Digital Twin Alliance to Address Complex Digital Transformational Challenges

In brief: Three Organizations Combine Expertise to Bring Digital Twins to Life, Create Added Value, and Deliver Support Across the Asset Lifecycle

The idea of an open system for data flow from engineering through construction to startup to operation & maintenance, and perhaps even to decommissioning has intrigued me for years. I have worked with MIMOSA and its Open Industrial Interoperability Ecosystem for many years. Check it out.

For the most part, suppliers have been a bit slow to this game. The way of the world is that automation vendors never liked the “open” part, since their design emphasizes tight integration of as many parts as possible under their proprietary umbrella.

An ecosystem is one thing, and a partnership is another. Sometimes companies announce partnerships with great flourish and publicity only to see the great promise wither from neglect. Sometimes end users (owner/operators) reap significant benefit.

With that background, I approach the announcement of a partnership. I like the idea, but execution and sustainability will be proof of the strength of this partnership. Note that two of the companies are sort of like “conjoined twins” joined at the hip.

From the announcement:

DORIS Group, global Engineering and Project Management company in the energy industry, Schneider Electric, supplier of products and solutions for digital transformation of energy management and automation, and AVEVA an engineering and industrial software supplier, have agreed to develop a strategic partnership to deliver Digital Twin technology for the upstream oil and gas markets.

These new solutions will support the goals of oil & gas organizations to improve asset performance, increase sustainability and maximize return on capital on projects.

The three companies will combine offerings to bring engineering capabilities, an asset lifecycle software solution and digital specialization in order to create a fully formed digital twin to serve as a backbone for improving performance for the upstream sector. The new solution will:

  • Bring new assets on stream faster through the use of cloud-enabled software that improves collaboration and increases engineering efficiencies
  • Deliver enhanced safety leading to better business outcomes
  • Improve traceability through a single point of accountability
  • Enable remote operations and production assurance through a fully functional Living Digital Twin that mirrors all aspects of the operating asset

Oil & Gas owner operators have struggled to go digital due to the lack of a structured offering and orchestration as no single vendor currently delivers what is required to achieve this. Large amounts of data of various types, from different sources is another challenge they face, often leading to data inaccuracy and incompatibility, as well as difficulties in organizing that data and identifying trends.

Similarly, the oil & gas sector is under considerable pressure to quantify, track and reduce CO2 emissions as well as reduce overall pollution – this can be even more difficult with limited monitoring, no established method and no data-driven decision making.

Together, DORIS, AVEVA, and Schneider Electric will offer a structured digital and collaborative solution across the lifecycle of projects that will help oil & gas owner operators address many of these challenges.

Christophe Debouvry, CEO of DORIS Group, stated, “DORIS Group is excited to be strategically partnering with Schneider Electric and AVEVA in this unique venture which will allow us to accelerate the building out of our digital transformation strategy. Combining our complementary expertise will go a long way to providing a powerful enabler to offer our customers embarking on their digital transformational journeys with optimized solutions throughout their assets lifecycle.”

Craig Hayman, CEO AVEVA, also commented, “Leaders driving the next wave of transformation are moving quickly and that’s why this partnership with Schneider Electric and DORIS Group is so opportune. Our common aim is to support organizations on their digital journey especially in the current environment, helping them accelerate the use of digital technology, realize the value of a digital twin and also work towards a more sustainable future. It’s never been easier to begin a digital transformation program, as access to cloud computing, great connectivity, a merged edge and enterprise combined with analytics and machine learning, means that the ability to digitally drive productivity improvements into the industrial world is now unprecedented.”

Christopher Dartnell, President Oil & Gas and Petrochemicals at Schneider Electric, commented, “This partnership is in line with Schneider Electric’s objectives around Digitization and Energy Transition and we will bring our expertise in both energy and process efficiency to the industry. Our goal is to support customers looking to adopt a digital twin model, by offering our experience to facilitate the overall digital transformation for our clients enable them to improve lifecycle performance and safe operations while also making their operations more sustainable.”

Schneider Electric Finally Completes Industrial Software Sale (sort of)

Schneider Electric Finally Completes Industrial Software Sale (sort of)

A little consolidation in the industrial software space. Remember when Schneider Electric was shopping its software division a couple of years ago and came up with a reverse acquisition with AVEVA? And the deal fell apart almost a year ago?

Well, it seems that Schneider spent the year internally restructuring such that it could pull off this weird financial transaction. Announced Monday evening, the two companies have reached an agreement to ship SE software to AVEVA forming a new company with SE as a 60% owner and AVEVA holds the other 40%. Plus AVEVA shareholders get some cash in the deal.

Management touts the transaction as having a clear and compelling business logic.  Reasons include building a “global leader in engineering and industrial software”, covering entire asset lifecycle management, and positioned for further acquisitions.

I’ve believed that Schneider would sell off its software businesses ever since the deal for Invensys was announced. Some venture capitalists have talked with me about potential acquisitions. Evidently no one wanted to buy it. I thought maybe Wonderware could make it on its own as a spinoff, but there probably wasn’t enough financial payoff for Schneider with that sort of deal.

However, this also isn’t a clear divestiture. One is left wondering what the future will bring in a couple of years when this transaction matures.

The Management of the Enlarged AVEVA Group will be comprised of:

  • Key members of the existing executive management team of AVEVA, namely Dave Wheeldon (Chief Technology Officer and currently also Deputy Chief Executive Officer) and Steen Lomholt-Thomsen (Chief Revenue Officer) are expected to remain in place following completion;
  • Ravi Gopinath, currently Executive Vice President of the Schneider Electric Software Business, will be appointed as Chief Operating Officer of the Enlarged AVEVA Group. He will report to the Chief Executive Officer of the Enlarged AVEVA Group; and
  • David Ward will continue in his current role as Chief Financial Officer of AVEVA, until a new Chief Executive Officer is appointed. Following such appointment it is intended that David Ward will be appointed to the role of Company Secretary of the Enlarged AVEVA Group.

I received this from Vertical Research Partners analyst Jeff Sprague:

  • Deal Structure Overview – Schneider Electric announced today the combination of its industrial software business and AVEVA to create a global leader in engineering and industrial software. On completion, Schneider will own 60% of the combined new AVEVA group while existing AVEVA shareholders will have 40% equity ownership. However, SU is contributing a little over 60% of the proforma EBITA in addition to a £550MM payment, and allowing AVEVA to distribute a £100mm dividend to AVEVA shareholders at or around completion. Schneider will benefit from unlocking the higher trading multiple of its Software business outside of the Group structure, in addition to future synergies (unquantified). We estimate the transaction creates 42 euro cents of value to SU’s stock price. Closing is expected to be at or around end of 2017.
  • Strategic Rationale – The combined company will provide engineering services and industrial software, with combined revenues of £657.5mm and adjusted EBITA of £145.8mm for the financial year ended March 2017. The combined portfolio will cover process simulation to design and construction to manufacturing operations/ optimization. As shown below, AVEVA is very strong in the front end design and engineering work while SU is strong in O&M and asset optimization. The company noted an ability to create a more streamlined solution as it will control both ends of the spectrum. Management also indicated plans to scale up with future M&A. AVEVA will also enhance the value proposition of Schneider’s existing IOT platform (ExoStructure).

The only interest I’ve seen with total asset lifecycle management is with the OIIE platform from MIMOSA (download whitepaper from my site). A few end-user companies have shown interest in that, but I don’t know that the combined companies will offer much of a competitive advantage in that regard. That would require strong management bringing the disparate parts together into a whole.

For example, I only point to GE Digital whose recent public woes with the Predix system point to the difficulties of software integration.

Schneider Electric Finally Completes Industrial Software Sale (sort of)

Standards and Interoperability Drive Innovation and Adoption

Standards that enable interoperability drives innovation and industry growth.

For some reason, technology suppliers tend to avoid standards at almost all costs—and the costs can be substantial in terms of losing market share or momentum—in order to build a “complete” solution all their own.

One reason beyond the obvious is that standards creation can be a time-consuming and tedious process.

Where would we be without standardized shipping containers, standardized railway tracks and cars, standardized Ethernet and the ISO stack, and more?

I’ve been working with OPC Foundation and am finishing a white paper about the technology of combining two standards—OPC UA and Time Sensitive Networking. This is going to be huge some day.

I also work with a standards organization known as MIMOSA which has promulgated an information standard for asset lifecycle management.

These are key technologies that can move industry forward

I ran across this article by Ron Miller on TechCrunch about standards in another area—cloud services. This article discusses Amazon Web Services (AWS).

AWS just proved why standards drive technology platforms

Quoting from Miller:

When AWS today became a full-fledged member of the container standards body, the Cloud Native Computing Foundation, it represented a significant milestone. By joining Google, IBM, Microsoft, Red Hat and just about every company that matters in the space, AWS has acknowledged that when it comes to container management, standards matter.

AWS has been known to go the proprietary route, after all. When you’re that big and powerful, and control vast swaths of market share as AWS does, you can afford to go your own way from time to time. Containers is an area it hasn’t controlled, though. That belongs to Kubernetes, the open source container management tool originally developed inside Google.

AWS was smart enough to recognize that Kubernetes is becoming an industry standard in itself, and that when it comes to build versus buy versus going open source, AWS wisely recognized that battle has been fought and won.

What we have now is a clearer path to containerization, a technology that is all the rage inside large companies — for many good reasons. They allow you to break down the application into discrete manageable chunks, making updates a heck of a lot easier, and clearly dividing developer tasks and operations tasks in a DevOps model.

Standards provide a common basis for managing containers. Everyone can build their own tools on top of them. Google already has when it built Kubernetes, Red Hat has OpenShift, Microsoft makes Azure Container Service — and so forth and so on.

Companies like standards because they know the technology is going to work a certain way, regardless of who built it. Each vendor provides a similar set of basic services, then differentiates itself based on what it builds on top.

Technology tends to take off once a standard is agreed upon by the majority of the industry. Look at the World Wide Web. It has taken off because there is a standard way of building web sites. When companies agree to the building blocks, everything else seems to fall into place.

A lack of standards has traditionally held back technology. Having common building blocks just make sense. Sometimes a clear market leader doesn’t always agree. Today AWS showed why it matters, even to them.

 

Schneider Electric Finally Completes Industrial Software Sale (sort of)

Another IoT Platform This One With Machine Learning

When it comes to the Internet of Things, it is becoming all about the platform. Every week is a new one. Most are built by suppliers in an attempt to either bring in everyone’s data to their systems, e.g. Microsoft, SAP, Exosite, Cisco, Siemens, GE, etc.

One platform is designed to be essentially built only with standards. As far as I know, I’m the only one writing about it–and have been the only one for at least 10 years as it has developed. That is the Open Industrial Interoperability Ecosystem (OIIE) promulgated by MIMOSA.

Another platform assembled with the leadership of Dell EMC’s IoT team is open source dubbed EdgeX Foundry.

This announcement from FogHorn Systems adds the nuance of machine learning to its platform.

FogHorn Systems today announced the availability of Lightning ML, the newest version of its Lightning edge intelligence software platform for the Industrial Internet of Things (IIoT). Lightning ML is now the industry’s first IIoT software platform with integrated machine learning capabilities and universal compatibility across all major IIoT edge systems.

Accenture predicts that IIoT can add $14.2 trillion to the global economy by 2030. However, industrial environments present a challenge to status quo methods for data collection and analysis.

“The money and time required to move massive amounts of machine data to the cloud for
analysis, only to send the results back to the edge, often makes little sense,” said Mike
Guilfoyle, Director of Research and Senior Analyst at ARC Advisory Group. “In many instances
cloud computing won’t be practical, necessary, or desirable. The reality is that edge intelligence is critical to a successful overall analytics strategy.”

“FogHorn is accelerating the pace of innovation in edge computing by not just democratizing analytics but by making machine learning accessible to industrial operators,” said FogHorn CEO David C. King. “The addition of FogHorn Lightning ML is a monumental leap forward indelivering on the promise of actionable insights for our IIoT customers. In the initial launch of FogHorn’s Lightning platform, we successfully miniaturized the massive computing capabilities previously available only in the cloud. This allows customers to run powerful big data analytics directly on operations technology (OT) and IIoT devices right at the edge through our complex event processing (CEP) analytics engine. With the introduction of Lightning ML, we now offer customers the game changing combination of real-time streaming analytics and advanced machine learning capabilities powered by our high-performance CEP engine.”

Machine Learning at the Edge

Lightning ML brings the power of machine learning at the edge in three groundbreaking ways:

1. Leverages existing models and algorithms: Industrial customers can seamlessly plug in and execute proprietary algorithms and machine learning models on live data streams produced by their physical assets and industrial control systems.

2. Makes machine learning OT-accessible: Non-technical personnel can use FogHorn’s tools to generate powerful machine learning insights without the need to constantly rely on in-house or third party data scientists.

3. Runs in tiny software footprint: Lightning ML enables complex machine learning models to run on highly-constrained compute devices such as PLCs, Raspberry Pi systems, tiny ruggedized IIoT gateways, as well as more powerful Industrial PCs and servers. Even with the addition of advanced machine learning capabilities, the complete Micro edition of the Lightning ML platform requires less than 256MB of memory footprint.

“FogHorn’s breakthrough edge computing technology brings the power of big data analytics and machine learning to the OT (operations technology) world,” said Casey Taniguchi, General Manager and Head of Business Development Center at Yokogawa Electric Corporation, a global leader in process and industrial automation systems. “The introduction of support for ARM32 processors, advanced data pre-processing capabilities and streaming analytics accomplished in a tiny footprint, along with seamless on-prem/cloud integration represents a major step forward in speeding the adoption of FogHorn’s technology in a wide variety of IIoT markets and industrial use cases. We look forward to working closely with FogHorn to incorporate all of these groundbreaking technologies into Yokogawa’s family of advanced industrial automation solutions.”

Comprehensive Support for IIoT Hardware

While the first Lightning release supported all x86-based IIoT gateways and OT systems, Lightning ML also supports ARM32 — one of the most widely used processors in OT control systems (like PLCs and DCSs) and the newest generation of small footprint Raspberry Pi derivative IIoT gateways.

“Fog computing requires a variety of different compute performance levels, all of which can be enabled by the flexible, low-power ARM architecture,” said Rhonda Dirvin, director of IoT and embedded, Business Segments Group, ARM. “FogHorn Systems’ Lightning platform supports and validates ARM-based solutions in OpenFog applications, and will enable new efficiencies and applications in the industrial edge computing space.”

On-Premise Centric and Cloud Agnostic

The FogHorn Lightning ML software platform can run entirely on premise or connect to any private cloud or public cloud environment. This gives customers maximum flexibility in selecting the best deployment model in terms of IT infrastructure, security policy and cost.

Designed for Operational Technology

FogHorn Lightning ML has been specifically designed to empower OT users through a simple drag-and-drop authoring tool that abstracts away the complexities of an underlying IIoT deployment, allowing operators to focus on translating their domain expertise into meaningful analytics and machine learning insights.

“OT staff are domain experts in their respective industrial environments, but not necessarily experts in edge computing and advanced IT,” said FogHorn CTO Sastry Malladi. “By giving them intuitive tools to automate, monitor and take action on their industrial data in real-time, operators can enhance situational awareness, prevent process failures and identify new efficiencies that lead to huge business benefits. This is a very different approach from other IT-centric solutions that fail to leverage the tribal knowledge of key OT experts.”

FogHorn develops “edge intelligence” software for industrial and commercial IoT application solutions.

Siemens User Conference Highlights Connectivity, Visibility

Siemens User Conference Highlights Connectivity, Visibility

Siemens Automation held its annual Users Conference the end of June at the Boca Raton Resort in Florida. Digitalization comprised the underlying theme, however connectivity technologies highlighted the important announcements and discussions.

MindSphere holds the top place as the most important Siemens technology at this time. Users and Siemens professionals highlighted two use cases at the conference both centering on condition monitoring / predictive maintenance.

The other connectivity announcement concerned PCS 7, the Siemens DCS. The company unveiled new I/O featuring Profinet connectivity. The new, denser I/O includes a user-configurable product, as well as traditional digital and analog modules. Ethernet connectivity featuring Profinet held center stage in the press announcement.

Siemens introduced MindSphere to me at Hannover 2016. Its evolution has been swift. Now dubbed an Internet of Things platform, it includes a set of APIs and libraries. It includes an “App Store” open to 3rd party developers in addition to Siemens apps. If you are a developer, just register and app and pay a royalty based on data or connections.

MindSphere placed in context is similar to what I’ve seen from Cisco, Dell EMC, GE, Microsoft, and SAP. I’m sure there are more and that we’ll see more in the future. Dell EMC’s platform is open source. MIMOSA, an industry standards organization provides a similar platform called the OIIE based on standards containing no proprietary components.

All of these platforms are important for maintenance and reliability professionals, as well as for plant management, engineering, and operations because of the increased data and visibility into operations and assets. This will result in improved planning, more efficient operations, and increased percentage of uptime.

Components of the platform include:
• MindSphere Apps – Siemens and 3rd party ; data analytics
• MindSphere Sphere – Azure, SAP, AWS, etc.
• MindSphere Connect – open standards, right now OPC UA, gateway, integrated with S7, build your own connectivity

 

 

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