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.

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

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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

What Is Machine-to-Machine (M2M) Communication?

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Machine-to-machine communication, or M2M, is at the core of what makes a smart factory smart. The smart factory model relies on a machine’s ability to track and report on data that is relevant to its operation and productivity. Without this capacity, the machinery is useless and cannot contribute to the insights that may be generated through a cloud-based platform.

In this post, we will look at how M2M communication influences the smart factory and the ways it can be applied in manufacturing. This will help give you an understanding of the smart factory from the ground up.

 

How It Works

M2M communication is just what it sounds like; it is the act of two or more machines or systems sharing information with each other. This transfer of information can occur through a wired medium, but it is more commonly done wirelessly. M2M is also not just limited for physical machinery, but can be between individual chips, sensors, or components within a machine.

In manufacturing, many companies offer plugins that can enable traditional machinery with the ability to connect wirelessly to the internet and with online, cloud-based platforms. For instance, Oden Technologies offers a simple device that can be plugged into any machine or PLC to communicate wirelessly to their cloud-analytics platform. Once the machinery is enabled with wired or wireless communication, it now has the physical means to communicate with each other and with any system that is connected to the same network.

 

Applications In Manufacturing

M2M communication influences the way that a machine reports on and shares data in a manufacturing environment. It is incredibly important for plant managers to understand the current state of their factory, and one way to give them this information is to allow machines to communicate it directly to the manager through a software interface. Having accurate and relevant data will allow employees to gain meaningful insights on ways to improve their business.

Downtime in manufacturing occurs when a system or machine is not operating at its expected efficiency. This results in significant costs for manufacturers, and because of this, it is vital that manufacturers have systems in place to accurately report on the state of their factory at any given time. With M2M communication, each individual sensor on a machine reports its data to a central platform to solve this problem.

fourth industrial revolution factory

When a machine is operating at a lower efficiency or malfunctions, it will talk to the other machines and to the platform itself. This is for two reasons: 1) So that the factory employees can be notified and make the necessary manual adjustments or fixes, and 2) So that the other machines can make automated adjustments, like changing their rate of production or operating times.

 

M2M Automation

A major theme in M2M communication is automation. Automation can be good and bad depending on how it is implemented, but its purpose is always to improve efficiency, lower costs, and optimize production. Every manufacturing company is looking to reach these goals, and to do this, the proper technology must be deployed in their factory.

M2M communication is crucial to automation because it allows developers to dictate how a machine should operate based on certain conditions. For example, if a machine malfunctions, the system would be able to detect what part of this machine is inoperable and could even place an order for a replacement component.

 

The Value of M2M Communication

M2M communication creates the foundation for a smart factory that can be powered by artificial intelligence and machine learning. This form of a smart factory can bring tremendous value for the manufacturer such as increased productivity, reduced material waste, predictive maintenance and more. A smart factory is powered by big data, and any AI system is only as useful as the data that it has access to and it’s ease of use by factory employees.

A core component to machine learning is giving a computer system the ability to learn without explicit programming of that knowledge. The only way to do this is for a system to have access to information about itself and its environment, and that is only possible through M2M communication.

 

M2M For Optimization

On a more general level, the true value the M2M communication brings is the capacity for optimization. Whether it is through manual maintenance on machinery from real-time notifications, or it is an automated chain of actions that developers design to complete tasks, the ability for machines to exchange information is at its core.