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manufacturing Archives - Oden Technologies

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 mimir@oden.io.

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 mimir@oden.io.

 

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

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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.

Read more on Forbes.com

Oden Talks Industry 4.0 in Wire Journal International

By | Blog

I recently had the pleasure of speaking with Wire Journal International on the increased adoption of Industry 4.0 and how more manufacturers are embracing digital transformation and analytics.

Below is an excerpt from the feature.

 

How has your activity in Industry 4.0 most changed since the 2016 report?

In 2016 it felt like we had to do a lot of education and evangelization about Industry 4.0, but now we don’t have to introduce the topic anymore. Our company, Oden Technologies, and client base has grown exponentially, and we’re seeing bigger audiences at our speaking engagements and webinars. However, the one thing I’m very excited by is that we’re moving deeper and deeper in the Industry 4.0 technology to deliver more value. We’ve hired a VP of Data Science, Deepak Turaga, who led IBM’s AI and Machine Learning group so we can move further and truly deliver on the promise of Industry 4.0 with predictive quality and predictive maintenance.

Other industries and media, outside of manufacturing, are catching on to the potential of Industry 4.0. I’ve been asked to be a contributor to Forbes.com on the future of manufacturing and Industry 4.0. Additionally, we just closed a new round of funding with Atomico, and throughout the process we saw just how much venture capitalists and large financial institutions are seeing the tremendous value data analytics can provide manufacturers.

Read the Full Feature

Why IIoT is Essential for Every Factory

By | Blog

Enterprise-grade connected technology associated with the ever-expanding internet of things has continued to expand its reach. The latest iteration of IoT has hit manufacturing in the form of the Industrial Internet of Things, or IIoT, allowing workers to harness the power of the internet to streamline and strengthen production processes and more effectively meet consumer demands.

On paper, IIoT seems like the technology poised to drive innovation in manufacturing – and industrial organizations are following this thread in their investments. Enterprise IoT spending is expected to surpass $772 billion in 2018 and reach $1 trillion by 2021.

That said, for IIoT to be a sustainable solution, upgrading manufacturing technology needs to be more than just “keeping up with the Joneses.” The question then becomes: Is IIoT an operational necessity or just a flashy add-on?  Manufacturers and other industrial firms need to look clearly at their existing technology and determine where IIoT can translate to substantial – critical – improvements.

 

Human and automation symbiosis

Businesses in the manufacturing space are among the most enthusiastic adopters of IIoT technology, accounting for $189 billion in investments related to these cutting-edge assets in 2018. An estimated 38 percent of factories are already leveraging IIoT processes. As a result, you see some of the most mature IIoT workflows in this space – warehouses and production facilities where man, machine and advanced data analytics are working in harmony to achieve incredible results.

Perhaps one of the most prominent examples of IIoT at work is taking place at one of the world’s most successful companies: Amazon. In what MIT dubbed a “human-robot symbiosis,” Amazon has transformed their warehousing and fulfillment centers through the deployment of automation, allowing for the company to cut operating costs by 20 percent.

What makes the Amazon deployment so novel is that IIoT is being viewed as an enhancement of industrial processes rather than a replacement for human labor.

“It’s a natural outgrowth of efforts to harness cheap computing power to make robots more collaborative,” Wily Shih, a professor at Harvard Business School who studies manufacturing, said at the time.

Smaller companies have similarly employed IIoT to improve operations in their facilities. Robotics maker Fanuc, for instance, sought to address the issue of downtime by employing a cloud-based analytics software that would predict imminent component failures and flag for maintenance. The Zero Downtime system Fanuc pioneered ultimately resulted in the company being awarded GM’s prestigious Supplier of the Year Innovation Award in 2016.

 

250% increase in productivity with automation

Smart factories represent the pinnacle of IIoT technology and early facilities, such as those discussed above, have revealed that connected industrial-devices, deployed at scale can have an immense impact on the shop floor. This is why an estimated 76 percent of manufacturers worldwide are developing these advanced sites. In fact, almost 60 percent of the industry have $100 million or more invested in these efforts.

Embarking on the IIoT journey: Where to start

As both of these use cases show, IIoT is more than just a flashy add-on to existing workflows. It’s hard to argue with the ability to seamlessly turn digital designs into reality via automated production lines or a whopping 250 percent increase in productivity.

Manufacturers that have yet to roll out concrete IIoT development plans should certainly consider doing so quickly, as it seems that this technology may soon drive the industry. Still, this can be an intimidating undertaking. Even smaller scale IIoT deployments have lots of moving parts – literally and figuratively – that even the most advanced internal IT teams might struggle to juggle without external assistance and guidance. Even worse, some some manufacturers may not even know where to start with their needed upgrades.  

This is why we built Oden Technologies: to assist manufacturers that want to embrace IIoT technology, but aren’t sure where and how to begin. Our hardware and software solutions allow manufacturers to collect actionable shop floor data and use it to improve and streamline their production flows, thereby building the data-backed foundation needed to move into more advanced IIoT deployments.

Connect with us today to learn more about how our technology can future-proof your manufacturing operation.

Forbes: ‘What’s At Stake In The Race To Industry 4.0?’

By | Blog, Featured Post

As Industry 4.0 gains momentum in the manufacturing world, executives are calculating the risk-reward ratio of becoming early adopters of this technology. Some are considering the cost, in money and time, against the potential gains. Others are determining whether they should wait until their competition shows definitive proof of the benefits before striking out into the largely unknown territory. Still, others, stung by the over-blown promises of overly complex and costly earlier technologies, are simply wary. All of them are working to figure out what exactly is at stake in leading or lagging behind the Fourth Industrial Revolution.

To put it simply, the answer is that the future of your business is at stake. But most executives will see that answer as too simple or abstract, if not too glib.

To truly understand the risks and rewards of being among your industry’s leaders during this transformation, bring the debate down to earth. Consider one of the fundamental issues you deal with every day: the cost of poor quality and the cost of downtime.

Reducing the cost of poor quality and downtime

The daily battles that manufacturers wage to make better products and keep machines running figure prominently in Industry 4.0. Driving down the cost associated with these basic elements of manufacturing are among the most critical challenges a manufacturer must address — and for good reason.

The true cost of poor quality — the sum of the costs from repair, rework, scrap, service calls, warranty claims and write-offs from obsolete finished goods — can range between 5 and 30% of a manufacturing company’s total revenues, with the range for a majority of companies falling between 10 and 20%.

And that’s not counting the costs associated with lost customers.

This profit leakage is a staggering amount for an individual company, alone. When you calculate how it compounds through the supply chain, impacting the bottom line and ultimately the customer, the value of fixing the problem becomes clear.

Likewise, the cost of downtime reduces profitability in a variety of ways too numerous to detail here: lost production and capacity, higher labor cost per unit and inventory costs and added stress on employees and machines. When the machines are down, everyone’s attention is diverted from growing the business, whether it’s responding to new opportunities or innovating new products and services.

Though variable industry to industry, one survey places the cost of one minute of downtime in the automotive industry at an average of $22,000 per minute. If you can reduce your downtime costs to a fraction of that, the benefits to the bottom line alone will be substantial.

Read more on Forbes

Forbes: ‘Industry 4.0: The Journey Towards Perfect Production’

By | Blog, Featured Post

I was thrilled when Forbes invited me to contribute to their website on the future of manufacturing. Given all the time I spend speaking to people in manufacturing about Industry 4.0, its competitive advantages, and how they can leverage their factory data to improve production, I’m excited to now share my perspective with the readers on Forbes.

Below is an excerpt from my first article in the series. Join me every other week for my take on how manufacturers should approach Industry 4.0 in addition to other challenges facing the industry.

“Manufacturers are under constant pressure. They need to decrease waste while increasing uptime, throughput and quality to continue to compete effectively. Manufacturers are no stranger to disruption either, and in recent years lean manufacturing practices and automation have applied further pressure on them, even forcing some out of the game altogether.

The next disruptive phase in manufacturing is already well underway. “Industry 4.0” builds on the previous three phases of industrialization – mechanization, mass production and controls. It’s an intelligent production environment enabled by an integrated platform of enterprise data systems, the Internet of things (IoT) and cloud computing.”

Industry 4.0 provides insight into variables or anomalies that can cause performance issues, such as machine failures, bottlenecks or waste, and it is going to completely transform the manufacturing sector and fundamentally change the established relationship between the makers and consumers of products.

Read more on Forbes.com

Oden Co-Founders Make Forbes 30 Under Europe Industry List

By | Blog

The Oden Team is proud to announce that our co-founders, Willem Sundblad and Peter Brand, have made this year’s Forbes 30 Under 30 Europe Industry List. The Industry List recognizes those individuals whose companies are making a significant impact in transforming the manufacturing industry.

Oden Technologies, which was incorporated in London in 2014, is not so quietly disrupting the industry by empowering manufacturers to improve quality, eliminate waste, and achieve perfect production with our Industrial IoT technology. We are thrilled to have our innovate leaders recognized on this list, as well as continuing to work with forward-thinking manufacturers to usher in the Fourth Industrial Revolution.

For more information on the Forbes 30 Under 30 Industry List, read the article in full.

Learn more about our Industry 4.0 technology.

No announcement available or all announcement expired.