You’ve surely heard that “Industrial Internet of Things” or IIoT is shaking up how manufacturers operate. But just what is “IIoT” and how can this connected technology revolutionize your production processes?
Manufacturers face the ongoing challenge of a highly competitive environment and the continually rising cost of resources. In order to remain competitive in this aggressive climate, many have invested in digital transformation initiatives. As a result, we are seeing IIoT technology play a key role in the rapid evolution of manufacturing.
Market watchers know the demand for digital transformation in manufacturing will grow exponentially in coming years. IDC stated in early 2019 that it expected the year’s global Internet of Things (IoT) spend to reach $745 billion, driven by discrete manufacturing ($119 billion) and process manufacturing ($78 billion). IDC expects IoT spend to surpass the $1 trillion mark in 2022, with manufacturing playing a key role.
With these impending trends on the horizon, let’s explore the role of IoT in manufacturing and answer the vital question, what is IIoT?
IIoT Meaning and Technical Definition
IIoT, often also referred to as Industry 4.0, involves the industrial application of connected device networks. The advantage of these networks is to provide a digital interface which enables machines to communicate with each other via embedded sensors and shared data analytics. This allows machines to make critical decisions without the need for human intervention.
Technological advances in cloud computing and increasingly powerful edge devices combined with applied analytics has enabled IIoT by allowing devices “talk” to each other. Manufacturers have several immediate options with current networks and wifi to enable this type of communication. 4G networks have always been a key component in enabling IIoT; however, the speed and power offered by 5G is thrusting factories even farther into the future. The future is on the brink as we’re seeing some 5G networks come online already.
The world is watching Industrial IoT as it is attracting notable interest and investment around the manufacturing arena. With improved operational efficiency, performance and trend tracking, more accurate measurement and closer interconnectivity of machines is wanted. IIoT in manufacturing is leading to faster, more data-driven decision making.
The Evolution of IIoT in Manufacturing
As outlined, the increasing competition of doing more with less has driven digital transformation in manufacturing. Manufacturers have always sought new efficiencies, which is why so much automation has entered the factory floor in recent decades. Industrial IoT takes this automation to the next level.
For Machine Learning (ML) and Applied Analytics to work best in the factory, it is essential that data fed into devices is accurate in real-time so that they can make accurate judgments and recommendations. Through this technology, manufacturers can even benefit from predictive analytics, including predictive quality and predictive maintenance as machine learning algorithms pick up trends, errors, imperfections or potential improvements that the human eye could otherwise miss.
Also continuously driving innovation, this digital transformation in Machine Learning and Applied Analytics for manufacturers now attracts younger talent entering the workplace, as most expect to work with this innovative technology. This trend is so desirable, many digital natives may even expect devices to talk to each other in the factory the same way devices interconnect at home.
The industry is recognizing Machine Learning and Applied Analytics technologies as already helping manufacturers unlock previously hidden opportunities and solve challenges.
Maximizing efficiencies throughout production runs are clear proof points for the legitimacy and value of this digital manufacturing transformation. Using Industrial IoT, manufacturers are seeing how they can improve output and productivity while reducing waste, leading to improved competitiveness and profitability over the long term.
How is IoT Different from IIoT?
Before we delve into what is IIoT, let’s take a step back and look further at IoT. In brief, this refers to the interconnectivity of separate machines, sensors and data sources over the internet. Connected devices have been entering our everyday lives over the last few years. They are available for everything from Google, Amazon and Apple all providing smart assistants for the home – to home security and even doorbells.
We are accustomed to connected devices in our everyday lives and increasingly expect to see the same efficient device interconnectivity in our workplace.
Enter Industrial IoT or IIoT
What is the difference between Iot and IIot? IIoT brings the same interconnectivity of IoT into the manufacturing process. Connected sensors, advanced analytics, and cybersecurity are all top of mind. Meanwhile, other connected devices are deployed across a whole range of collaborative processes. For example, additive manufacturing – such as 3D printing – is seeing significant IIoT development, as are augmented reality (AR) and virtual reality (VR) devices.
While in our personal lives we may use connected devices to count steps or calories burnt, with IIoT, manufacturers can assess factory performance at a granular level.
According to ZDNet, Tech Pro Research (2019) finds that 82% of manufacturers had either “implemented IoT, are running a pilot program, or are considering it.” The group also finds that 40% of respondents are not currently implementing any IoT systems due to a lack of in-house skills. The key focus for most (59%) is maintenance.
At Oden, we see four stages of development for factories embarking on their Smart Manufacturing journey:
The Connected Factory: Here, data is ingested, joined, analyzed and visualized with sensors, machines and systems connected to a central database that may include a cloud or hybrid environment. Data is more accurate and it is being used to address challenges and sport opportunities. Connectivity is the base level of Industrial IoT and necessary in order to advance into predictive and prescriptive analytics.
The Predictive Factory: Once you start aggregating your data into a centralized location, you’ll be able to use Machine Learning and Applied Analyticsto predict patterns and proactively solve issues. Predictive applications can identify potential problems, alert operators, and allow them to make adjustments necessary to minimize the impact.
The Prescriptive Factory: Leveraging historical and real-time data, Machine Learning models can actually recommend optimal settings and machine conditions to replicate your most profitable production runs. Executing optimal Golden Runs allows you to increase contribution margins by minimizing wasted resources.
The AI-Driven Automation Factory: This is the most advanced level of Industry 4.0, where manufacturers benefit from automated actions being taken that are based on data. Machine Learning and Applied Analytics technologies identify opportunities, generate new settings and actually instruct devices and machines to make positive, efficient actions.
What’s Next in IIoT and Industry 4.0?
The drive for efficiency will continue to put pressure on manufacturers to adopt digital technologies as they strive up the four stages of Smart Manufacturing.
We will see connected factories using predictive quality and maintenance applications as well as the wider use of prescriptive analytics. The ultimate goal is full automation, where the factory has the ability to execute a product run at highest possible efficiency without the need for human intervention.
What Are the Benefits of IIoT?
After answering the question “What is IIoT?,” it is important to next assess the business benefits of IIoT. Industrial IoT makes use of networks to aggregate data from connected devices while centralizing it on an IIoT platform where it can be processed and translated into meaningful insights.
Let’s look closely at three major benefits of IIoT that helps manufacturers make more, waste less and innovate faster.
Perfect Production with IIoT
Manufacturers are under constant pressure to decrease waste while increasing uptime, throughput and quality in order to remain competitive. IIoT can provide insights into variables or anomalies that can cause performance issues – machine failures, bottlenecks, product defects and waste. IIoT helps you future-proof your organization, create more customized products and reduce waste, which is better for the environment and lowers overhead.
Quicker Decision-Making with IIoT
IoT in manufacturing reduces human intervention and provides quicker data gathering from connected devices, which is then shared with centralized analytics. This helps perform maintenance when analytics highlight the need for it resulting in an ability to respond quicker to changing scenarios which will reduce waste and improve efficiency.
At Oden, we call this the “Golden Run,” when artificial intelligence and machine learning use data to identify the very best way to make a product to the manufacturer’s specified quality. With IoT in manufacturing at this level, producers know that their products are being created in the most efficient way possible.
Leveraging Integrations with IIoT
For devices to “talk” to each other they first need to speak the same language – or at least understand each other. Without this ability, it is difficult to draw meaningful insights.
This is why it is crucial that you unify systems around a single language, such as Open Platform Communications Unified Architecture (OPC UA). This provides a communications layer in a unified architecture that empowers devices to communicate and exchange data. The next step is to develop applied analytics and machine learning capabilities that will provide actionable insights to drive efficient productivity in the most economical way.
In short, manufacturers are finding the need for their devices to speak the same language and build an infrastructure that supports it.
Applying IIoT to Your Company
How can you apply IIoT to your organization? We have already covered the productivity, efficiency, competitiveness and even talent-attracting benefits of adopting Industrial IoT. By applying IIoT to your operation you are future-proofing it, making it ever more competitive, discovering trends that you never expected.
The key to applying IIoT is to be clear on what you want to get out of your IIoT project. What does success look like? Look at Oden’s Four Levels – where is your organization on its digital transformation journey? Start early, start small and build up a robust structure that supports further evolution.
Keep testing, keep learning and keep on gathering data for future use. Senior support is absolutely vital to drive forward Industry 4.0 projects. Also, make sure your leadership keeps staff updated on the objectives and roadmap of your IIoT program, and provide regular training opportunities to build up an engaged culture.
The Perfect IIoT Platform
The perfect IIoT platform is often top of mind and understanding where a factory stands on their digital transformation journey is key to turning Smart Manufacturing dreams into reality. Every organization’s situation is unique but here are a few key characteristics.
IIoT Enabling Infrastructure: Once network connectivity is confirmed, manufacturers can turn to their machines. When data architectures begin using modern protocols and data transfers like MQTT and OPC UA, IIoT becomes more reachable.
Centralized Process Data: The next stage is to aggregate key process data into a centralized location such as an OPC UA Server or a Historian, reducing overall need for hardware on the factory floor.
Multi-Source Data Interoperability: At this stage, manufacturers would be considered to be more aware of IIoT needs and the state of Industry 4.0, but if not managed correctly, multiple data sources can create headaches for personnel. ERP, QMS, MES, and Historians can all be essential in a factory’s ecosystem. If you do not have the right means to interconnect these systems you will have skilled workers spending weeks working through data to contextualize.
Real-Time Performance Data: When a factory connects their machines to an IIoT platform, machines will start reporting data on how they are operating with the context of what product and/or batch.
Predictive & Prescriptive Analytics: The ability for a machine to make predictions is powerful. It requires a complete and accurate set of data to teach the ML algorithms and from then moving forward, this approach leads to cost savings and higher productivity over time.
And these functions should all be imparting data to a shared analytics platform.
IIoT Applications Benefit Many Industries
Industrial IoT can be applied to any field – wire & cable, plastic, consumer packaged goods and more – because performance data is valuable to every organization.
Let’s take a look at the food and beverage sector as an example. This is an industry characterized by high volume/low margin manufacturing. There are seasonal, geographical, and health and safety considerations, and there is a desire for more automation and flexibility throughout the process from cleaning and prepping to packaging, labeling, quality control and logistics.
The food and beverage sector is expected to increase smart investments by 7% for the next five years. Players in this sector are asking “What is IIoT and how can it help me?” IIoT can help better understand production cycle, planning, quality control, reduction in waste, predictive quality and so much more.
What is IIoT? Get Oden’s Help
The future of manufacturing is already here. Removing tribal knowledge from operators and engineers empower projects that lead to greater value in higher production and lower waste. These distinctive initiatives attract the best new talent fueling the ability to remain competitive now and into the future. In this way, IIoT delivers incredible value throughout the supply chain and production line. It can help you operate in a more efficient, productive and ultimately profitable way.
To power this bold future, you need the right IIoT platform. Request a demo today.