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.

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.

The Eye of Oden Podcast – Episode 1: What would happen if Oden data centers got hit by an asteroid?

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Have you ever wondered why it’s spelled Oden not Odin? What made Oden take the road less traveled and provide both hardware and software to the manufacturers? Or perhaps, what would happen if Oden’s data centers got hit by an asteroid?

Our new podcast, featuring a series of interviews with the Oden team, has all the answers. 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.

In our first interview, we talk to Willem Sundblad, co-founder and CEO of Oden Technologies. You can listen to it on Soundcloud and/or read the transcript below.

VO: Let us take you through the story behind Oden, beginning with Willem’s childhood and his first job that involved ‘making things, better’.

Willem: I grew up in a suburb north of Stockholm, Sweden and I think I had a fairly normal upbringing. My parents had just moved back to Sweden. They had spent over 10 years living abroad in the US and then in Holland and then moved back with me right before I was born and my older brother as well.

For a long time I wanted to be a skier and actually an extreme skier. I wanted to go big mountain skiing in Alaska and be paid to do so. So I guess you can say I’ve never been a risk-averse person. I also wanted to be a stuntman because I was getting injured so much that I figured I might as well get paid for it. So that was kind of some early ideas of how I would make a living. But I’ve always liked making things and building things and solving problems.

The first company that I thought I would start with that you know obviously wasn’t a real company but a friend and I we actually made some products in shop class in like third grade.  And at that point you know you did either woodworking then you went and you did sewing. And we built a really cool baseball bat and we thought we were so good that we’re gonna build the whole company and brand around it and make other stuff when we’re going into sewing class. That never happened. But guess that was the first idea of a company.

VO: The baseball bat fiasco didn’t put Willem off the idea of building things. Equally passionate about the subjects of math, science and business, he chose to study industrial engineering, carrying on his family tradition.

Willem: My family’s on my dad’s side always been in manufacturing for four generations primarily in the paper and pulp industry, and the forest industry which is one of the biggest industries in Sweden. My great-grandfather was one of those people that was kind of an eccentric genius. He didn’t know how to make eggs. But he graduated from engineering school at an extremely early age with a bunch of patents on how to make paper and actually was in charge of building most of the paper and pulp factories across all of Sweden. He then actually became CEO of one of them for about 30 years and then my grandfather – his son – went to the US actually at a pretty early age and saw that kind of growth of the packaging industry and saw that no one was really doing that in Sweden or in Europe. So he then took over that kind of paper and pulp factory and turned it into a really high-value cardboard factory and built a brand called Invercote which is now one of the most widely used high-value paper boards in Europe. So if you look at any nice perfume bottle and a nice bottle of alcohol those are usually done in a paperboard and actually all of Apple’s paperboard and packaging comes from that company and in that brand that he created. And my dad was also working in the manufacturing industry always in either forced industry or heavy machinery industry.

VO: While at university, Willem traveled around manufacturing plants in Europe to learn how they examine and improve their production processes. There for the first time, he realized what an incredible value manufacturers can create from optimizing processing and eliminating waste. Yet after he graduated, Willem moved to London to work not on a factory floor, but at Vodafone, a British multinational telecommunications conglomerate.

Willem: I came up with the idea behind Oden while I was still studying but I had at the same time started looking at kind of job opportunities and I knew that the manufacturing industry itself it takes a pretty long time to change it from the inside. But changing it from the outside you can have a faster impact frankly. And I knew what I wanted to build. So I was looking at technology jobs and telecommunication jobs because I actually want to work with machine to machine communications. I figured machine to machine communications is an enabler of what we do.

VO: Willem spent a year working at Vodafone, but starting his own venture remained firmly on his mind. As he was planning his next move, Willem met Peter Brand who at the time was with Sailthru, a US email marketing software startup.

Willem: I got introduced to Peter through I lived with an American family as an exchange student and that family was friends with Peter’s family. So when we both moved to London they introduced us and Peter was an early employee at a tech company from New York and was sent over to run a kind of client service and in customer-facing operations in EMEA. We became friends and then a couple of months later he actually tried to hire me to join that company.

And so about a couple of weeks later or actually two weeks later Peter and I met up for dinner. And it’s funny because we didn’t know this and that shows you how out of touch and single we were because we met up for dinner on Valentine’s Day, and we had no idea was Valentine’s Day. We then just looked around at the restaurant and saw that there’s just a bunch of other couples. He made me an offer to join his company, which was extremely compelling from a project standpoint from a monetary standpoint from everything. So I just said I’m not gonna say yes or no but here’s what I want to do.  You have to know what I would be walking away from. And then I told him about Oden and then about four and a half hours later and a few drinks later he rescinded the job offer and said let’s do that and then I want to join you instead.

VO: So what did Willem tell Peter that convinced him to quit his own job?

Willem: The idea I sold him was that there is an incredible amount of waste in manufacturing and the original idea was that I had was to really build a new type of industrial automation company kind of in three phases where Phase 1 is analytics Phase 2 assimilation and Phase 3 control. So first I have to analyze how you’re doing and why Phase 2 was really what is the optimal way of making this product. And Phase 3 was executing it. How can you automate the manufacturing of a perfect product of perfect production. And so really those four hours were him questioning. Are you serious that people are doing this in manufacturing, really? And I said yes, people are still wasting insane amounts of money, material time energy. It’s crazy. My research on this was from 2011 and we were having this discussion in 2014. So big data was all the hype but we still weren’t seeing people really bringing that to manufacturing in the right way. There were some people who were piggybacking off companies that had already made full SCADA investments or people who are trying to apply standard big data to manufacturing. But there was no one that was really building the company that we were trying to build. And especially when you combine it with hardware so that you can actually apply it to all types of manufacturing or to larger parts of the manufacturing industry that may not have made SCADA investments then you’re just opening up a whole different part of the market and you’re really increasing the size of the pie too. A large opportunity in creating a new type of industrial automation company there.

VO: The beginnings of Oden weren’t always easy, but Willem felt that they resulted in invaluable lessons for the team.

Willem: The funny thing is that we were I mean we were extremely naive at the time. I remember the first factory that we ever did. We did it with GSM with SIM cards in each device because we wanted to be completely separate from the network in the factory. And then that customer bought an expansion and a second factor, which was great progress. You know it’s delivering so much value they want to expand it. It’s awesome. We get to the second factor and they have no cell phone coverage. So the whole thing that we’d actually built the technology on didn’t work. And so then we obviously already signed the deal that we were going to do it. We just hadn’t actually surveyed the network in that factory. So then we needed to go in and really redo the entire architecture and we actually did that in about I think two and a half weeks with a different hardware architecture with a different networking stack and still delivered to the customer. So those kinds of you know painful stories, in the beginning, are just also the ones that you look back on really fondly because when the storm is blowing it’s really easy to know where it’s blowing from you know exactly like problem-solving just becomes so tangible.

VO: Today Oden is working with customers in packaging, wire and cable, building products, and automotive to optimize their production processes, improve product quality and reduce waste.

Our customers are making products, they’re making everything from building products to cables to packaging to medical devices things that go into our everyday objects. And so a lot of them are plastics manufacturers now and there’s a tremendous amount of waste that you can reduce from that process. But an interesting thing is that if you process plastic you need to do it differently in the winter compared to the summer because you’ve got different temperature different humidity different dew point. And so one of the things that our technology does is actually based on the environment that day, we recommend new settings so new ways for that operator to make the same product to increase the quality of that product. It’s really how are we helping the people on the factory make those products as efficiently as possible so that means that we’ve got the hardware device that we plug into their machines that communicates with the machines to get data from the machine on how the machine is doing how the process is doing how the product is being made. The analytics platform that then really helps the people in the factory analyze and optimize how they’re processing the material, how they can solve quality issues so they can solve machine failures, how they can speed up production while maintaining quality and then as always then fed back to the people on the floor so that they can make it in a different way and make it in a more efficient way.

VO: Improving efficiency is a constant theme for manufacturers, more so than for any other industry. Willem explains why.

Willem: Manufacturers can lose between 5 and 30 percent of their total revenues due to the cost of poor quality. And that’s just insane from an individual company perspective on what they could do if that wasn’t lost. It is insane from a sustainability perspective but also from a consumer perspective you know imagine that you’re buying a car that’s made up of 30,000 components from different suppliers and they’re all losing that much at least or every part of that car could be made twice as efficiently as it did as it is today. So it’s really founded in that kind of disbelief that there has to be a better way of doing this and enabling people in the factories with data and analytics and the right intelligent industrial automation tools to execute that perfect production has to be the way of the future and we want to build a business that has the highest potential impact we can in creating that future that means that we really see an opportunity in building a new type of industrial automation giant a really new intelligent industrial automation giant that really is data first and kind of software-defined in how we’re building our tools.

VO: Oden started as an IoT company. But the founders quickly realized that the potential of its technology – that combines both hardware and software – extends into the realm of industrial automation.

Willem: What we used to talk about it as we used to say that we are Industrial Internet of Things and then we started talking a lot about Industry 4.0, but we realized that especially you know we’re not IoT anymore since we’re starting to control the machines also. So that means that it’s industrial automation not just IoT. Industry 4.0 there’s been too much confusion around it so that people’s eyes always glaze over and they don’t really understand what it is and what impact it’s going to have. So we’ve settled on intelligent industrial automation because it clearly differentiates us from what normal industrial automation is since we’re doing it from a data-driven perspective, real-time perspective and machine learning powered way. And it also makes it fit into the market’s ideas, they know what the value is, they bought that forever.

VO: But what does set Oden apart and how does it compete with established industrial automation providers. Who does Willem see as his sparring partners?

Willem: It’s Rockwell, it’s Honeywell, it’s Siemens, it’s Schneider Electric, it’s ABB. It’s those traditional industrial automation companies. There are companies that are doing similar things or there that are doing analytics but we surprisingly seldom see them in the manufacturing space in our target market at least. A lot of the analytics companies don’t have any hardware solution, they can’t deploy into they’re more of a front end that sits on top of someone that’s already bought a Rockwell data system as an example. Or are also developer platforms like Thingworx where people can build their own applications. But what we’ve seen is that the majority of the market really just wants the end to end application and that’s where we have a very compelling story because you get the entire infrastructure without the crazy investments of a SCADA system and you get more powerful analytics that is really built to live in unison from the edge to the cloud. It’s not a hodgepodge of many different systems. It is one platform and frankly that platform is open too. We still see a lot of resistance from that the older players to the concept of an open platform where we want to be open to integrating with other solutions API so they can access the data or they can access the results from the analytics or even use our machine learning data pipeline to run their own machine learning models. I think that in order to truly succeed in this you have to have a more open view but also deliver that into perspective and have the capabilities to deploy it end to end.

VO: Oden’s customers benefit from the company’s unique approach to industrial automation in a record time. As Oden’s platform can be deployed multiple times faster than its counterparts.

Willem: Where we’re seeing the best results are really with the customers that have kind of leadership from the top that has a vision about how they should use data and technology to make better products and the people on the floor have the right skill and the will to really improve their production also. We’ve seen tremendous results. We had actually just this week another customer. They managed to on average improve their line speed across all their products by 20 percent that is transformational from how they run their production. Now they can have less labor productivity per feet of product. They may not have to run over the weekends. They can cut down in shifts if they’re not fully at capacity. If they are at capacity then they just gained another 20 percent out of that actually. So that impacts margins tremendously too. And then if you’re looking at how you’re starting up that you’re also saving a tremendous amount of material in the startup phase of that production run. We’ve got other customers who’ve gotten multimillion-dollar returns per production line on improving how they actually process the recipe how they’re making their products.

VO: Being a data-first industrial automation provider, Oden takes the security of data extremely seriously. But to explain why Oden’s customers should not fear even an asteroid attack, we first need to explain its Norse mythology roots.

Willem: Oden is the god of victory and wisdom and that’s what we are taught in Sweden. I heard someone else say that outside of Sweden Oden is the god of war. I just think that’s a difference in perspective coming from the Viking Age. But in my head, Oden is the god of victory and wisdom and he actually sacrifices an eye for the wisdom of the world. And so that’s why our logo is the Eye of Oden. He also had two ravens who flew around the world gathering intelligence for him and so our hardware is actually named after those ravens. So you’ve got the Hugin and Munin devices gathering intelligence for the Oden platform.

Ragnarok in the Norse mythology is when the world ends. We have Ragnarok as our disaster recovery exercise every quarter where we simulate the death of Oden which is the simulation of the death of one of our data centers or all of our data centers and we really build up the entire stack as a true disaster recovery. So we simulate if an asteroid hits all of our data centers how do we make sure that our customers are not losing service, not losing data and get the full level of service as fast as possible. And you know we never lose data but we’re trying to make sure that they have the full level of service in a matter of hours even if an asteroid hits our data centers.

VO: And that’s all for today. Thank you for listening to The Eye of Oden. For more information about Oden Technologies, please. visit our website


AI and Machine Learning Usher in a New Era of Intelligent Industrial Automation

By | Blog

In the week that we at Oden launch the industry’s first cloud and edge Machine Learning (ML) and Artificial Intelligence (AI) framework for manufacturing, I wanted to examine what this means for the future of intelligent industrial automation.

The manufacturing sector is excited about the potential of AI and ML. 2018 research from The Manufacturer that 92% of senior manufacturing executives believe that digital technologies, including AI, will empower them to increase production and efficiency.

While many other sectors have adopted AI and ML, manufacturing has been slow to progress their application. This is because the complexity and specificity of manufacturing processes have required heavily customized solutions developed by internal data science teams.

Yet Machine Learning and AI have so much to offer manufacturing. The future is all about intelligence and intelligent industrial automation where manufacturers never automate a bad process. Let’s look at some of the potential deployments of AI and ML technologies.

How AI and ML with transform manufacturing

Machine Learning and AI will ultimately be able to provide manufacturers with prescriptive answers to production challenges that humans simply cannot. The top line is that, in tandem, they will help manufacturers make products as efficiently as possible, eliminating waste and reducing downtime.

Repeat processes can be automated and continually improved to their optimum production and efficiency levels as the application learns, assesses and iterates those processes.

It all starts with data. The success of any application of AI and ML relies on the quality of data collected. Manufacturers need to gather the right data in the right formats and in the right quantity. Otherwise, the application could ‘learn’ the wrong things and will not make informed decisions.

Automation is going to play a huge role in the digital transformation of manufacturing as producers embrace Industry 4.0. AI and ML are key to making that automation effective. We see a huge gap between manufacturers who are exploring automation, AI and ML, and those who are deploying them successfully.

To make the adoption of AI and ML much simpler for all manufacturers, we’ve developed the industry’s first end-to-end Machine Learning and Artificial Intelligence framework for manufacturing.

A new framework for manufacturing

Oden’s new, patent-pending infrastructure spans both the cloud and the edge, the framework allows manufacturers to deploy mission-critical ML and AI applications to avoid machine failure, eliminate waste, and optimize production in real-time.

The framework integrates ML algorithms and data science tools with both structured and unstructured data from machines, operator inputs, quality assurance (QA), work order, environmental monitors and product specs. The hybrid cloud and edge infrastructure delivers the power of the cloud without compromising the requirements of mission-critical applications.

Manufacturers can use the framework to continuously monitor their manufacturing process to predict quality and machine health, detect abnormal behavior, and provide recommendations on recipes and process settings. They can also prototype and test new ideas rapidly, and deploy them quickly with little or no overhead.

Every organization is unique and manufacturers cannot take a “one size fits all” approach to deploying AI and Machine Learning. This is why we’ve developed a platform to provide manufacturers with the flexibility that they need to deploy intelligent industrial automation in their production processes and supply chains.

Are you excited about the potential of AI and ML at your factory? Have you any questions about how you could apply them and become a future-proof, intelligent manufacturer? Check out our whitepaper on ML and AI applications for manufacturing or get in touch to learn more.

Delivering on Key Benefits of Machine Learning and AI for Manufacturers

By | Blog

As manufacturers prepare to reap the benefits of Industry 4.0, Machine Learning (ML) and Artificial Intelligence (AI) driven applications are widely expected to play the key role in their success.

These new types of applications will help operators, process engineers, and management solve their operational and production problems with diagnostic, predictive and prescriptive answers. Ultimately, they will increase efficiency, minimize waste, and drive innovation across the factory floor.

But the task of delivering production grade ML and AI applications have historically proven difficult to execute. Until now.

Today, we are pleased to announce the launch of Mímir – the Oden Operational ML and AI framework. Our framework brings together all the manufacturing data and best-in-breed ML tools and algorithms tailored for manufacturing, as well as an enterprise-grade deployment infrastructure spanning the cloud and the edge.

This framework is designed to manage all steps of the ML and AI application lifecycle, including exploration, training, validation, deployment, and monitoring. Once deployed, it enables manufacturers to build and operationalize mission-critical applications that are robust, verifiable, and scalable. Oden’s ML and AI framework is also designed to be extensible; it supports the creation of both foundational, general-purpose applications in addition to customer and problem-specific models. 

The Mímir framework is available to Oden’s customers from today. To learn more about our ML and AI solutions, you can download our white paper, or email us at

Oden Launches Industry’s First Cloud and Edge Machine Learning and AI Framework for Manufacturing

By | Blog

New York, December 4, 2018 – Oden Technologies, the intelligent industrial automation provider, announced today the industry’s first end-to-end Machine Learning (ML) and Artificial Intelligence (AI) framework for manufacturing.

With a novel, patent-pending infrastructure spanning both the cloud and the edge, the framework allows manufacturers to deploy mission-critical ML and AI applications to avoid machine failure, eliminate waste, and optimize production in real-time.

Despite the increasing adoption of Machine Learning and AI across other industries, their applications in process manufacturing have been limited. The complexity and specificity of manufacturing processes have traditionally demanded heavily customized solutions developed by internal data science teams.

Oden’s production-ready ML and AI framework is tailored specifically for manufacturing processes. It integrates ML algorithms and data science tools with both structured and unstructured data from machines, operator inputs, QA, work orders, environmental monitors, and product specs. The hybrid cloud and edge infrastructure delivers the power of the cloud without compromising the requirements of mission-critical applications.

The framework can be used to continuously monitor the manufacturing process to predict quality and machine health, detect abnormal behavior, and provide recommendations on recipes and process settings. Manufacturers can leverage the Oden framework to rapidly prototype and test new ideas for process monitoring and optimization, and more importantly, deploy them directly into their mission-critical operations with little to no overhead.

“Today’s launch marks the first step to delivering intelligent industrial automation to our customers,” said Willem Sundblad, co-founder and CEO, Oden Technologies. “The future of manufacturing demands intelligent systems that can provide real answers to the production issues manufacturers have been asking for decades. Only then can they achieve perfect production, with zero waste”.

The Oden platform provides continuous visibility into factory operations and processes, with customers seeing improvements such as a 20 percent increase in monthly output and 50 percent decrease in total scrap, resulting in millions of dollars in savings and additional revenue each year. Dr. Deepak Turaga, VP of Data Science at Oden Technologies, believes that the open and extensible nature of this ML and AI framework will accelerate such gains significantly.

“One-size-fits-all approach to Machine Learning and AI will never deliver on its full potential”, he commented. “That’s why our goal is to provide customers with the best-in-breed foundational ML and AI applications tailored for manufacturing, and the framework tools to easily extend and adapt them to their specific requirements and processes.

The ultimate benefits of Oden’s ML and AI framework extend beyond improving current production processes and operational efficiency. By integrating structured and unstructured data, supported by best of breed ML tools, it can be used to capture both implicit and explicit process know-how. In the future, this will allow manufacturers to leverage the system in bridging their talent skills gap.

To learn more about our Mímir ML framework download our whitepaper, or contact us at


About Oden
Oden Technologies is the intelligent industrial automation company empowering manufacturers to achieve perfect production by providing complete visibility into all the production processes in real-time. The Oden platform wirelessly collects data from any machine, integrates it with third-party systems, and delivers instantaneous insights leading to effective quality control, timely maintenance and lower machine downtimes, optimized operations, and higher customer satisfaction. Oden investors include Atomico, EQT Ventures, Inbox Capital, and LocalGlobe.

Oden Discusses the Benefits of Technology for Fabrication Shops in the FF Journal

By | Blog

I recently spoke with the the FF Journal about fabricators and the benefits of investing in technology to alleviate pain points on the shop floor.

Below is an excerpt from the article.

Advanced technology isn’t meant to simply replace people. “A combination of tech and talent still matters,” Acieta’s Poole says. “In order for companies to attract the best talent from this younger workforce, they need to show that their operation is looking to the future and investing in technology that will keep workers interested and engaged with the work they do.”

Fabricators compete for the same dwindling talent pool. Investing in new technologies is an important part of attracting new talent, says Willem Sundblad, CEO of Oden Technologies, which provides data acquisition hardware and process analytics software for manufacturers. Shops needn’t overhaul equipment either. Analytical tools can connect to machines new and old.

“You can easily double your efficiency without purchasing new equipment or undergoing a massive factory overhaul, just by understanding your current process,” Sundblad says. “Shops find that they can become more productive just by allowing their teams to solve more problems faster and be as efficient as possible.”

Read the Full Article

Forbes: ‘Machines As A Service’: Industry 4.0 Powers OEM Aftermarket Revenue Growth

By | Blog

Original equipment manufacturers (OEMs) are no strangers to boom or bust sales cycles. Traditionally, they’re either ramping up production to meet demand or seeking ways to slash costs when sales are down.

But Industry 4.0, or the Industrial Internet of Things (IIoT), is enabling new sales models that generate more consistent revenue streams for OEMs. There are considerable benefits for forward-thinking manufacturers that transition from selling a product to offering, “machines as a service.” Rather than relying on a one-time sale, they’re charging customers based on machine use and service.

Machines as a service can revolutionize the way OEMs design, sell and service products. It will be a win-win for OEMs and their customers, as both partners benefit from increased predictability.

Selling uptime as a differentiator

It’s a business model that’s becoming more prominent across a wide range of industrial products, including Rolls-Royce’s aircraft and marine engines. The U.K. company is an example of a manufacturer that’s leveraged IoT to turn a high-value asset into a continuous source of revenue.

Rolls-Royce offers “power-by-the-hour” service agreements that allow customers to pay a fixed rate per hour of operation rather than purchasing the engine outright. The company assumes responsibility for ongoing maintenance and provides predictive maintenance services based on insights from their IoT-enabled engines that wirelessly send machine data to four Rolls-Royce centers for monitoring.

Now compare that service model to the more common fail-and-fix approaches in which OEMs sell the equipment outright and only provide service when a machine breaks down. OEMs that adopt machines as a service differentiate themselves from competitors by guaranteeing 100% uptime and only charging for actual usage.