for efficiency and productivity in all phases of the machine life cycle. Companies and research institutes are working on the technical infrastructure for digital twins in an it’s OWL project. Digital descriptions and sub-models of machines, products and equipment as well as their interaction over the entire life cycle are now accessible thanks to interoperability. Requirements from the fields of energy and production technology as well as existing Industrie 4.0 standards and IT systems are taken into account. This is expected to result in potential savings of over 50 percent. At the joint stand, Lenze and Phoenix Contact will use typical machine modules to demonstrate how digital twins can be used to exchange information between components, machines, visualisations and digital services across manufacturers. Interoperability proves for the first time how the combination of data can be used to create useful information with added value for different user groups. For example, machine operators and maintenance staff can detect anomalies and receive instructions for troubleshooting.
Connect and get started – production optimization made easy
The cooperation in the Leading-Edge Cluster gives rise to new business ideas that are developed into successful start-ups. For example, Prodaso—a spin-off from Bielefeld University of Applied Sciences—has developed a simple and quickly implementable solution for the acquisition and visualization of machine and production data. The hardware can be connected to a machine in a few minutes via plug-and-play. The machine data is displayed directly in the cloud.
Prodaso has succeeded in solving a central challenge: Until now, networking machines from different manufacturers have been complex and costly. The Prodaso system can be retrofitted to all existing systems, independent of manufacturer and interface. In addition, the start- up also provides automated analysis and optimization tools. This enables companies to detect irregularities and deviations in the process flow at an early stage and to initiate appropriate measures. The company, founded in 2019, has already connected approximately 100 machines at companies in the manufacturing industry.
by Gary Mintchell | Feb 18, 2020 | Leadership
Effective leaders are comfortable within themselves. Both outgoing, quick witted leaders and quiet, thoughtful people can be effective leaders. People follow people who are clear, confident, and know them selves.
I first discovered the Enneagram at least 35 years ago through study of the Jesuits. Ennea from the Greek for nine; gram from the Greek for picture or diagram. The Enneagram is a diagram showing the nine basic personality types and some relationships among them.
The origins of the Enneagram are hazy, but an early church father is thought to have put out the original ideas.
The Road Back to You by Ian Morgan Cron and Suzanne Stabile provides an overview of the nine types and their nuances. Most importantly, since the Enneagram has Christian origins, it is more useful for personal and spiritual development than it is for psychological profiling.
Oh, the nine types:
- One-The Perfectionist, Reformer
- Two-Helper, Giver
- Three-Achiever, Performer
- Four-Individualist, Romantic
- Five-Investigator, Observer
- Six-Loyalist, Loyal Skeptic
- Seven-Enthusiast, Epicure
- Eight-Challenger, Protector
- Nine-Peacemaker, Mediator
I am a Five with a strong Four—just so you know why I write observations so much and prefer reading and researching. Don’t ask about the Romantic side 😉
Ian Morgan Cron has partnered with a company for Enneagram assessments.
As you go deeper, you discover that 9, for example, may have a relationship with 8 and 1. All three are in the “anger” triad. Each deals with the anger that began in childhood differently. They call these “wings”, so you could be 9 with an 8 wing, for example, which will describe you in more details.
Even that is simplified. However, each number has a healthy side and an unhealthy side. It becomes important to your growth and spiritual journey to recognize when you are healthy and when you are not. Then you have work to do to get to healthy.
Also, we all have some of each number. So in the mixture comes an occasional misunderstanding. Depending upon the assessment, I can come up with a strong 9. But upon reflection, it is really a manifestation of 5 where I take time to digest things, think about it, see both sides of the issue, and so on.
The purpose of the Enneagram is not just to know your type, or your significant other’s type, or the numbers of your co-workers. It is to do the work of growth and spiritual development. It never ends.
by Gary Mintchell | Feb 12, 2020 | Automation, Internet of Things, Manufacturing IT, News, Operations Management, Technology
Announcements and discussions at this year’s iteration of the Industry Forum sponsored by ARC Advisory Group were amazingly diverse. Another IT supplier appeared. Security remained an issue. Most conversations revolved around open (open source and open interoperability), edge, 5G, collaboration/partnerships, software-defined, machine learning, MQTT and its companion Sparkplug, and most importantly, solving problems for end users.
Following is a brief recap. Follow the links for in-depth information. Of course, many company announcements fit into more than one bucket.
Open
Examples one of a variety of open include Eclipse Foundation and the Open Group Open Process Automation Forum with the IT technology of Kubernetes thrown in.
The Eclipse Foundation launched the Sparkplug Working Group. Founding members Chevron, Canary Labs, Cirrus Link Solutions, HiveMQ, Inductive Automation, and ORing are defining an open standard specification to create interoperable MQTT IIoT solutions.
The Working Group will encourage the definition of technical specifications and associated implementations that rationalize access to industrial data, improve the interoperability and scalability of IIoT solutions, and provide an overall framework for supporting Industry 4.0 for oil and gas, energy, manufacturing, smart cities and other related industries.
Sparkplug is relatively new which leads to interoperability problems since each supplier and end user must create all definitions of the data. Success of this WG is essential for any widespread adoption of is. The Eclipse Foundation pointed out the intent and purpose of the Sparkplug specification is to define an MQTT topic namespace, payload, and session state management that can be applied generically. By meeting the operational requirements for these systems, Sparkplug will enable MQTT-based infrastructures to provide more valuable real-time information to business stakeholders as well.
The Open Group Open Process Automation Forum progresses. This topic broaches on both open and software-defined control. The Open Group Open Process Automation Forum (OPAF), in the first major update to the standard for open process automation systems since February 2019, has progressed perhaps more than I would have predicted after its unveiling only a few years ago at the ARC Forum.
Its first release focused on interoperability while the O-PAS Standard Version 2.0 provides a vendor-neutral Reference Architecture which enables the construction of scalable, reliable, interoperable, and secure process automation systems. The latest release, which is a Preliminary Standard of The Open Group, has further emphasis on standardized system configuration portability to significantly reduce capital cost and time investment for end-users. With these capabilities, end-users can easily exchange equipment without being tied to a single vendor or requiring individual configuration parameters to be written in different operating languages.
With their standard moving from interoperability to portable configurations, leaders told me that the next release will expand on this portability theme.
Bedrock Automation integrates Flow-Cal Flow Measurement into Open Secure Automation (OSA) Platform.
Speaking of both software-defined and open, Bedrock Automation Founder, CEO, and CTO Albert Rooyakkers explained its extension to the “Open Secure Automation (OSA)” platform with the addition of Flow-Cal algorithms “bringing oil and gas measurement and custody transfer securely into the digital age.” This was essentially a software addition to the platform to bring a new twist on flow computer functionality.
The new OSA +Flow family embeds industry-leading Flow-Cal measurement applications. Flow-Cal’s software has long been the industry’s choice for flow measurement and production-accounting data. Affirming Flow-Cal’s stature is the fact that the American Petroleum Institute (API) has selected it to develop, support, and distribute its standard flow measurement calculations.
The OSA +Flow software has been incorporated across all Bedrock controllers providing scalability for PLC, RTU, or DCS flow control requirements at custody transfer stations, separators, and other oil and gas production facilities. These solutions include full support of multi-drop serial, Ethernet, and HART for Coriolis, ultrasonic, and smart transmitters.
The system API compliant library, OPC UA, Inductive Automation software, MQTT, as well as software-defined I/O.
Diamanti Accelerates Energy and Service Organizations’ Adoption of AI/ML
AI and ML applications often leverage GPU processing for training models and they benefit from containers and Kubernetes—an open source container project. However, these processes are often complicated to adopt and run at scale. With the recent announcement of GPU support in the Diamanti AI/ML platform, enterprises have an easier on-ramp to managing large-scale containerized workloads under Kubernetes.
“We’re pleased to share the early customer traction we are seeing on our newest solutions in a wide range of industries including energy, services and more,” said Tom Barton, CEO of Diamanti. “These customers are validating state-of-the-art technologies internally while also benefiting from the reduced physical footprint and cost-savings that come with the Diamanti AI/ML platform.”
The new solution, announced in late 2019, is in early access today and fully supports Nvidia’s NVLink technology for higher performing workloads, as well as Kubeflow, an open source machine learning framework for Kubernetes that provides highly available Jupyter notebooks and ML pipelines. Combined with Diamanti’s Kubernetes control plane, this allows customers to deliver highly scalable environments for performance-intensive AI/ML workloads, accelerating model development and training.
A major energy company turned to Diamanti for a new workload leveraging AI/ML for optical character recognition (OCR) to scan invoices. The customer needed to scan more than 15,000 invoices a day. The legacy infrastructure could not keep up with the demand and eventually accrued a backlog of more than 200,000 invoices. Deploying the Diamanti solution with GPU support eliminated that backlog within hours.
Edge – 5G
As the other influencers at an HPE event told me once, “Gary, everything you do is the edge.” So it is not surprising that I had many conversations about the Edge. But 5G technology was also on many minds. The consensus opinion–5G will drive decision making to the edge.
As an example of edge at the Forum, here is an announcement from Opto 22. For as long as I’ve known the company, it continues to push the latest IT technologies mashed up with control and automation. This product release highlights its pioneering role in IoT.
Industrial automation manufacturer and industrial internet of things (IIoT) developer Opto 22 announced groov RIO, a family of intelligent, distributed input/output (I/O) for IIoT and automation applications. groov RIO represents a first-in-class solution for its ability to quickly connect traditional wired switches and sensors directly to Ethernet networks, software applications, and cloud platforms without intermediary control or communication hardware, such as PLCs, PACs, or PCs.
The first shipping version of groov RIO is the GRV-R7-MM1001-10, a standalone, 10-channel, multi-signal, multifunction I/O unit for signals including thermocouples (TCs), integrated circuit temperature devices (ICTDs), voltage inputs, current inputs, millivolt inputs, discrete DC inputs, self-wetting discrete inputs, discrete DC sinking outputs, and Form C mechanical relays. In addition, two channels provide special features like pulse counting, on- and off-time totalization, software latching, frequency measurement, and more. GRV-R7-MM1001-10 is completely standalone and software-configurable through a browser-based interface.
“When we designed groov RIO, we were looking for ways to democratize I/O data, because that’s what the IIoT is all about,” said Vice President of Product Strategy at Opto 22, Benson Hougland. “Although groov RIO can be used as remote I/O with our groov EPIC system or another control system, we also wanted it to operate autonomously, facilitating direct connection between I/O signals and databases, business software, or cloud IoT platforms.”
GRV-R7-MM1001-10 supports 12 different types of field I/O circuits. It also provides no-hassle, enclosure-free installation with multiple power options, including standard 802.3af Power-over-Ethernet (PoE); an extended operating temperature range; and UL Hazardous Locations and ATEX approvals.
Once installed, groov RIO can be independently managed and configured through browser-based tools. Per-channel I/O type and signal-processing options through groov Manage eliminate the need for a master control unit, and support for standard enterprise network services like DNS, DHCP, and VPN facilitates network connectivity. Embedded communication options range from efficient data publishing with MQTT Sparkplug to advanced signal processing, data aggregation, and transactions with databases and web services, using the low-code Node-RED environment and runtime.
Data —> Action
It’s all about data they all say. But when I talked with Mike Brooks who is now advising at AspenTech, he counseled, “Not too much data.” The action is in using data, not collecting it. Therefore the drawback (indeed, failure?) of data lakes. Too much storage, not enough usability. AspenTech exemplifies using Machine Learning not just to say they are in AI, but to find usable information for the companies to use to improve operations.
Collaboration – Partnerships
The Eclipse Foundation and OPAF exemplify collaboration and partnerships. Inductive Automation has community as a strategic initiative. Both founder Steve Hechtman and chief strategy officer Don Pearson highlighted it at last year’s Ignition Community Conference.
This announcement highlights community along with edge and other trends. Inductive Automation announced improvements to three products and a new development resource within Ignition by Inductive Automation. Ignition is an industrial application platform with tools for building solutions in human-machine interface (HMI), supervisory control and data acquisition (SCADA), and the Industrial Internet of Things (IIoT).
The solutions include:
- New and improved products for Ignition Edge.
- An expansion of the Ignition Onboard program.
- Improvements to the Ignition Perspective Module.
- A new, free resource for developers: Ignition Exchange.
Ignition Edge will soon have three new products. Ignition Edge is a line of lightweight, limited, low-cost Ignition software solutions designed for embedding into field and OEM devices at the edge. They allow organizations to extend data collection, visualization, and system management to the edge of the network. With the new products coming soon, the lineup will include Ignition Edge Panel, Ignition Edge Compute, Ignition Edge Sync Services, Ignition Edge EAM (Enterprise Administration Module), and Ignition Edge IIoT.
The Ignition Onboard program now has easier access to industrial hardware that comes with Ignition already installed, configured, and licensed. Numerous device manufacturers are embedding Ignition and Ignition Edge into their devices — including Advantech, Moxa, OnLogic, Opto 22, and ORing.
The Ignition Perspective Module lets users easily build mobile industrial applications in HTML5 for monitoring and control of their processes directly from their mobile phones.
A significant part of the Inductive Automation strategy is to promote community among its customers and partners. The development has been ongoing for some time culminating into Ignition Exchange — a new, online space where developers can get free Ignition resources provided by Inductive Automation and the Ignition community. These resources can save time for developers.
Software Defined
OPAF, Bedrock Automation- as in take hardware platform add flow metering, exemplify the trend toward software-defined hardware.
Machine Learning
I discussed ML in relation to AspenTech for decision making. Perhaps the industry is moving past the SciFi “artificial intelligence” part of the technology to emphasize real use cases deployed today.
Operations
To name a trend “operations” may sound archaic, but many conversations moved from technology to solving real problems for customers. This announcement from AVEVA exemplifies that trend.
AVEVA unveiled its new Discrete Lean Management software. The new offering improves operational efficiency through the digitalization of lean work management for both manual and automated production lines. AVEVA’s quick-to-deploy and easy to use digital tools enable access to production information, KPIs and notifications on dashboards, workstations and mobile devices to improve overall equipment and labor effectiveness, and to facilitate data-driven continuous improvement.
AVEVA Discrete Lean Management is designed to address the issues faced by operating manufacturing plants still using paper-based systems for lean and work order management, work instructions and data collection procedures. It enables physical records to be replaced with digital tools that mitigate the risk of manual processes and provides real time visibility into production performance allowing team collaboration in response to production issues.
The AVEVA Discrete Lean Management software solution is used in Schneider Electric’s manufacturing plants and has been successfully deployed in more than 70 smart factories globally resulting a 10% productivity increase due to downtime mitigation and 70% improved response-time due to automated escalation of production issues.
I actually visited one of the plants in the deployment—one in Lexington, KY. It was an excellent example of using software tools to enhance a lean process rather than getting in the way.
MQTT
MQTT was mentioned all over the conference. This is a data transport technology. It is usable for both OPC UA and for Sparkplug. Some companies touting their use of the technology include:
Security
I didn’t have as many security conversations as the past few years, but I did chat with some PAS Global executives, and the company announced several new products, along with some new branding.
PAS, now PAS Global, keeps building on the platform of alarm management and safety and its ability to see what is on the process plant’s network assuring integrity of the process control system.
While at ARC Forum, company executives stressed industrial operations must increase focus on cybersecurity while maintaining continuous vigilance on safety. Stated simply, organizations need to ensure OT integrity in the face of unprecedented opportunity and risk. PAS has introduced new and updated products to optimize the integrity of industrial assets and reduce cyber risk, improve process safety and reliability, and ensure OT data health.
PAS Cyber Integrity prevents, detects, and remediates industrial cyber threats. Version 6.5 introduces an enhanced user experience for OT asset inventory information and data collection and transfer. This release also provides support for multiple integration methods (REST API, Syslog, SQL, CSV, SDK), integration with Darktrace, and Microsoft Windows event analytics;
PAS PlantState Integrity Version 8.7 introduces enhancements to Independent Protection Layer (IPL) Assurance that include sensor monitoring and voting, analysis filtering, and process trip reporting.
PAS Decision Integrity enables trusted data for decision-making. Version 1.0 leverages capabilities from PAS Automation Integrity and adds support for OT data health monitoring (data chain accuracy and visualization) and data lake enrichment.
These new product releases will be generally available by the end of March.
