Sam Cessna joins Oden as Chief Revenue Officer

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Today, we’re delighted to announce that Sam Cessna has joined Oden as Chief Revenue Officer. Sam joins us from PTC where he was responsible for launching ThingWorx and pioneering the use of Industrial IoT technologies in traditional industrial markets. At Oden, he will lead sales and strategic partnerships to deliver IoT and industrial automation solutions to manufacturers and machine makers worldwide.

Sam has unrivaled experience in introducing new technologies to a wide range of traditional manufacturers. Building on his expertise, we will be able to offer new solutions to help manufacturers extract more value from their existing industrial automation investments. Sam will also oversee the expansion of our process improvement solutions into new manufacturing sectors and build our operations into Asia and Europe.

With more than 20 years of industry experience in providing software, hardware, and services that leverage emerging technologies, Sam is known for delivering the promise of Industry 4.0 to manufacturing organizations and creating some of the industry’s most highly regarded products and solutions. Prior to Oden, he held leadership positions at PTC, Wonderware, Standard Automation & Controls, Fairchild Systems, and Texas Instruments. 

Read the full press release.

Forbes: Security Is Key To The Success Of Industry 4.0

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Manufacturing is a highly competitive industry. The continuous need to outperform competitors is to such a great degree that it is imperative for manufacturing organizations to protect their intellectual property (IP) . Because if the security of their proprietary data is ever compromised, then their competitive advantage is jeopardized as well. And we’ve seen it happen too many times; compromised data leaves the potential for someone with malicious intent to cause harm, in terms of safety and financial risk.

Overall, manufacturers need to raise the bar when it comes to security and in order to reap the full benefits of Industry 4.0, business leaders must support their IT teams both culturally and financially to help them secure their networks. Let’s take a look at what this type top-level support entails.

What should manufacturers ask of their technology vendors?

As manufacturers engage in digital transformation, their internal IT teams need to form important partnerships with technology vendors. Before deciding which Industry 4.0 supplier to work with, it is vital for manufacturers to carry out rigorous checks of each vendor’s security credentials.

In order to protect critical production data, manufacturers should ensure technology vendors implement end-to-end encryption with strong encryption keys along the entire value chain. It is essential to check that a vendor’s encryption is up to the appropriate level of standards and spans from the cloud to edge computing. Bad actors can track the vulnerability of data throughout the network and low-bit encryption can be cracked easily.

Read more. 

The evolution of modern equipment manufacturing – what’s next?

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The modern manufacturing industry has experienced several incremental operational improvements over the last 50 years. We were introduced to W. Eduards Deming’s statistical quality management and TQM, followed by lean initiatives and Value Stream Assessment. We’ve experienced the rise of robotics and pervasive computer technology.

But none of these technologies have been as transformative as the digital revolution of the recent decade. We’ve entered the era of Machine Learning and Artificial Intelligence being applied on the factory floor, the era of Industry 4.0.

The term ‘Industry 4.0’ is typically interpreted liberally and despite being around for some time still causes quite a bit of confusion among manufacturers.

Originally an initiative by the German government with the objective of enhancing competitiveness of German industry and machinery manufacturers specifically, it’s been broadly adopted by machinery manufactures. It provided a standardized control interface and communication protocol, mostly OPC UA and specifically in the plastics industry – Euromap standards. This development fashioned different equipment with the ability to communicate and exchange data.

While the ability to collect and review production data is transformational, it’s just the beginning of this manufacturing revolution. The next step? It’s developing Machine Learning and AI capabilities that will provide meaningful and actionable insights into making products at the highest possible throughput, with the highest possible quality and yields, and the most economical material usage.

Oden is already ahead of this curve, and offers manufacturers the ability to predict the dimensions, quality, throughput, material usage on an extrusion line 5 minutes into the future. The Oden platform can alert manufacturers about undesirable, suboptimal process conditions and tell the user on how to adjust processing parameters. Besides the obvious operational cost benefits, this also aids the experienced workforce shortage problem, by providing less experienced shop floor personnel the ability to perform at the highest level.

Oden’s analytics infrastructure also has tremendous benefits for machinery manufacturers. Predictive analytics can be applied in monitoring critical components and sub systems of production equipment, leading to truly predictive maintenance alerts and the ability to predict when components will fail. This will enable machinery manufacturers to effectively eliminate unplanned downtime for their customers and offer post-sales real-time equipment monitoring service

Finally, Oden’s analytics platform can integrate and support existing manufacturing production data that is tied to inventory logistics through ERP and MES solution.

The Eye of Oden podcast – Episode 3: Machinery veteran Steve Braig on the future of automation and robotics

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In episode 3, Steve Braig, Oden’s VP Business Development talks to us about the the future of automation and robotics.

VO: Welcome to The Eye of Oden. The stories behind the team that brought you intelligent industrial automation and developed the industry’s first machine learning and artificial intelligence for manufacturing. The team who’s working tirelessly to deliver new technologies to the factory floor, and to help manufacturers optimize their production, eliminate waste and close the skills gap forever.

Let us introduce you to Steve Braig, Oden’s VP of Business Development responsible for building relationships with manufacturing equipment makers and strategic partners.

VO: Steve is a self-professed manufacturing lifer, but what attracted him to this industry in the first place. He gives a few reasons.

Steve: The first one probably always has been in my DNA. My father, my grandfather, my uncle, my brother – all engineers and back at the time it was just a natural path for me to follow. Secondly. I’m always excited about seeing a product being made, seeing physics at work. A fast moving toggle clamp on an injection molding machine or precise motion controlled by server technology. It excites me. It gives me a lot of satisfaction. Lastly, we all want to do something in our life or in our career that is meaningful and contribute to society. Manufacturing has the largest multiplier effect in any industry. So for every manufacturing job that is created, there is about one and a half jobs in support of that particular activity. So the socio-economic benefit in manufacturing is far larger than in any other business segment. Several years ago, I was very proud about the fact that I was appointed to the US Manufacturing Council by the previous secretary of commerce. And I’ve been able to advise member of members of Congress and the administration on manufacturing conducive policy. So to me it’s a meaningful activity that’s contributing something to the society.

VO: Manufacturers can’t avoid hearing that we’re now in the fourth industrial revolution. How did we get here? Steve explains the key stages of manufacturing evolution and what it means to the workforce today.

Steve: The big steps in manufacturing evolution were certainly: total quality management – TQM and subsequently statistical process control. So after that we had computer controlled systems on the factory floor, CNC machines. We saw the connectivity between machines, ERP systems. Another incremental improvements were driven by  certainly value stream assessments and lean initiatives where manufacturers really started to zero in on understanding how value was created on the manufacturing floor and then subsequently eliminating wasteful steps. That was quite a transformational process for many manufacturers. And then today we’re at the advent of Industry 4.0. Which brings the ability to collect data from many different input points, from machines, from processing technology, offline quality operator inputs. Collecting a massive set of data, analyzing that data  and storing that data for future comparisons. And really helping or providing the insight of what is happening on the manufacturing floor. In addition, the insight or the transparency is certainly an enabling feature.

What we have today, we are at the advent of the fourth industrial revolution. And this in my mind is going to be the most transformative, the most significant one. Because we can collect data from many different sources: from machines, operator input, offline quality. And we can analyze that data, make the history of that data available. Then we can provide operators, process technicians, plant management with the inside on how to adjust their processes so they will always operate in the most efficient way. Meaning faster throughput highest yields at the lowest total cost.

An additional benefit of having that inside, having data analytics, is really helping manufacturers overcome the workforce development problem. There is a lack of skilled workers in a manufacturing environment. Baby boomers who have a lot of that domain knowledge and experience are retiring, less skilled, less experienced team members join companies. With the ability to provide process insight we are leveling the playing field to some extent. We are giving the opportunity to less experienced workers to perform just as a high as a level as somebody that might have 25 or 30 years of experience. So this enabling the usage of a subset of data analytics where we really help manufacturers to operate at the highest possible efficiencies .

VO: With background in robotics and automation, Steve has a unique view on the role of robots and how it’s changing in manufacturing.

Steve: I studied robotics – the Holy Grail of automation back then. 30 years ago, it was robotic manufacturing with ‘lot size one’. What that means is that every product that comes down an assembly line is completely different or somewhat different from the previous one, and from the next one. So that’s what ‘lot size one’ means. And you can imagine that this needs a lot of flexibility to actually do that for a robot, with all of the supporting mechanisms to adjust with each cycle to a different assembly or to a different manufacturing task. Automation and robotics prevail in high volume long lifecycle product manufacturing, because tooling up an automated assembly line and that cost is depreciated over the lifetime of a program.

So automated assembly robotics always have been very prevalent and very conducive in high volume manufacturing environments. And what it lacked and still does to some extent is the flexibility to adjust to a different product. So to some extent if you take cell phone manufacturing for example, you have a new model launch every nine to 12 months. Also there is a big mix of different models with access to cheap labor. It typically has been more conducive to have some conveyor assembly lines but still have humans running manual assembly operation. I think the industry is still trying to fulfill again that Holy Grail where you have robotics, where you have automated assembly that is completely flexible and can perform not only a repetitive task but whatever the task requires. So that might be a different shape of components that are being assembled at different locations with different features. So that needs a lot of technological breakthroughs.

For example workers can feel a certain resistance for example or apply just a certain pressure. Instead, robots are vision controlled. So they’re looking for the start and the end points versus having a fixed programmed and started end point including the path between those two points and then also the entire supporting infrastructure. If you assemble a product you most likely have screws, you have inserts, you have circuit boards. They typically all need to be in a jig so that the robot can pick up these components and place them repetitively in the product that is to be assembled.

If you have a lot size one you can not have (…). So these are hard tools automation solutions and the opposite of that is again that you can bring any product, any shape in any location within a certain proximity that the robot can find. The robot understands the location and the orientation of the part that is being picked up and subsequently assembled. So it requires a lot of computing power, requires vision sensors and again –  a completely different concept from a hard coded programmed path and task that the robot fulfills.

A lot of progress has been made already. Vision sensors have become much more cost effective. The resolution of vision sensors has become much better. But thirty years later, there are still very few examples where automated assemblies with a lot size one has been successfully implemented. I mean in a commercial environment. In lab environments – yes, but not necessarily in your typical manufacturing environment.

The innovation cycle certainly is accelerating to some extent. I mean that also follows Moore’s Law, continuing to have access to increased computing power at at higher speeds. But you know, we have been focusing on tasks again  – a robotic assembly, where the other significant part of manufacturing are processing industries. Where were you actually make a part, unlike just putting them together in an assembly environment.

So here you have plastics processing. You have CNC machining, you have dye casting, a lot of other processes that require a certain expertise in fine tuning. So that you can operate at the highest yields, with the highest throughput and the most cost effective way. And that is an area where we have seen much faster progress then with some of the assembly tasks and robotics use that I just described before.

VO: But will the robots take over the factory floor?

Steve: I think that is foreseeable. I don’t have a crystal ball or make any prediction when that happens. But there will always be some level of it. Well, first of all that also really depends on the type of product that you are making or on the type of industry. But you always will need some level of manual human support. One is obviously maintaining the equipment. And here also with Oden Technologies, we are currently expanding our machine learning, our artificial intelligence capabilities in providing equipment manufacturers and ultimately manufacturers users with predictive maintenance.

So we analyze migration patterns, magnetic fields temperature and we able to conclude the state or the condition of components or of subsystems of a machine. Right now one of the largest disruptive elements in a manufacturing environment is unplanned downtime, unavailability in availability of machines. So if we can monitor the condition of components subsystems and predict with a level of accuracy when a component fails, and advise the maintenance team to change these components proactively. Then this will ultimately lead to the elimination of unplanned downtime due to machine failure. So all of these tasks, all of these day-to-day headaches that we have a manufacturing floor, with the availability to collect, analyze and interpret data will lead to a significant changed environment. And again lead to a much more efficient way on running your manufacturing floor.

Oden launches partner program to help machinery manufacturers eliminate unplanned downtime

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In current competitive market, machinery manufacturers struggle to build ongoing relationships with customers post-sale. Once equipment is deployed by a customer, they lose visibility into machines’ performance, heavily relying on field service teams in case of failure. At Oden, we believe there’s a better way.

That’s why today we’re announcing our partner program to enable machinery manufacturers to leverage Oden’s IoT technology infrastructure and our Industry 4.0 expertise, and immediately begin adding value for their customers. Our goal is to help machine makers re-imagine customer aftermarket service.

Oden’s Vice President of Business Development Steve Braig will oversee the partner program and lead the development of machinery OEM relationships and strategic partnerships with system integrators and software providers. Steve is the former CEO of Engel Machinery and Trexel who served on the U.S. Manufacturing Council, advising Congress and the administration on manufacturing conducive policies.

The machinery manufacturers who are providing remote monitoring and maintenance services to their customers are already realizing considerable gains. More than 80 percent benefited both from increased customer satisfaction and improved uptime and machine availability. One third have also decreased the number of on-site service calls and lowered the cost of problem resolution. The Oden real-time, data-driven technology approach has the potential to increase these gains exponentially.

Using Oden’s platform, machine makers can provide their customers with real-time alerts and fix equipment before it fails, effectively eliminating unplanned downtime. Their customers will benefit from the option to outsource the maintenance and repair of their assets to the equipment maker, reducing their MRO costs and increasing machine availability.

Oden’s platform, which spans both hardware and software, offers machinery manufacturers easy to install wireless IoT devices, and production-ready, intelligent industrial automation platform. Its predictive analytics can be applied to monitoring critical machine components and sub-systems of production, delivering real-time insights into the inner workings of their equipment, and predictive maintenance post-sale.

If you would like to learn more about Oden’s partner program for machine manufacturers, please get in touch.

Forbes: Two Ways to Transform Your Manufacturing: The Traditional Approach and The ‘Intelligent’ Way

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Digital technology has brought on new ways to transform businesses and manufacturing operations, but it still raises questions from manufacturers. I hear, “Digital transformation? Isn’t that what we’ve been doing for the past three decades? We’ve already connected our business, manufacturing, and supply chain systems with ERP and MOM/MES.”

In many ways, they’re right. It could be argued that manufacturers have been in a near constant state of transformation since the first Industrial Revolution, with change happening at a more rapid pace with each new era. What’s different now is that Industry 4.0 technology, such as Artificial Intelligence (AI) and Machine Learning (ML), are amplifying human capabilities. They’re delivering insights, predictions, and recommendations to solve problems that couldn’t be solved with earlier technologies. That’s why the current era is being called as the Fourth Industrial Revolution; it’s a fundamental break from the past.

When we talked about transformation—even digital transformation—during the Third Industrial Revolution, we talked about how to use new tools and systems to make specific processes or products faster and better than they could be made before. Leveraging the alphabet soup of applications—ERP, MES, MRP, etc.—manufacturers incrementally streamlined, connected and accelerated nearly every part of their business.

The Fourth Industrial Revolution builds on these advances and leverages Internet of Things (IoT) technology to integrate and streamline entire systems, from design to delivery. Augmented with AI and ML, these systems are always on and self-learning, improving their capabilities over time from observation of the processes, user actions, and their corresponding outcomes. The result is an architecture that enables humans to answer new types of questions.

Read more.

Forbes: The Four Levels of a Smart Factory Evolution

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For many manufacturers, the path to building a Smart Factory is still confusing because of information overload.  In order to overcome this challenge, manufacturers should view this transformation as a journey with four stages that reap ongoing benefits to their operations . As with any extensive company-wide transformation, trying to achieve the end goal too quickly can leave you back where you started, having wasted time and money.

It’s critical that manufacturers understand that the Smart Factory is primarily about data.

Prior to the Fourth Industrial Revolution, commonly known as Industry 4.0, manufacturers relied on clipboards and manual methods to collect machine data, perform root-cause analysis, or gain insight into their operations. But as the competitive landscape of manufacturing changed, and consumer demand increased, the industry reached a point where these manual processes were no longer efficient. In fact, they cost manufacturers time and money in the form of lost productivity, suboptimal machine output and product quality.

The Smart Factory evolution is about building upon the advancements of the Third Industrial Revolution by automating the collection of data from machines and applications, and transforming that data into immediate insights. This new technology turns the tedious, but critical, process of extracting insights from data into one that is instantaneous, streamlined, and achievable for every manufacturer.

Read more. 

The clearest, fastest way manufacturers can capitalize on data analytics

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A go-at-it-alone approach won’t work

Of all the new capabilities that manufacturers can gain by adopting Industrial Internet of Things (IIoT) technology, data analytics can be among the most powerful—and the most challenging. Manufacturers make things and, as such, they’re accustomed to working with materials and machines, not bits and bytes. Though it’s true that many have experience working with data from ERP systems and MES, few have the internal resources, skills and knowledge to capitalize on the high-volume data streams of IIoT analytics.

Compounding the challenge is a talent shortage. Pure-play data companies such as Google, Amazon and Facebook are more likely to appeal to the best and brightest. They have the data that talented data scientists want to work with, can (and do) offer generous salaries, and are located in high-tech, fast-growing cities. Manufacturers will find it difficult to compete: They’re not viewed as data-centric companies where data scientists can thrive, are unable to meet or beat the competition’s salary, and tend to be located far away from high-tech centers.

Manufacturers simply aren’t going to be able to hire their way to a data-centric future. To bridge the divide between what manufacturers know they must do and what they’re able to do, they’ll need to work with partners and consultants—at least until a critical mass of data scientists becomes available or they can upskill their process engineers in the data sciences.

But that begs the question: If a manufacturer doesn’t have expertise in the IIoT and data analytics, what do they look for in a partner?

Read more here.

Let’s Meet! Oden Spring 2019 Events Calendar

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Have questions about Oden Technologies and how we help manufacturers improve their process, increase operational efficiency, and preserve their processing recipes? Stop by our booths or presentations at any of the following events, to get answers and meet the Oden team. Request a meeting and a member of our team will get back to you.

Meet the Team

PLASTEC West

February 5-7, 2019 — Anaheim, California Exhibiting: Booth 3883

Speaking: Wednesday, February 6

Attending PLASTEC West? Book a meeting with an Oden representative here.

 

Thermoset Topcon

February 19-20, 2019 — Charleston, South Carolina

Speaking:  Tuesday, February 19

Attending Thermoset Topcon? Book a meeting with Oden CEO Willem Sundblad here.

 

International Polyolefins Conference

February 24-27, 2019 — Houston, TX

Speaking: Tuesday, February, 26

Attending International Polyolefins Conference? Book a meeting with Oden CEO Willem Sundblad here.

 

ANTEC 2019

March 18-21, 2019 — Detroit, Michigan

Exhibiting: Booth 220 Speaking: Tuesday, March 19

Attending ANTEC 2019? Book a meeting with an Oden representative here.

 

Molding 2019

March 19-21, 2019 — Indianapolis, Indiana

Exhibiting: Booth 23

Speaking:  Wednesday, March 20

Attending Molding 2019? Book a meeting with an Oden representative here.

 

Hannover Messe

April 1-5, 2019 — Hannover, Germany

Exhibiting: Hall 8, Stand A07

Attending Hannover Messe? Book a meeting with an Oden representative here.

 

Manufacturing & Technology Conference

April 1-3, 2019 — Pittsburgh, PA

Speaking:  Tuesday, April 2

Attending the Manufacturing & Technology Conference? Book a meeting with an Oden representative here.

 

NAMES19

*Platinum Sponsor*

April 16-17, 2019 — Chicago, IL

Book a meeting with an Oden representative here.

 

AeroDef

April 30-May 1, 2019 — Long Beach, CA

Speaking:  Wednesday, May 1

Attending AeroDef? Book a meeting with Oden CEO Willem Sundblad here.

 

Plastics Extrusion World Expo

May 8-9, 2019 — Cleveland, OH

Exhibiting: Booth C153

Speaking:  Wednesday, May 8

Attending Plastics Extrusion World Expo? Book a meeting with an Oden representative here.

 

Automation World Conference & Expo

May 14-15, 2019 — Chicago, IL

Exhibiting: Booth 8

Speaking:  Tuesday, May 14 & 15

Attending Automation World Conference & Expo? Book a meeting with an Oden representative here.

 

Interwire 2019

May 13-16, 2019 — Atlanta, GA

Exhibiting: Booth 1829

Speaking:  Tuesday, May 14

Attending Interwire 2019? Book a meeting with an Oden representative here.

The Eye of Oden podcast – Episode 2: The biggest challenges for manufacturers in 2019

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In the second episode of The Eye of Oden podcast, we’ve caught up with Willem Sundblad, co-founder and CEO of Oden Technologies to discuss the biggest obstacles for manufacturers today.

VO: Manufacturing is going through the renaissance, but not without its challenges. Here’s what Willem Sundblad, co-founder and CEO of Oden Technologies sees as the biggest obstacles for manufacturers today.

Willem: It’s interesting because right now it is such a good time in manufacturing. Filling orders and hiring people is actually the biggest challenges for most manufacturers. Manufacturing is extremely cyclical so know when there’s good times they try to make as much as they can and make as many products as they can. And you know they’re trying to make sure that they’re being as efficient as they can. But they’re really struggling to hire the right people, the right talent also. So obviously it’s the third thing. I would say the biggest challenge is also competition. You can see that all across the globe right now that you know they’re competing on a global scale. You’ve got now competition in China. Competition in the US and Europe. It’s really only the small regional niche players that aren’t feeling the pressure of competition which is kind of interesting because we’re seeing the adoption with the bigger companies because that’s where they have that competitive pressure. That’s where they have now really the need to improve, they need to innovate. The small regional players, they’re servicing their target audience. But in all of those areas in meeting demand, in shipping product out the door and shipping good product out the door, in getting a competitive advantage, in attracting people. I think that what we do are really compelling solutions for all of those three problems really.

VO: But can manufacturers overcome the challenges and how?

Willem: Well so on the first two: on competition and in shipping products out the door that’s extremely straightforward. In the end because if you’re losing five to 30 percent revenue to the cost of poor quality, if you’re losing 10 to 20 percent of your time to unplanned downtime. Understanding what that downtime is, being able to prevent it with alerts and predictions is a very straightforward way of delivering better to the customers. And also the true value of the analytics is in the bottom line impact that it has which obviously can really change the game in a competitive standpoint too. It’s either that they can lower the price but maintain the margin or they can really start in getting more bottom line frankly to invest more in the business and its people when it comes to the people in the factory. And it’s interesting because if you look historically, a lot of the jobs in manufacturing that have been lost haven’t actually been to outsourcing. I think that something like 76 percent of the jobs lost in manufacturing have been to technology and automation rather than offshoring. But it’s not clear, this chicken or egg thing because actually if you look at the biggest challenge, it’s a skills gap in the workforce development that are facing manufacturers. The problem is that not enough people are going into manufacturing to start with. So you have to automate and you have to improve the technology because you have to make do with less people because fewer people want to work in factories. And I think that’s part is information asymmetry. Again I think that there’s not enough people that understand or know how exciting and rewarding and fun their career in manufacturing can be but partly it’s just people want to work you know they want to live in the cities they want to work with other types of tools and technologies and markets. So being able to make sure that your existing teams are as productive as they can be. So that one process engineer can do the job of three engineers is really critical for the success of the manufacturing industry. And I think we’re where we’re going towards that but I don’t think it’s the technology that’s taking people away from those jobs it’s people who are leaving it. And technology helps the people that are there.

VO: Robotics is the talk of the town. But what real impact can we expect, and will the robots put us out of the job?

Willem: So I feel like some people too black and white view of robotics saying that oh everything will be robotics, same way that people say oh well we’ll just 3D print everything in the future. I don’t think it’s as binary as that. I think that robotics and collaborative robots will come in and do tremendous things to alleviate people of menial tasks frankly and help really ensure higher compliance higher traceability and higher quality in the manufacturing process. But I still think that there is a huge need to have the human in the loop in the manufacturing process. And that’s a term for the machine learning kind of industry: having a human in the loop machine learning. I think it’s the same thing with human loop in manufacturing process because there’s things that people are great at and there’s things that computers and machines are great at. And you should leverage both to the highest kind of combined strength rather than look at it as a binary who’s going to win.

VO: Let’s talk about this machine and artificial intelligence that everyone is so excited about.

Willem: If you’re thinking about how can a system, how can a software, how can a piece of technology create value. There’s two things really. One is to help a person do something faster than they could otherwise. So as an example, their software might help a person solve a problem in five minutes that would otherwise take them a day. That’s obviously valuable. And that’s good. Where it gets really interesting is whether technology helps the person solve a problem that they wouldn’t otherwise have been able to at all. And that’s the same type of things that you can do with machine learning and artificial intelligence. Because you can start actually analyzing more data than a person could consume or more data than a person could compute in 10 lifespan pretty quickly to come up with what is the perfect way of making this product. So as an example the environmental analytics, that type of analysis just wouldn’t be possible by a human so that really takes a huge transformative leap in how people interact with material, machines to make the most efficient products. And  we’re really not even scratching on the surface on the type of value that we can create there because even that case uses very simple machine learning techniques frankly. But there’s other ways that you can apply artificial intelligence where you’re just doing the type of analysis that just wouldn’t be possible for a person or team of people to do like other startups that tackle this specific space.

VO: There’s been a big explosion in the number of startups that are focusing on improving how factories are run. Why is it happening now?

Willem: What we were trying to do, you had the enabling technologies of wireless networks becoming ubiquitous. You had cloud computing which has tremendous value to what we’re doing, but in 2014 it still had a very bad perception in the manufacturing industry. It’s just now that people are really coming round to understanding how it’s actually more secure and it gives them tremendous economies of scale. And then you’ve got the kind of decrease in cost of electronics so doing what we do now would be extremely different 5, 10, 15 years ago. I actually meet people all the time who say oh I had this idea I tried to start this in the 90s, when I tried to start this in 2002 and they couldn’t get the technology to work because at that point couldn’t move the needle from what Rockwell and Siemens, and Schneider were doing. But now you can with a completely different technology stack. I also think that there’s a tremendous amount of information asymmetry, you can look at the Venn diagram of people who are entrepreneurs who want to start tech businesses and the people who really know intimately about the challenges that are facing manufacturing that Venn diagram has a very small intersection. So there are some very few people that actually know about this opportunity and know about how much value you can create in manufacturing and how rewarding it is frankly and how available that is.

When we started in late 2014 early 2015 I saw the biggest risk to us was that we were too early. It is very obvious to me that this is how the future of manufacturing will look like. And we’ve got a tremendous opportunity in being the company that defines that. And so we have to do everything that we can to both attract the customers that are the early adopters but also evangelize about what’s possible. You know we saw In the last couple of years we just saw a lot of confusion in the industry. We saw a lot of wait and see, we saw the majority of the market kind of not knowing or understanding what industry 4.0 will concretely mean for them. So we saw it as a huge part of our job is to really evangelize and talk about concrete solutions. Talk about this is how it’s going to impact their day to day. This is what’s possible. This is how we get started. And so that’s even though we’re a product company, we’re not a consulting company. There’s a lot of learnings that we get from just seeing how the industry is moving, seeing what we’re doing, seeing what works, seeing what our competitors are doing and when we can know if we’re open about that that is just going to help the entire industry.