Industrial Analytics of Things

Definition

The "Industrial Analytics of Things" (IAoT) is the analytical component of "Industrial Internet of Things" (IIoT). In the industrial setting, device and sensor technologies are rapidly becoming more intelligent and directly "on the net", bringing us more data from everywhere and needing to go anywhere.

"Industrial Analytics of Things" uses this data about your operations including materials, process conditions, product and production performance, customer feedback from the web, product and brand sentiment, everything you need no matter where it is located. We capture, validate, clean and filter, analyze, predict, adapt and optimize enterprise performance in real-time. Real-time optimization is proven to reliably improve performance 5-20% and sometimes much more. To deliver the "Industrial Analytics of Things", we are creating a new high performance distributed computing architecture that captures all this streaming industrial "big data" at its source and delivers awareness, understanding and predictive performance everywhere, anywhere, all the time.

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Value to Your Organization

Real-Time Optimization = 5-20% to Your Bottom Line

We provide real-time optimization world-wide and we have historically achieved a 5-20% improvement in performance, regardless of the operation. In some cases a 500% increase. Other times we have taken a customer from a 40% pass rate to an award winning 100% perfect product every time. Regardless if you are a large or small company, this gives you a sizable boost to your bottom line. Other benefits include:

• Clean and Validated Data So You Can Trust It To Manage Your Organization
• Situational Awareness and Visibility Across the Organization
• Understanding of What Information is Valuable and Useful
• Cause and Effect Identification in Real-TIme to Eliminate Defects and Problems
• Increased Customer Satisfaction
• Lower Operating Costs
• Enhanced Collaboration and Shared Understanding Across the Organization

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Broad, Big and Widely Distributed Real-Time Data

Requires a Highly Distributed, Compute at the Source, Integrate Data as Needed, Architecture

More than ever, industrial operations are producing operational data in larger volumes in real-time and with the "Industrial Internet of Things" it's coming from everywhere; controllers, sensors, test equipment, all sorts of devices found within your unit operations, plants, regions, labs, maintenance shops to name a few. In the future, fewer sensors will be hard-wired to control systems, but will become a shared resource of streaming data. This data needs to be captured, stored, validated, cleaned, synchronized, related, visualized, analyzed and shared to enhance your product, process and business performance.

The best way to handle all this data is to put analytics close to the source and aggregate it as needed. Some call this "Fog" computing, a low level cloud. Some call it "Warehouse Scale Computing", but here the "warehouse" is your entire enterprise. The tenents of such a system are:

• Access, validate and store data at or near its source but accessible from anywhere
• Collect only data that is useful: Right-size your sensing and collection
• Perform analytics insitu, close to the operation for high speed reaction times
• Reduce "Big Data" and bandwidth by not sending all data to a central "Cloud"
• Aggregate and analyze related data where they intersect:
• MES Workcenter relating process, materials and performance
• Across the Plant to correlate and coordinate across workcenters and departments
• Intra-Enterprise to correlate producer-consumer intra-organizational relations and learning across similar operations in your plants, laboratories and pilot plants around the world
• Inter-Enterprise to link to your suppliers and to those you supply because your supplier's materials characteristics are a part of your product

Architecture: Real-Time Large Scale Distributed Computing

What we need is to be able to place computing where it is needed, and performant, suited for the purpose, sitting where it needs to be, at a workcenter, inside a control panel, at a desk, in a lab, in a rack in a data center, anywhere and everywhere, all sharing related data to understand and improve your performance. While located throughout your organization, the system operates as a single unified resource, a distributed cloud that integrates with centralized clouds as they contain market and customer feedback, desires and behaviours that reflect product performance in the eyes of the customer. The characteristics of an Industrial Analytics of Things system are:

• A Highly Distributed Concurrent Computing (HDCC) System
• A peer-to-peer mesh of computational nodes in a virtual hierarchical structure that matches your organization
• Communicates with smart sensors, controllers, historians, quality and materials control systems and others as peers
• Runs on affordable, off the shelf computing technologies
• Supports multiple operating platforms; Unix, Windows, Mac
• Employs simple, fast and standardized IoT internet protocols (TCP/IP, Sockets, etc.)
• Browser user experience, after all, it is the "Industrial Internet of Things"
• Built on field-proven high performance distributed computing technologies

Capturing, historizing, validating, cleaning and filtering, integrating, analyzing, predicting, adapting and optimizing performance at all levels and across the enterprise in real-time requires High Performance Computing (HPC) power. This does not necessarily mean high expense, as commercial off the shelf standard PCs with the power of a typical laptop computer will suffice and the software running the system need not be expensive.

To architect such a system, we draw upon the experiences, architectures, tools and successes of such computing giants as Google, Amazon, YouTube, Facebook, Twitter and others. They have created robust high performance computing architectures that span global data centers. They have provided development tools and languages such as Google's GO (golang) that are well suited for high speed concurrent distributed processing and robust networking and web services. Having a similar need, but more finely distributed, we can adopt similar high performance computing architectures to deliver and share results where they are needed in real-time.

Pulling It All Together

And so by standing on the shoulders of giants, and by drawing on our decades of experience in industrial analytics, we are assembling the "Industrial Analytics of Things" to deliver outstanding performance for your organization.

Join us in this journey. We are actively seeking commercial / industrial alpha and beta testers. Be a part of something new and exciting! Give us a call at 1-281-760-4007 or send us an email

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