Vision Inspection Powered by AI

Vision Inspection Powered by AI

Artificial Intelligence, or AI, is not necessarily the dystopian technology portrayed in books and movies. Although neither artificial or intelligent, AI can be a powerful tool in the engineer’s kit.

Recently Carl Palme of Neurala chatted with me introducing the company and what it means by AI in its vision systems. We both have some sheet metal work in our backgrounds, so we found common cause with one of the powerful applications—finding small surface anomalies.

There is also company news. In short:

  • IHI Corporation Selects Neurala to Enable Industrial Visual Inspection and Analysis Powered by AI
  • One of the Largest Global Heavy-Industry Manufacturers Partners With Leader in Automated Visual Inspections to Build Vision AI-Powered Industrial Solutions

AI-powered visual inspection pioneer Neurala announced a partnership with IHI, one of the largest manufacturers in the world.

IHI is a leading producer of aircraft engines and turbochargers for vehicles and industrial machines, along with additional transport-related machinery and more. Neurala’s automated visual inspection platform will be deployed as a key component of IHI’s workflow, improving manufacturing optimization and enabling more efficient industrial inspections.

“Automation is an area of critical focus as we further strengthen our reputation as the leading manufacturer of transport-related machinery worldwide,” said Ms. Nobuko Mizumoto, Director of IHI Corporation. “Today, we are collecting data on our workflow that needs to be carefully analyzed. AI-assisted data analysis is the future of manufacturing processes, and Neurala has the industrial and manufacturing inspection expertise we require in an AI solution. As we lead IHI into Industry 4.0, we are proud to partner with Neurala to deploy a reliable AI that can function in settings that are subjective and change rapidly, without requiring any downtime on our production lines.”

IHI will leverage Neurala’s automated visual inspection platform to review product and workflow processes, cementing its reputation as a leader in safety and efficiency. AI-powered inspections allow manufacturers to accelerate new initiatives without sacrificing a gold standard of quality workmanship. IHI will use Neurala’s Brain Builder, the first cost-effective AI tool that allows users to build, deploy and analyze custom vision AI solutions with instant feedback on performance. Brain Builder simplifies the process and reduces the time to deployment in subjective settings, using on-the-fly learning to increase accuracy as the user adds data.

“We are thrilled to partner with IHI as we illustrate the critical role AI will play in manufacturing, improving efficiency in a field in which optimization is essential,” said Massimiliano Versace, co-founder and CEO of Neurala. “We look forward to building upon our strong presence in the APAC region through an industry leader like IHI. IHI selected Neurala to bolster its offerings as the industrial sector continues to evolve; our partnership will demonstrate the value of implementing AI to solve challenges of visual inspection on factory floors and to improve automation.”

Neurala is the company behind Brain Builder: a SaaS platform that dramatically reduces the time, cost and skills required to build and maintain production-quality custom vision AI solutions. Founded in 2006, Neurala’s research team invented Lifelong-DNN (L-DNN) technology, which reduces the data requirements for AI model development and enables continuous learning in the cloud or at the edge. Now, with customers in the industrial, drone, robotics, and smart devices verticals, Neurala’s technology has been deployed on 53 million devices globally.

Vision Inspection Powered by AI

Camera-Based Quality Control System for Flat Sheet Industries

Years ago I dabbled in machine vision integration. It was fun and creative. My customers and I did some pretty cool quality control applications. So I maintain a liking for the technology even though the price of the hardware plummeted and ease-of-use skyrocketed. So, I bring you this interesting news.

Honeywell is collaborating with Papertech to develop and market TotalVision, a connected, camera-based detection system for the flat sheet industries. The system enables customers to identify and resolve defects on the production line, improving quality and efficiency. The fully integrated total quality control solution is designed for flat sheet and film processes in which surface detection and production break monitoring capabilities are critical for competitive success. This new solution is designed for paper, pulp, tissue, board, extruded film, calendaring, lithium-ion battery, copper and aluminium foil producers.

Combining Honeywell’s ExperionMX technology with market-leading Papertech’s TotalVision defect detection and event capturing capabilities, the solution provides a single-window operating environment for all aspects of process and quality control. Customers benefit from faster root cause determination of runnability and quality problems, thereby saving significant time in lost or downgraded production. When integrated with connected offerings such as Honeywell QCS 4.0, system data and analytics can be accessed anytime, anywhere, from any device.

“Honeywell represents an ideal collaborator for Papertech as our industry-leading WebInspector WIS and our WebVision web monitoring system (WMS) single platform TotalVision camera system seamlessly integrate with Honeywell’s quality control systems for a range of industries,” said Kari Hilden, CEO of Papertech Inc. “We look forward to working with the global Honeywell team and their customers.”

Honeywell will continue to support existing camera system users with parts and services, while offering an easy migration path to the new solution. Given the collaborative nature of the agreement, customers can choose to take a single party, single-window approach or to engage with Honeywell and Papertech separately.

“As the world moves from plastic to biomaterial-based packaging, and from hydrocarbon-based transportation to electric vehicles, flat sheet producers are under increased pressure to ensure output consistently meets a variety of performance and safety requirements,” said Michael Kennelly, global business leader for sheet, film and foil industries, Honeywell Process Solutions. “By bringing together Honeywell’s core strengths of measurement, control, connected applications and services in flat sheet production with Papertech’s leadership in web monitoring and inspection systems, we uniquely provide customers with that capability along with industry-beating lifecycle costs.”

Papertech is the global industry-leading machine vision system supplier for a range of web-based production lines with more than 1200 TotalVision installations in 42 countries. It is part of the IBS Paper Performance Group, a company with a more than 50-year history in delivering papermakers a full range of proven machine efficiency and product quality optimization solutions.

For more information visit Honeywell Quality Control Systems and Papertech TotalVision solutions.

Vision Inspection Powered by AI

The Salesforce Economy Bolsters Manufacturing Cloud

Salesforce recently began reaching out to me. I found a (to me) surprising connection to industrial / manufacturing applications beyond CRM and the like. In general, more and more applications are moving to the cloud. In Brief: New research finds The Salesforce Economy will create more than $1 trillion in new business revenues and 4.2 million jobs between 2019 and 2024. Salesforce ecosystem is on track to become nearly six times larger than Salesforce itself by 2024, earning $5.80 for every dollar Salesforce makes.

Financial services, manufacturing and retail industries will lead the way, creating $224 billion, $212 billion and $134 billion in new business revenue respectively by 2024.

Salesforce announced new research from IDC that finds Salesforce and its ecosystem of partners will create 4.2 million new jobs and $1.2 trillion in new business revenues worldwide between 2019 and 2024. The research also finds Salesforce is driving massive gains for its partner ecosystem, which will see $5.80 in gains for every $1 Salesforce makes by 2024.

Cloud computing is driving this growth and giving rise to a host of new technologies, including mobile, social, IoT and AI, that are creating new revenue streams and jobs that further fuel the growth of the cloud — creating an ongoing virtuous cycle of innovation and growth. According to IDC, by 2024 nearly 50 percent of cloud computing software spend will be tied to digital transformation and will account for nearly half of all software sales. Worldwide spending on cloud computing between now and 2024 will grow 19 percent annually, from $179 billion in 2019 to $418 billion in 2024.

“The Salesforce ecosystem is made possible by the amazing work of our customers and partners around the world, and because of our collaboration we’re able to generate the business and job growth that we see today,” said Tyler Prince, EVP, Industries and Partners at Salesforce. “Whether it’s through industry-specific extensions or business-aligned apps, the Salesforce Customer 360 platform helps accelerate the growth of our partner ecosystem, and most importantly, the growth of our customers.”

Because organizations that spend on cloud computing subscriptions also spend on ancillary products and services, the Salesforce ecosystem in 2019 is more than four times larger than Salesforce itself and will grow to almost six times larger by 2024. IDC estimates that from 2019 through 2024, Salesforce will drive the creation of 6.6 million indirect jobs, which are created from spending in the general economy by those people filling the 4.2 million jobs previously mentioned.

“The tech skills gap will become a major roadblock for economic growth if we don’t empower everyone – regardless of class, race or gender – to skill up for the Fourth Industrial Revolution,” said Sarah Franklin, EVP and GM of Platform, Developers and Trailhead at Salesforce. “With Trailhead, our free online learning platform, people don’t need to carry six figures in debt to land a top job; instead, anyone with an Internet connection can now have an equal pathway to landing a job in the Salesforce Economy.”

Industry Economic Benefits of the Salesforce Economy

Specifically, Manufacturing industry will gain $211.7 billion in new revenues and 765,800 new jobs will be created by 2024.

Salesforce’s multi-faceted ecosystem is the driving force behind the Salesforce Economy’s massive growth:

  • The global ecosystem includes multiple stakeholders, all of which play an integral part in the Salesforce Economy. This includes the world’s top five consulting firms, all of whom have prominent Salesforce digital transformation practices; independent software vendors (ISVs) that build their businesses on the Salesforce Customer 360 Platform and bring Salesforce into new industries; more than 1,200 Community Groups, with different areas of focus and expertise; and more than 200 Salesforce MVPs, product experts and brand advocates.
  • Launched in 2006, Salesforce AppExchange is the world’s largest enterprise cloud marketplace, and hosts more than 4,000 solutions including apps, templates, bots and components that have been downloaded more than 7 million times. Ninety-five percent of the Fortune 100, 81 percent of the Fortune 500, and 86 percent of Salesforce customers are using AppExchange apps.
  • Trailhead is Salesforce’s free online learning platform that empowers anyone to skill up for the future, learn in-demand skills and land a top job in the Salesforce Economy. Since Trailhead launched in 2014, more than 1.7 million Trailblazers have earned over 17.5 million badges; a quarter of all learners on Trailhead have leveraged their newfound skills to jump-start their careers with new jobs. Indeed, the world’s #1 job site, included Salesforce Developer in its list of best jobs in the US for 2019, noting that the number of job postings for that position had increased 129 percent year-over-year.
Vision Inspection Powered by AI

Supercomputing for the Exascale Era

Cray, an HPE company, held a panel discussion webinar on October 18 to discuss Exascale (10^18, get it?) supercomputing. This is definitely not in my area of expertise, but it is certainly interesting.

Following is information I gleaned from links they sent to me. Basically, it is Why Supercomputing. And not only computers, but also networking to support them.

Today’s science, technology, and big data questions are bigger, more complex, and more urgent than ever. Answering them demands an entirely new approach to computing. Meet the next era of supercomputing. Code-named Shasta, this system is our most significant technology advancement in decades. With it, we’re introducing revolutionary capabilities for revolutionary questions. Shasta is the next era of supercomputing for your next era of science, discovery, and achievement.

WHY SUPERCOMPUTING IS CHANGING

The kinds of questions being asked today have created a sea-change in supercomputing. Increasingly, high-performance computing systems need to be able to handle massive converged modeling, simulation, AI, and analytics workloads.

With these needs driving science and technology, the next generation of supercomputing will be characterized by exascale performance, data-centric workloads and diversification of processor architectures.

SUPERCOMPUTING REDESIGNED

Shasta is that entirely new design. We’ve created it from the ground up to address today’s diversifying needs.

Built to be data-centric, it runs diverse workloads all at the same time. Hardware and software innovations tackle system bottlenecks, manageability, and job completion issues that emerge or grow when core counts increase, compute node architectures proliferate, and workflows expand to incorporate AI at scale.

It eliminates the distinction between clusters and supercomputers with a single new system architecture, enabling a choice of computational infrastructure without tradeoffs. And it allows for mixing and matching multiple processor and accelerator architectures with support for our
new Cray-designed and developed interconnect we call Slingshot.

EXASCALE-ERA NETWORKING

Slingshot is our new high-speed, purpose-built supercomputing interconnect. It’s our eighth generation of scalable HPC network. In earlier Cray designs, we pioneered the use of adaptive routing, pioneered the design of high-radix switch architectures, and invented a new low-diameter system topology, the dragonfly.

Slingshot breaks new ground again. It features Ethernet capability, advanced adaptive routing, first-of-a-kind congestion control, and sophisticated quality-of-service capabilities. Support for both IP-routed and remote memory operations broadens the range of applications beyond traditional modeling and simulation.

Quality-of-service and novel congestion management features limit the impact to critical workloads from other applications, system services, I/O traffic, or co-tenant workloads. Reduction in the network diameter from five hops (in the current Cray XCTM generation) to three reduces cost, latency, and power while improving sustained bandwidth and reliability.

FLEXIBILITY AND TCO

As your workloads rapidly evolve, the ability to choose your architecture becomes critical. With Shasta, you can incorporate any silicon processing choice — or a heterogenous mix — with a single management and application development infrastructure. Flex from single to multi-socket nodes, GPUs, FPGAs, and other processing options that may emerge, such as AI-specialized accelerators.

Designed for a decade or more of work, Shasta also eliminates the need for frequent, expensive upgrades, giving you exceptionally low total
cost of ownership. With its software architecture you can deploy a workflow and management environment in a single system, regardless of packaging.

Shasta packaging comes in two options: a 19” air- or liquid-cooled, standard datacenter rack and a high-density, liquid-cooled rack designed to take 64 compute blades with multiple processors per blade.

Additionally, Shasta supports processors well over 500 watts, eliminating the need to do forklift upgrades of system infrastructure to accommodate higher-power processors.

Vision Inspection Powered by AI

How To Avoid Pilot Purgatory For Your Projects

This is still more followup from Emerson Global Users Exchange relative to sessions on Projects Pilot Purgatory. I thought I had already written this, but just discovered it languishing in my drafts folder. While in Nashville, I ran into Jonas Berge, senior director, applied technology for Plantweb at Emerson Automation. He has been a source for technology updates for years. We followed up a brief conversation with a flurry of emails where he updated me on some presentations.

One important topic centered on IoT projects—actually applicable to other types of projects as well. He told me the secret sauce is to start small. “A World Economic Forum white paper on the fourth industrial revolution in collaboration with McKinsey suggests that to avoid getting stuck in prolonged “pilot purgatory” plants shall start small with multiple projects – just like we spoke about at EGUE and just like Denka and Chevron Oronite and others have done,” he told me.

“I personally believe the problem is when plants get advice to take a ‘big bang’ approach starting by spending years and millions on an additional ‘single software platform’ or data lake and hiring a data science team even before the first use case is tackled,” said Berge. “My blog post explains this approach to avoiding pilot purgatory in greater detail.”

I recommend visiting Berge’s blog for more detail, but I’ll provide some teaser ideas here.

First he recommends

  • Think Big
  • Start Small
  • Scale Fast

Scale Fast

Plants must scale digital transformation across the entire site to fully enjoy the safety benefits like fewer incidents, faster incident response time, reduced instances of non-compliance, as well as reliability benefits such as greater availability, reduced maintenance cost, extend equipment life, greater integrity (fewer instances of loss of containment), shorter turnarounds, and longer between turnarounds. The same holds true for energy benefits like lower energy consumption, cost, and reduced emissions and carbon footprint, as well as production benefits like reduced off-spec product (higher quality/yield), greater throughput, greater flexibility (feedstock use, and products/grades), reduced operations cost, and shorter lead-time.

Start Small

The organization can only absorb so much change at any one time. If too many changes are introduced in one go, the digitalization will stall:

  • Too many technologies at once
  • Too many data aggregation layers
  • Too many custom applications
  • Too many new roles
  • Too many vendors

Multiple Phased Projects

McKinsey research shows plants successfully scaling digital transformation instead run smaller digitalization projects; multiple small projects across the functional areas. This matches what I have personally seen in projects I have worked on.

From what I can tell it is plants that attempt a big bang approach with many digital technologies at once that struggle to scale. There are forces that encourage companies to try to achieve sweeping changes to go digital, which can lead to counterproductive overreaching. 

The Boston Consulting Group (BCG) suggests a disciplined phased approach rather than attempting to boil the ocean. I have seen plants focus on a technology that can digitally transform and help multiple functional areas with common infrastructure. A good example is wireless sensor networks. Deploying wireless sensor networks in turn enables many small projects that help many departments digitally transform the way they work. The infrastructure for one technology can be deployed relatively quickly after which many small projects are executed in phases.

Small projects are low-risk. A small trial of a solution in one plant unit finishes fast. After a quick success, then scale it to the full plant area, and then scale to the entire plant. Then the team can move on to start the next pilot project. This way plants move from PoC to full-scale plant-wide implementation at speed. For large organization with multiple plants, innovations often emerge at an individual plant, then gets replicated at other sites, rolled out nation-wide and globally.

Use Existing Platform

I have also seen big bang approach where plant pours a lot of money and resources into an additional “single software platform” layer for data aggregation before the first use-case even gets started. This new data aggregation platform layer is meant to be added above the ERP with the intention to collect data from the ERP and plant historian before making it available to analytics through proprietary API requiring custom programming. 

Instead, successful plants start small projects using the existing data aggregation platform; the plant historian. The historian can be scaled with additional tags as needed. This way a project can be implemented within two weeks, with the pilot running an additional three months, at low-risk. 

Think Big
I personally like to add you must also think of the bigger vision. A plant cannot run multiple small projects in isolation resulting in siloed solutions. Plants successful with digital transformation early on establish a vision of what the end goal looks like. Based on this they can select the technologies and architecture to build the infrastructure that supports this end goal.
NAMUR Open Architecture (NOA)
The system architecture for the digital operational infrastructure (DOI) is important. The wrong architecture leads to delays and inability to scale. NAMUR (User Association of Automation Technology in Process Industries) has defined the NAMUR Open Architecture (NOA) to enable Industry 4.0. I have found that plants that have deployed digital operational infrastructure (DOI) modelled on the same principles as NOA are able to pilot and scale very fast. Flying StartThe I&C department in plants can accelerate digital transformation to achieve operational excellence and top quartile performance by remembering Think Big, Start Small, Scale Fast. These translate into a few simple design principles:

  • Phased approach
  • Architecture modeled on the NAMUR Open Architecture
  • Ready-made apps
  • East-to-use software
  • Digital ecosystem
Vision Inspection Powered by AI

Collaborative Robots Just Keep Getting More Interesting

This entire area of collaborative robots (cobots) just keeps getting more interesting. The idea of humans and robots working collaboratively is intuitive but has been difficult to achieve. Cobots have ramifications far beyond industrial applications. But even here, they can lead the way to better productivity and effectiveness.

In this latest piece of news, Universal Robots (UR) announced the immediate availability of the UR16e which boasts an impressive 16 kg (35 lbs) payload capability.

This cobot combines the high payload with a reach of 900 mm and pose repeatability of +/- 0.05 mm making it ideal for automating tasks such as heavy-duty material handling, heavy-part handling, palletizing, and machine tending.

“In today’s uncertain economic climate manufacturers need to look at flexible solutions to stay competitive,” said Jürgen von Hollen, President of Universal Robots. “With UR16e, we meet the need for a collaborative robot that can tackle heavy-duty tasks reliably and efficiently. This launch significantly expands the versatility of our product portfolio and gives manufacturers even more ways to improve performance, overcome labor challenges, and grow their business.”

Developed on UR’s e-Series platform, the UR16e offers these benefits:

·        Fast and frictionless deployment with easy programming and a small footprint

UR16e makes accelerating automation easy and fast. Programming and integration is simple – regardless of the user’s experience or knowledge base. Like all UR’s cobots, UR16e can be unpacked, mounted and programmed to perform a task within less than an hour. With a small footprint and 900 mm reach, UR16e easily integrates into any production environment without disruption. 

·        Addresses ergonomic challenges while lowering cost

With its 16 kg payload, UR16e eliminates the ergonomic and productivity challenges associated with lifting and moving heavy parts and products, lowering costs, and reducing downtime.  

·        Ideal for heavy-duty material handling and machine tending

Rugged and reliable, UR16e is ideal for automating high-payload and CNC machine tending applications, including multi-part handling, without compromising on precision.

“At Universal Robots we continue to push the boundaries of what’s possible with collaborative automation,” continued von Hollen. “Today, we’re making it easier than ever for every manufacturer to capitalize on the power of automation by bringing a cobot to market that is built to do more, as it delivers more payload than our other cobots.”

Like with UR’s other e-Series cobots; UR3e, UR5e and UR10e, the UR16e includes built-in force sensing, 17 configurable safety functions, including customizable stopping time and stopping distance, and an intuitive programming flow. UR16e meets the most demanding compliance regulations and safety standards for unobstructed human-robot collaboration, including EN ISO 13849-1, PLd, Category 3, and full EN ISO 10218-1.

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