Examples of IIoT In The Workplace

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The Industrial Internet of Things (IIoT) is influencing the manufacturing industry in a big way. In short, the IIoT makes use of networks, like the internet, to aggregate data from connected devices. The data is centralized on a platform where it can be processed and translated into meaningful insights. There are many examples of IIoT being used in the workplace. The platforms and services available to manufacturers can help with everything from machine performance monitoring to predictive maintenance. Many of these systems also incorporate machine learning and other subsets of artificial intelligence to optimize performance and more accurately make predictions.

In this post, we will look at some of the best examples of how IIoT improves the way a factory operates.

Real-Time Performance

One of the best uses for IIoT in a manufacturing plant is for the real-time performance tracking capabilities. When a factory connects their machines to an IIoT platform, the machines will start reporting data for how they are operating. The platform will provide a view that shows every input and corresponding output for all of the machines that are in operation.

This functionality offers huge benefits for a company. With real-time performance tracking, a plant manager or employee can monitor the entire factory and get immediate notifications when a machine or group of machines are not performing at their expected or optimal level. This will ultimately lead to quicker fixes, increased efficiency, and higher quality products.

Factory Integration

Another one of the examples of IIoT in the workplace revolves around the way in which the factory’s machines are enabled with the tracking and communication features. In most cases, the machines already have ports where external devices can be plugged in.

Oden Technologies offers simple data collection device that can be plugged into any machine or PLC and can communicate wirelessly to their platform. This simple integration is what makes some services stand out from others. Factory integration is big part of IIoT but it should be a short process and shouldn’t require factories to purchase new machines and equipment.

Predictive Maintenance

The last example of IIoT in manufacturing is in a system’s ability to make predictions on when maintenance should take place for a machine. This is part of the IIoT incorporates machine learning algorithms. These algorithms look through large amounts of data to recognize patterns, which help the AI form models that represent the correlation between inputs and outputs. Over time, the machine learning algorithms will have enough ‘training’ to be able to make predictions about what may happen based on given data.

In the example of predictive maintenance, the machine learning algorithms will be able to take the performance data from the machines and figure out the likelihood that this machine will need maintenance and by what time. The more data that a factory has at its disposal, the more accurate these predictions will be. This is an approach that leads to cost savings over time and higher productivity.

The Smart Factory

All of these examples of IIoT in the manufacturing industry come together to form what is referred to as a “Smart Factory.” A smart factory has a sort of sensory system that allows it to monitor itself and communicate this information through a unified network. When paired with AI and machine learning, a smart factory can start to make predictions that lead to smarter business decisions for a manufacturer.

The IIoT brings tremendous value and is very easy to take advantage of. It is as simple as getting in contact with the right IIoT platform and integrating this technology into your business. It is important to start collecting this data today so that you can benefit from now and in the future.

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 inoperational 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.

What is IIoT?

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The Industrial Internet of Things (IIoT) refers to the industrial applications of a network of internet connected devices. The devices that are used in such a system measure, track, and share information about various components in the manufacturing process. All of the data that the hardware collects is sent to a central, cloud-based service, where it can be properly organized and analyzed.

The application of the IoT for the manufacturing industry is sometimes referred to as “Industry 4.0,” and is already being offered by some companies. The IIoT will allow manufacturers to acquire and access a far greater amount of data at quicker speeds. This ultimately leads to more insight and efficiency for a factory. The IIoT is continuing to evolve and is providing immense value for manufacturers, so let’s take a look at the benefits the IIoT has to offer.

How Does it Work?

IIoT can be seen as the “back-end” of the various IoT categories. Although it is largely hidden from the average consumer’s view, many of the everyday objects that people use are heavily driven by IIoT technology. Almost every modern manufacturer makes use of some sort of IIoT ecosystem to optimize and streamline their operations.

IIoT incorporates machine learning and big data to generate powerful insights on how a factory is functioning. To do this, IoT devices are installed to collect data from sensors that are added to or built within the factory equipment. This can include almost any device or measure any piece of information that manufacturers think may influence their operations. The data is aggregated onto a central platform where it can be easily digested by a plant manager or other factory employee.

Benefits of IIoT

A powerful network of IIoT devices can significantly improve operational efficiency, scalability, monetary savings, time optimization, and communication across an entire organization. The various IIoT devices that are installed in the machines of a factory will continuously gather machine performance information (which consists of potentially millions of data points). This information is stored via the cloud, processed through a data analytics platform, and then used by plant managers, engineers, operators, and executives in a variety of ways.

When a factory integrates internet connected devices into their operations, it gives the factory a sort of sensory system. This new ability for the factory to collect information about itself will translate into manufacturers making much more informed decisions. In fact, with enough information, manufacturers are able to perform predictive maintenance on their machines so that they can avoid the cost of downtime.

This all leads to the optimization of machine performance, which will save manufacturers time and money. IIoT can also enable manufacturers to maximize their factory’s overall output. Whether it is utilizing big data to make predictions or to detect underperforming machines, IIoT is poised to drive this industry.



Why Should Manufacturers Invest in IIoT?

IIoT is already changing the way that manufacturers operate in the age of the internet. With access to significantly more information, manufacturers are optimizing and breaking informational silos with their access to shared analytics platforms.

Data is one of the most valuable commodities for technology integrated organizations. Unlike most investments, an investment in data is guaranteed to appreciate in value over time. The more data that is gathered, the better it can be used to make previously uninformed decisions.

Decision making is a huge bottleneck in manufacturing, mainly due to its risk-management factor. It is crucial to bring together as much information as possible to assess the risks of a given decision. The introduction of the IIoT allows manufacturers to monitor and store detailed factory data for quick access to production metrics and fast historical querying capabilities.

It is also crucial for manufacturers to gather as much data as possible when thinking about the future application of artificial intelligence (AI) in their factory. Without getting into too much detail, AI is as powerful as the quality and quantity of data that it has access to. For AI to make or suggest these decisions, it would need a large pool of information at its disposal. The longer that you have been collecting data, the more data will be available to feed into the AI. This is why it is increasingly important to implement the IIoT into a factory.

A Solution for the Future

IIoT solutions in the manufacturing space can be accessed by anyone. If you want to enable the utmost level of performance at your factory, this is absolutely the way to go. The benefits of a properly integrated IIoT system will even carry over to the sales and marketing department where factory productivity information can be used to make financial projections, targeting decisions, and much more.

IIoT is clearly driving the future of manufacturing. Innovation has been taking place at an increasingly faster pace, and it won’t be slowing down anytime soon. One way to get ahead, however, is by taking advantage of IIoT technology and the insights that it provides.

Industry 4.0 Misconceptions Debunked

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In the world of manufacturing, there is plenty of skepticism surrounding Industry 4.0 technology. Will it live up to the hype? Is it too early to consider? Is the manufacturing industry really moving in this direction? As with any cryptic subject, there is also a list of misconceptions that arise due to skepticism. We feel that it’s time to address the objections to adopting advanced technology in manufacturing. Let’s talk about a couple Industry 4.0 misconceptions.



Misconception 1: “I should wait to start investing in Industry 4.0.”


This very well might be the most common misconception that manufacturers have about Industry 4.0. When any innovative technology is in its early stages, only a few invest in the technology before it becomes popular. These are known as the early adopters.

As with any investment, it’s only worth time and effort if the ultimate ROI is significant. Industry 4.0 is no different. What makes Industry 4.0 especially compelling for manufacturers is the value that data accumulates brings to a factory in the long-term. Data is the only asset that is guaranteed to appreciate over time. Since big data and data analytics are the backbones of Industry 4.0 technology, it’s especially beneficial for manufacturers to start investing today.


Because it can take a long time to create a full-fledged smart factory. In competitive markets like manufacturing, it’s vital to have the foresight to adopt new technology that will keep you ahead of your competition. By integrating smart factory technology and simultaneously adjusting your operations from the insights gleaned from those solutions, early adopters of Industry 4.0 technology will gain the competitive advantage over those who play ‘wait and see’.

Misconception 2: “It’s not worth making the difficult transition into smart manufacturing.”


Contrary to popular belief, taking the first steps to building a smart factory don’t have to be a painful, headache-filled process. With services like Oden, which makes data collection and hardware tech integration easy for manufacturers pressured to digitize, it’s become easier than ever to make the move.

When most people hear “Industry 4.0” or “smart factory” they picture an extremely expensive, entirely automated factory filled with machine-learning robots working 24/7. In reality, a smart factory can be achieved by simply connecting your existing equipment to IoT devices that capture data and installing software that provides analytics that shorten your time to resolution and production improvement.

If you implement Industry 4.0 technology today, you’ll benefit from it in both the short term, by making immediate production improvements, as well as in the future, when you are ready to adopt more technology into your factory. Manufacturers who start data collection now will also benefit from having years of data to train machine learning models on to make better, more informed decisions.

Misconception 3: “Industry 4.0 isn’t happening anytime soon.”


This simply isn’t true. In fact, PwC recently did a thorough study on Industry 4.0, in a global perspective, and published their findings in a 30+ page analysis. The PwC study even shows that 83% of manufacturers, in various industries and countries, believe that data analysis will become important to their operations by 2021. In fact, even General Motors, one of the dominating manufacturers in the automotive industry, has made moves to integrate data gathering systems into their operations. If that’s not enough proof that Industry 4.0 is coming to fruition, Oden is living, breathing proof that the manufacturing industry is leading the pack of Industry 4.0’s exponential growth.

Misconception 4: “It is difficult to learn about Industry 4.0.”

This one definitely has some merit to it. There are few resources circulating in the world of manufacturing that provide clear and concise information about Industry 4.0, which is the exact reason why we produce that content.

We’re trying to increase Industry 4.0 literacy through our weekly content because we believe that manufacturers looking to digitize shouldn’t be left in the dust of technological innovation. We want to provide the resources that will help them learn why the journey to digital manufacturing is important, inevitable, and easy to start today.


The path to maintaining technology advancement within a factory doesn’t have to be difficult for plant managers. Services like Oden are aiming to erase misconceptions about Industry 4.0, especially the misconception that transitioning to a smart factory isn’t worth the investment.

connected factory IoT sensors

Industry 4.0 In-Depth: Sensors and IIoT

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connected factory IoT sensors

As Industry 4.0 technology increases in popularity, it’s vital that manufacturers understand the terms associated with it. However, vocabulary is only the tip of the iceberg. For any individual who wants to get ahead of the competition in their space, having a clear understanding of the technology they’re working with is just as fundamental. This is especially true for manufacturers who feel pressure to digitize. The Industry 4.0 space is a fairly complicated realm that involves a series of different, separate technologies coming together to build one aggregate system.

One way to think about Industry 4.0 smart factories is to view it as any other complex machine. Let’s use a computer as an example. Computers aren’t a single technology. Computers are the aggregate product of various different pieces of hardware like CPUs, GPUs, SSDs, and countless other elements. Industry 4.0 smart factories, like computers, aren’t a single piece of hardware– smart factories are the product of multiple components that are integrated together to build an efficient system.

Today, we’ll be talking about IoT and sensors, one of the most important terms to understand for manufacturers who aim to build a smart factory. Machine sensors aren’t anything new, but the development of devices that can extract information from these sensors is garnering a new age of information distribution and empowered decision making. In fact, Mark Cuban, a prolific investor in technology, says that sensors are indeed the future. Excited about IoT and sensors yet? We’ll break it down for you.

IoT and Sensors– What Are They?


IoT sensorsThe IoT (Internet of Things) is a term used to describe the collective number of hardware in the world that gathers data and is connected to some form of internet connection. A great way to think about the IoT is to imagine it like a giant web of devices that gather information and sometimes share that information with each other (depending on who owns them). Some of the devices in the IoT are cell-phones, laptops, and other devices that are commonly associated with the internet. However, sensors that exist within or added to factory equipment, make up 8+ billion of the IoT volume.

It is the adoption of smart devices, which extract the data from sensors, and gather the process metrics and calculate insights, that really provides the power in Industrial IoT. Industry 4.0 technology has become more useful and practical for manufacturers to leverage. Since smart devices gather various data points (temperature, humidity, production speed, etc.) they are especially important to engineers and operators. Advanced devices that calculate metrics, such as OEE and scrap, are the key to providing actionable information to the plant managers and executives of smart factories.

How do sensors and IoT relate to Industry 4.0?

sensors the cloud IoTMachine sensors connected to smart devices, in conjunction with the cloud, make up the IoT and serve as the backbone of Industry 4.0 technology. Everything starts with sensors, but without devices to gather information from wherever they’re placed, nothing else will work.

The long-term consequence that manufacturers who fail to digitize will face is the technical expenses they’ll incur by not integrating smart devices into their machines. It’s important to start as soon as possible. Rather than trying to retrofit their existing machines for PLCs and SCADA systems, or buying expensive new equipment, it’s more effective to invest in smart technology that can easily gather data from your existing machine sensors without additional upgrade expenses.

In the near future, at the peak of Industry 4.0 adoption, while every other manufacturer struggles to catch up, manufacturers who digitize today will be ahead in three ways.

  1. Early adopters will have more data to work off of and can make more informed decisions.
  2. The technology is already integrated into their operations. Early adopters will be able to leverage the technology better and more effectively than newbies.
  3. Since data is an asset that appreciates with time, they will have the benefit of compound interest. The more data a factory has accumulated, the better.

Why should manufacturers invest in Industry 4.0 technology today?

While it may seem burdensome for manufacturers to install smart devices into their already-functioning factory, they should invest in the long-term and start today. Eventually, all manufacturers will need to integrate this hardware into their factory because if they don’t, they will be at a heavy disadvantage against their competition.

Blockbuster didn’t see value in video-streaming on the Internet in 1990’s. On September 23, 2010, Blockbuster filed for Chapter 11 bankruptcy, having incurred $900 million in debt and outperformed by on-demand video streaming services. The same could easily happen to manufacturers who sit by idly while their competitors invest in the future (Industry 4.0 technology) and bring the smart devices to their factories. The solution? Become an early adopter.