NPE 2018 Post-Show Report: Industry 4.0 is the Key to Smarter Plastics Manufacturing

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I had the opportunity to discuss ways the plastics industry can meet these challenges during the NPE 2018: The Plastics Show in Orlando last month. I presented on how Industry 4.0 and Industrial Internet of Things (IIoT) can help the industry transform standard processes, such as machining and molding, into highly efficient high-tech operations.

The world wants more plastics. That’s a good thing for the industry but also means manufacturers need better problem-solving capabilities. They need to find ways to produce materials faster and cleaner.

Plastics manufacturers need to adopt IIoT technologies to keep pace with unprecedented demand.  Global demand for polyethylene (PE), the most widely used plastic, is expected to reach 120 million metric tons (MMT) by 2022, up from 96 MMT in 2017, according to IHS Markit. Demand spikes are common across many industries, but the plastics sector faces additional challenges.

 

New Demands, Same Challenges

While the surging demand for plastics may be new, the challenges faced by processors have remained the same for decades: make more products, faster and cheaper, with less material waste. As Nick Vafiadis, Vice President of Plastics for IHS Markit, put it, “the industry must find ways to produce more with less.”

“Global demand for PE has been robust, and integrated margins have remained at elevated levels for several years, despite record new additions of cost-competitive capacity being added in North America and elsewhere. It is this robust demand growth, combined with production constraints, that continues to drive tight PE margins,” Vafiadis said.

 

The IIoT Factor

During NPE 2018, we fielded numerous questions about the role Industry 4.0 and IIoT will play in the future of plastics. IIoT helps plastics manufacturers monitor valuable metrics in real time that can help improve production, eliminate waste and improve product quality. This is critical because the introduction of new materials and processes can add complexity to production and create a competitive disadvantage for manufacturers that lack transparency into their operations.

A recent article in Plastics Technology highlighted some of the key ways Industry 4.0 will impact the plastics industry, including the application of “smart molding” and extrusion processing solutions, as well as predictive maintenance monitoring of cell equipment.

For example, Wittmann Battenfeld, a manufacturer of plastic processors, has incorporated Industry 4.0 capabilities into its products, including the ability to monitor gripper vacuum levels to warn of leaks or other problems before the robot loses its grip. Color-coded operating-status lights on Wittmann robots indicate whether vacuum levels are adequate (green), in the warning zone (yellow) or too low to hold the part (red).

During the show, several plastics machinery manufacturers debuted base-level IIoT solutions to help customers increase efficiencies. While they were similar to connected solutions we’ve discussed in the past, they lacked the data processing power, ease of use, and full process analytics of Oden Technologies.

Oden can affix small wireless IoT devices to machines or PLCs that can send critical data to a cloud-based analytics platform. Whether it’s maintenance data or overall equipment effectiveness, this connected environment provides a fast, single source of truth about critical production variables.

It’s clear that modern-day demands mean plastics manufacturers must find new ways to gain a competitive edge. IIoT helps manufacturers identify waste streams and inefficiencies faster. It also automates many manual tasks, which frees key personnel, such as engineers and operations managers, to focus on meeting modern-day demands.

Don’t view these new global pressures as a threat. If you’re a plastics manufacturer, consider how IIoT could help you gain an advantage in this increasingly competitive marketplace.

How IIoT Brings You Closer to Customers

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The manufacturers gaining the competitive edge on product quality and customer satisfaction appear to be those that adopt smart-manufacturing technologies, including the Industrial Internet of Things (IIoT). Why is IIoT such a key differentiator in today’s economy? It lies in the ability to monitor, correct and optimize operational issues in real time.

A headline in Chief Executive Magazine recently posed the question: “Who’s Pushing U.S. Manufacturing Forward?”

“Accelerating the rebound in U.S. factories depends on what they make and how they make it, not just where,” wrote Chief Executive contributor Dale Buss.

It’s a statement that rings especially true today. Talk of trade wars, changing consumer demands and continuing workforce shortages mean U.S. manufacturers must place a greater emphasis on quality, innovation, and efficiency to remain competitive.

Dependence on low-cost sourcing won’t win the game anymore.

Many manufacturers have relied on outsourcing to remain competitive. But this model isn’t quite as effective as it once was. For one, wages are increasing in many low-cost countries, such as China. Also, consumer demands for faster delivery and more customized products mean manufacturers can’t afford long lead times, supply chain disruptions or quality issues.

The winners appear to be manufacturers that adopt smart-manufacturing technologies, including the Industrial Internet of Things (IIoT). Why is IIoT such a key differentiator in today’s economy? It lies in the ability to monitor, correct and optimize operational issues in real time. If you make things efficiently at home there’s no reason to source materials halfway around the world. And that means you can serve customers faster and be agile enough to meet their demands for more customized products or just-in-time deliveries.

The key is finding IIoT systems that provide the in-depth analytics you need to make immediate decisions to correct variations in quality or increase throughput. Sensor-based data systems are nothing new. IIoT has become a catchphrase for any manufacturer that deploys a sensor to its equipment or production line to receive critical performance data over the Internet.

But truly effective IIoT includes dashboards, alerts and statistical analysis to correct problems as they happen and adjust production to meet changing customer requirements. Many IIoT systems still deliver information to traditional spreadsheets, such as Excel, which requires manual manipulation to begin root-cause analysis.

In fact, according to Deloitte’s “Global Cost Survey Report,” digital solutions, such as data analytics, are the most effective ways to drive cost savings. Analytics and automation empower “companies to analyze mountains of data and identify key costs savings opportunities. These technologies will help increase efficiency and effectiveness — evolving new platforms and driving cost improvement across the entire enterprise,” according to Deloitte.

Chief Executive Magazine recognized rapid prototyping manufacturer Protolabs as a company that’s “pushing U.S. manufacturing forward.”   The St. Paul, Minnesota, company helps manufacturers respond to customer demands faster with services such as 3-D printing. Company President and CEO Victoria Holt noted that about half of companies’ annual revenues are from products they launched within the last three years. In other words: product lifecycles are getting shorter.

“To be able to address that, we’ve got to be taking advantage of manufacturing technologies and Manufacturing 4.0, or we won’t be able to compete,” Holt told Chief Executive.

Is IIoT Secure? 5 Tips to Protect Your Factory

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Disruptive innovations come with risks. Think about the recent tragedy involving a self-driving car in Arizona. While this is an extreme example of what can happen when technology fails, it’s a reminder that safety must always be a priority.

The Industrial Internet of Things (IIoT) is no exception. Operational technologies (OT), such as plant-floor equipment and machinery, have traditionally lacked exposure to the type of attacks that IT systems face. But now more manufacturers are tying their IT and OT systems together as they adopt IIoT technologies.

We understand that companies have concerns about security when connecting their devices to the Internet. Fortunately, there are strategies manufacturers can implement to secure their IIoT investments.

1. IT and Operations Must Collaborate

The operational side typically doesn’t consider security requirements, so it may lack an organized security practice, notes Gartner contributor Susan Moore. However, a primary focus for IT is protecting information. This is why IT and operations need to collaborate early in the IIoT implementation process.

“IT and OT cultures are not incompatible, but they require executive guidance to realize initial alignment,” Moore writes.

2. Know What You Have

A simple, yet often overlooked safeguard is knowing exactly what IIoT devices you have in place and where they’re located.

“You can’t secure what you don’t know you have, so an effective IoT security strategy must begin with a comprehensive inventory of all networked assets,” according to an IndustryWeek article by contributors from Crowe Horwath LLP. “In addition to known and authorized devices, the inventory also must capture unauthorized or previously unmanaged devices, such as security cameras, monitors, machine sensors and other devices that have been plugged into the company’s network by employees or vendors without the IT department’s knowledge or participation.”

 

3. Opt for Multi-Layered Security

Make sure your IIoT network doesn’t rely on a single technology for security. For example, Google Cloud offers security at the device and network levels as well as security for apps running on the network, data storage, and hardware. With Oden’s IIoT solution, all data sent over the network is encrypted and transmitted over a secure VPN connection.

 

4. Stay Up-to-Date

Don’t ignore updates or patches.

“If a device is running out-of-date software, it may contain unpatched security vulnerabilities. Such vulnerabilities may allow exploitation of the device and its data by attackers,” notes the IoT Security Foundation.

This includes updated an IoT device’s firmware to the latest version, “which incorporates all current bug fixes, vulnerability fixes, and mitigating or compensating controls,” according to Crowe Horwath.”

5. Assess and Test

Continuously assess your security. This includes risk-based analyses with business impact statements, Crowe Horwath suggests. This will allow you “to prioritize projects and make the most of limited resources.”

Security issues related to IIoT are rare. Taking a few precautions can ensure IIoT technologies remain safe. Don’t hesitate to consult with IIoT experts to determine how you can safeguard your system while reaping the benefits of a smart, connected enterprise.  

Preparing For Artificial Intelligence In Manufacturing

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In today’s technology space, it is almost impossible to go a day without reading or hearing about artificial intelligence (AI). AI has applications in seemingly every major industry, but what is really going on?

AI, as a subject, can sometimes be confusing to understand. There are many subsets of AI, and each one serves a distinct purpose. Our goal in this post is to dive into the ways that AI is being implemented in manufacturing and to give you ideas for how your manufacturing business can prepare for artificial intelligence now and in the coming future.

 

Applications In Manufacturing

Machine learning is the main area of AI that is currently being applied in manufacturing. The purpose of machine learning is to give a computer the ability to learn new information without being explicitly programmed to know that information. This is made possible through machine learning algorithms, which dictate the way that an AI system should break down and process information.

As an AI system gathers more and more data and learns from it over time, it can gain the ability to make accurate predictions, automate decision-making, detect real-time malfunctions, and much more. For a manufacturer, this will translate into greater efficiency in production, waste management, cost-savings, and will also introduce new features like:

  • Improvement in the accuracy of maintenance and repair schedules
  • Predict workloads based on market trends
  • Product quality management
  • Process controls
  • Management of operations
  • Predictive maintenance/asset management
  • Supply chain management/sourcing
  • Safety and facility management

All of these bring tremendous value to a manufacturer, and that is why AI is such an important area to focus on.

 

It Is All About Data

Data is the lifeblood of AI. For an AI system to function effectively, it needs a substantial amount of data at its disposal. The better the data, the better the AI. This is why it is absolutely necessary for a manufacturer to move their operations onto a digital medium.

The first step in preparing for the integration of AI in a factory is to enable the machinery with data tracking and communication ability. At Oden Technologies, we offer a simple data collection device that can be plugged into any machine or PLC to allow for data to be wirelessly transferred to our cloud-platform.

Once the hardware is in place, the next step is to connect the machinery to a central platform where the data will be recorded and processed by different algorithms. Every platform offers some differences in features, but the main objective is to ensure that you are collecting valuable data about your manufacturing operations. Having a large quantity of quality data is necessary to train an AI to be able to more accurately do all of the things that it is capable of. With less data comes less accuracy.

 

Third-Party Services

In most cases, it makes the most sense to use a 3rd-party service because of the significant amount of capital needed to develop such a platform. There are various platforms available, and the best part about competition is that it will drive the products and services to deliver more value to the customer.

When you use a platform to manage and operate your smart factory, you are limited to the features that this service provides. The good part, however, is that these companies are already providing features based on AI and will continue to develop and make use of new forms of that technology. By working with a provider, you can trust that they will focus on these features.

 

Straightforward Preparation

Preparing for the integration of AI in manufacturing is pretty straightforward. You either spend hundreds of thousands, if not millions, to hire AI engineers to develop a system for you, or you use a 3rd-party service that is already building out these features. Once you find the right company to work with, it is as easy as adding a plugin to your machines and connecting them to the platform online.

If this is the route that you choose to go, the best part is that you do not need to worry much about any other preparation. As long as the service that the customer is using is implementing effective machine learning algorithms and other aspects of AI, the benefits of this technology will be easily attainable.

3 Ways IIoT Helps Attract and Retain Workers

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“The challenge for manufacturers in the U.S. isn’t foreign manufacturing; it’s the high school guidance counselor,” Brian Fortney, global business manager for Rockwell Automation, told Design News. They don’t understand that manufacturing is high tech. The plants are not dark and dangerous.”

Yes, the workforce skills gap still plagues manufacturing. In fact, 71 percent of manufacturers responding to The Future of the Manufacturing Workforcesurvey by Manpower say “insufficient manufacturing skills is increasing in severity now and will continue to get worse over the next several years.”

For manufacturers, the skills challenge often comes down to an image problem. On the one hand, many people still view manufacturing as “dark and dangerous.” Another common misperception is that automation or the Industrial Internet of Things (IIoT) are replacing workers. In reality, highly automated, smart operations help manufacturers empower their current workforce and attract top talent.

Let’s take a closer look at some of the key ways IIoT empowers the workforce, while helping manufacturers close the skills gap.

Developing the Next Generation of ‘Problem Solvers’

In a previous post, we discussed the benefits of real-time production performance tracking. Sensor-connected devices provide workers with more information at their fingertips. The modern workforce is becoming tech savvy and expects to have instant access to critical information, whether it’s displayed on a workstation monitor or via mobile devices. They also want more fulfilling jobs that provide opportunities to create value.

IIoT frees your workers to focus on problem-solving activities rather than repetitive, sometimes dangerous tasks. These connected workers have “easy access to smart operating procedures, and both generic and asset-specific instructions and checklists. Carrying hundreds of pages of unwieldy manuals prove a thing of the past,” according to an Accenture report. 

 

Breaking Down Productivity Barriers

Of course, all manufacturers want their workers to be more productive. Unfortunately, data often exists in silos, which means your workers don’t have access to critical information they need to increase productivity. It also means workers are expending more energy on mundane, physically demanding tasks.

Frustration mounts when workers must stop the line or their machine to troubleshoot a maintenance or quality issue. IIoT allows for true predictive maintenance. In an IIoT environment, workers often receive real-time condition-monitoring alerts, such as vibration data, temperature fluctuations and energy consumption. This results in less downtime and improved employee morale. They also may receive real-time analytics that show variations in product quality or yields.

A Single Source of Truth

When data exists in silos, workers in separate departments may view or interpret data differently. This creates frustration, disagreements about the data integrity and oftentimes low employee morale. Consistency across your enterprise is essential to ensure everyone is working in concert to achieve a common goal. A cloud-based analytics platform can help that’s accessible anywhere, from any device helps break down data silos.  The system takes data inputs, processes the information and provides feedback. The data that is collected gets uploaded to the cloud and is safely stored so that it can be accessed by any Internet-connected device.

 

Other Things to Consider …

The workforce shortage isn’t going to remedy itself. IIoT is becoming a critical component to addressing current and future workforce challenges. Consider IIoT solutions that are accessible to an unlimited number of users. This reduces information siloing and helps you build a more empowered, collaborative team of problem solvers. Also, if you’re an early adopter, look for out-of-the-box solutions that don’t require lengthy, complex commissioning times, which will only complicate your workforce challenges.

How Do Cloud-Based Analytics Work?

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Cloud-based analytics is at the heart of every major technology company. Data analysis itself is a common activity in any business, but when it takes place in the “Cloud,” it can truly change the way that a company operates.

In the technology industry, “The Cloud” refers to a network or group of networks that give connected devices access to shared pools of resources like servers, applications, and services. The internet is an example of this type of network, and therefore, any internet connected device is a part of the cloud.

Cloud-based analytics provides a handful of tools that enable companies to extract insight from large data sets, present those insights in an intuitive and understandable way, and make it all available via a web browser.

 

Data Centers

Most cloud-based analytics systems run on a network of secure data centers, which are owned by some of the biggest tech corporations in the world including Google and Amazon. These data centers are regularly upgraded with most efficient computing hardware, and this is also what makes cloud services much more reliable.

The servers, in addition to other hardware at a data center, is what physically supports a cloud-based analytics platform. It makes data accessible at very fast speeds and ensures that if a company’s internal systems malfunction, all of the data will still be safe at the data center.

 

Cloud-Based Analytics

First and foremost, a cloud-based analytics system must be hosted on some sort of platform or website over the internet. Usually, this is a software system that takes data inputs, processes the information, and provides feedback. This is obviously dependent on the platform itself, but there is always something in common — the data that is collected gets uploaded to the “Cloud” and is safely stored so that it can be accessed by any internet-connected device.

In regards to manufacturing, a cloud-based analytics system usually connects with various hardware devices that all incorporate sensors and communication modules. These devices constantly collect information on the performance of the factory’s operations. The data that gets collected from a machine is uploaded to the cloud and managed on an analytics platform.

A business can choose to build their own, in-house platform, or they can decide to use a third-party service. Usually, a service is cheaper, and these services already have built out functionality that can benefit a company immediately.

The functionality that is provided via a cloud-based analytics platform is made possible through proprietary algorithms that can organize, process, and make meaning out of data. This data goes through various mathematical equations and produces values that are represented in intuitive ways to the users.

A cloud-based analytics platform can provide tremendous value for a company versus an offline version. By being connected to the internet, users will also have the ability to integrate offline data into their datasets with the click of a button, for far greater insight.

 

Cloud-Based Analytics and AI

Cloud-based analytics also paves the way for any future integration of artificial intelligence in a company’s operations. AI is only as powerful as the data that it is utilizing to make its decisions, so by having a digital data infrastructure, you are building the foundation for future tools that will be made available by service providers.

For example, in a manufacturing setting, it is important to track information about the performance of a machine. There are already tools that are available for manufacturers to track and upload this information to a cloud-based analytics platform. Once this data is uploaded, it is processed by the platform’s algorithms and learns about the machine.

In the field of AI, machine learning is a subset that refers to a computer’s ability to learn by itself. As more powerful machine learning algorithms are developed and made available, cloud-based analytics platforms will gain the ability to learn by on their own. One major benefit of this is that the platform is then able to more accurately predict future outcomes based on all of its previously collected data. This will translate into more efficiency, and allow you to avoid things like unplanned downtime. This is why having a cloud-based analytics system is so important.

 

Improved Functionality

The true value of cloud-based analytics comes from the improved functionality for the user. With data being uploaded to services that function over the internet, users gain more accessibility and value. Data is managed more efficiently and represented in more intuitive ways. Cloud-based analytics presents a big opportunity for any business, so if you have not made the transition to the cloud, this might be the best time for it.

Tools To Aid With Predictive Maintenance

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In the manufacturing industry, predictive maintenance refers to the use of big data and analytics to predict when a machine or system will need maintenance. This is made possible through the integration of smart sensor devices that can communicate with external programs to gather and process the necessary information.

Predictive maintenance is important in a smart factory because it allows a business to mitigate unplanned downtime. By having accurate predictions of when a machine may lose efficiency or malfunction, a company can plan ahead to ensure that the lost production from that machine will not influence their operations.

The tools that aid with predictive maintenance include everything from hardware plugins to areas of artificial intelligence (AI). These tools allow businesses and individuals to implement predictive maintenance in their factories.

Connected Machinery

First and foremost, to create a smart factory you will need to enable your machinery with the ability to connect to a central network. This can be through a wired medium, but most services make use of wireless communication. For example, Oden Technologies offers a simple data collection device that can be plugged into any machine or PLC to gather and wirelessly communicate data to their online platform.

A good way to view the machinery of a connected, smart factory is by likening it to the nervous system of a human. Let’s pretend that your factory is an organism, and for it to function, it needs the ability to detect information about itself and its environment. This IoT device and the machines that it is connected to makes that possible.

Cloud-Analytics Platform

 

The next tool that will aid with predictive maintenance is a cloud-based, analytics platform. In more simple terms, this is just an online service where you can connect you machinery to so that the true value of your data can be extracted.

The platform that a company decides to use for their connected factory is where all of the gathered data will be aggregated and processed. Depending on the algorithms that are in place, various insights will be provided to the user about the current and future state of the factory. If we go back to our human body analogy, the platform would be the mind while the machinery is the body.

Machine Learning

Machine learning is a subset of AI that enables a computer with the ability to learn by itself. It is also an important tool for manufacturers to use in predictive maintenance. When machine learning algorithms are applied to a smart factory, the system will be able to learn how different inputs correlate to outputs. This is necessary for predictive maintenance because it will allow a computer system to learn how the conditions of their operations are affecting the outcomes of those operations.

Over time, the AI will see that, for example, if a factory is operating at an average of 70% capacity for 2 weeks, there will be a 92% chance that machine X will underperform and need maintenance. Therefore, if the company wants to avoid this downtime occurrence, they can figure out what they need to do to make the malfunction less likely to occur.

Maintenance Scheduling

The main value that comes from predictive maintenance is that it allows you to figure out the optimum time frames for when maintenance should occur so that unplanned downtime can be avoided. The best platforms for predictive maintenance will automate as many processes as possible to a degree where the employee is empowered to make smarter and better decisions. The first step in this process is to determine when a system or machine may lose productivity or malfunction. Once this is detected, the next step is for the employees to fit the maintenance work into the proper time slot.

Scheduling to Save Money

Predictive maintenance, at its core, is a method for saving money. When a machine or system malfunctions, it can drastically affect the bottom line of a company. This is why it is important to have systems in place to be able to predict and plan for when these machines will need maintenance.

The best way to take advantage of the value that predictive maintenance provides is to make use of connected hardware and a powerful, software platform. It is important to make sure that whatever service and technology you are using has the features that makes this all possible.

How to Launch Your IIoT Journey

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I had the pleasure of attending Frost & Sullivan’s Manufacturing Leadership Council plant tour and roundtable discussion at Merck & Co., Inc.’s Maurice R. Hilleman Center for Vaccine Manufacturing in Durham, NC the last week in November. As the CEO of an Industry 4.0 software provider, I found the experience invaluable in keeping a pulse on the challenges faced by manufacturers today.

My main takeaway from the tour visit was learning more about the prevailing issues facing the manufacturing industry on what to do with big data and Industrial IoT (IIoT) projects. The two most common questions I heard during the roundtable discussion with industry veterans and executives were:

  1. “We don’t know where to start with our Industry 4.0 projects,” and,
  2. “We already collect lots of data, but don’t know what to do with it.”

These two sentiments were reiterated by one manufacturer after another, prompting me to write this blog post and prescribe a pain-free guide for manufacturers to successfully invest in IIoT.

Click here to read more on the Manufacturing Leadership Council’s blog.

Let’s Meet! Oden 2018 Events Calendar

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Have questions about Oden Technologies, our Industrial IoT platform, or production data and analytics in general? Stop by our booths or presentations at any of the following events, to get answers and meet the Oden team.

Attending NPE2018: The Plastics Show? Make sure to RSVP for our free cocktail reception immediately following the exhibit hours Tuesday, May 8, 2018. Reserve your spot today!

Upcoming Conferences

NPE2018: The Plastics Show

May 7-11, 2018 — Orlando, Florida
Exhibiting: W8681 — West Hall E – Level 2
Speaking: Monday, May 7 at 2:30 PM: Expert Session: “Industry 4.0 & Achieving Perfect Production”
Hosting: Tuesday, May 8 at 5:00 PM: Oden NPE2018 Cocktail Reception. RSVP Today.

WAI Wire Expo & Operations Summit 2018

May 14-16, 2018 — Nashville, Tennessee
Exhibiting: Booth 603
Speaking: Tuesday, May 15: “The Competitive Advantage of Digital Manufacturing”

 

Past Conferences

Advanced Cable North America 2018

February 26-28, 2018 — Atlanta, Georgia
Exhibiting: Booth #14

Molding Conference 2018

February 27 – March 1, 2018 — Long Beach, California
Speaking: Wednesday, February 28 at 3:30 PM –“The Competitive Advantage of Industry 4.0”

Advanced Design & Manufacturing Cleveland 2018

March 7-8, 2018 — Cleveland, Ohio
Exhibiting: Booth #807

American Manufacturing Summit 2018

March 27-28, 2018 — Lombard, Illinois
Speaking: Day 1 Workshop and Roundtable Luncheon

North American Manufacturing Excellence Summit

April 10-11, 2018 — Chicago, Illinois
Speaking: Tuesday, April 10 at 11:40 AM — Workshop Room 2: “Embracing the New Capabilities of Digital Manufacturing Operations”

Fastener Fair USA

April 12, 2018 — Cleveland, Ohio
Speaking: Thursday, April 12 at 11:00 AM: “Liberating Data from Existing Industrial Equipment, and Making Sense of It”

Smart Manufacturing Experience

April 30 – May 2, 2018 — Boston, Massachusetts
Exhibiting: Booth 723
Speaking: Smart Manufacturing Knowledge Bar — TBD