The Industrial Internet of Things, or IIoT for short, is an incredibly powerful advancement in manufacturing and processing technology. Whilst many have always focused on physical robots handling goods and products, IIoT instead looks at how industrial devices coexist and share data with each other.

This interconnected ecosystem is reshaping traditional industrial practices and heralding a new era of smart production systems. In this article, we take a look at how IIoT has made its mark in the manufacturing world, looking at its uses, benefits, and real life applications.

What is the Industrial Internet of Things?

The Industrial Internet of Things (IIoT) is the integration of internet-connected devices, sensors, and software applications within industrial environments, such as manufacturing, health, and energy.

This technology enables the collection, exchange, and analysis of real-time data from machines and systems.  IIoT aims to enhance efficiency, productivity, and decision-making in industrial processes by using connectivity and data-driven insights to drive innovation and competitive advantage.

The two fundamental aims behind IIoT’s are:

  1. Performing superior data analysis to humans
  2. Communicating data analysis more efficiently than humans

How does IIoT help industrial practices

The Industrial Internet of Things plays a pivotal role in revolutionising traditional industrial practices and paving the way for a new era of smart factories. IIoT offers a wide range of benefits that are reshaping the industry landscape.

  • Efficiency and optimisation - IIoT optimises production processes by collecting real-time data from sensors embedded in machines and equipment. This data enables manufacturers to identify inefficiencies in supply lines, reduce downtime, and maximise resource usage.
  • Quality control -  by enhancing quality assurance, IIoT continuously monitors production parameters and product quality. Smart sensors detect deviations,  therefore minimising defects.
  • Predictive maintenance -  by implementing IIoT-enabled predictive maintenance, manufacturers can anticipate equipment failures before they occur. This proactive approach minimises downtime, extends equipment lifespan, and reduces maintenance costs.
  • Supply chain integration: IIoT integrates supply chain processes, from procurement to distribution, enhancing visibility and efficiency. Real-time data exchange enables agile responses to demand fluctuations and improves inventory management.
  • Innovative production models: IIoT enables flexible and adaptive production models such as mass customization and just-in-time manufacturing. Connected systems facilitate agile production processes that respond quickly to market demands.

IIoT implementations

IIoT solutions encompass a diverse array of technologies and devices tailored to meet the unique demands of industrial environments. These solutions leverage interconnected devices, advanced analytics, and cloud-based platforms to drive innovation and optimise manufacturing operations.

Let’s take a closer look at how industries are implementing IIoT into their everyday processes:

  • Sensor networks - sensor networks capture real-time data from equipment, machines, and production lines through small devices recording conditions in the environment. Sensors measure variables such as temperature, pressure, vibration, and humidity, which help optimise the condition of products within.
  • Edge computing - IIoT uses edge computing to process data closer to the source, reducing latency and enabling faster decision-making. Edge devices perform data filtering and analysis locally before transmitting relevant information to a central cloud platform.
  • Cloud-based platforms - cloud-based platforms enable data storage, analytics, and visualisation in the cloud, thus providing all the information needed in one secure place. These platforms integrate with enterprise systems to deliver insights to workers, allowing them to remotely monitor and control assets.
  • Communication protocols - communication is key for IIoT. These devices use communication protocols such as Message Queuing Telemetry Transport (MQTT)  and Open Platform Communications Unified Architecture (OPC UA) to ensure secure and reliable data transmission between devices and systems.
  • IoT gateways - IoT gateways serve as communication hubs, compiling data from multiple sensors and devices within a specified area. These gateways preprocess and filter data before transmitting it to the cloud or enterprise systems.
  • Industrial robots - IIoT-enabled robots are equipped with sensors and actuators to perform complex manufacturing tasks autonomously. These robots optimise production efficiency and aid in streamlining processes.
  • Connected assets - implementing IIoT allows for connectivity between multi-level industrial assets, such as pumps, motors, and conveyor belts. Manufacturers can implement predictive maintenance strategies and minimise downtime through these connections.
  • Wearable devices - wearable devices equipped with IIoT capabilities enhance worker safety and productivity. These devices track employee health, location, and activity levels. In turn, this improves workplace efficiency and reduces any potential hazards.

The benefits of Industrial IoT

The Industrial Internet of Things is reshaping the manufacturing world, offering a wide range of benefits that drive operational efficiency and competitive advantage. Here are some of the key benefits that IIoT is bringing to the workplace:

1. Efficiency

At the forefront of IIoT is efficiency. Every device or implementation of it, in some shape or form, essentially eases the processing for many different industries. Some examples include:

  • Monitoring equipment performance
  • Analysing production production metrics
  • Identifying inefficiencies or defects
  • Minimises waste
  • Reduces downtime

This improved operational efficiency translates into increased productivity and lower manufacturing costs.

2. Predictive Maintenance

Another key advantage of IIoT is predictive maintenance, which helps manufacturers transition from reactive to proactive maintenance strategies. Predictive maintenance predicts equipment failures before they occur, allowing for timely repairs and preventing costly breakdowns. 

This approach extends equipment lifespan, reduces maintenance costs, and ensures uninterrupted production.

3. Quality Assurance

IIoT improves quality assurance by determining whether a product meets its required criteria. By using smart sensors to detect deviations and anomalies in real-time, IIoT allows manufacturers to identify and address quality issues early on. 

This switch to a proactivity goes hand in hand with predictive maintenance. This ensures that defects or inefficiencies have minimal impact on later production and customer satisfaction.

4. Supply Chain Optimisation

In the manufacturing world, every second counts. By introducing IIoT to regular processes, manufacturers can save time and money in the long run through its efficiency. 

Connecting suppliers, manufacturers, and distributors through IoT-enabled systems, IIoT enhances supply chain visibility, reduces lead times, and improves inventory management. Manufacturers can respond quickly to market demand fluctuations and ensure timely delivery of goods to customers.

5. Safety and Risk Management

Workplace safety is paramount and IIoT can assist in monitoring work conditions and employee activities in real time. 

Through wearable devices and safety equipment, IIoT can provide insights into worker health and safety, allowing manufacturers to mitigate risks and prevent accidents. IIoT also supports compliance with regulatory standards and fosters a culture of continuous improvement in occupational safety.

6. Data-Driven Decision-Making

Last, but definitely not least, IIoT gives manufacturers the insights they need to empower their entire process, all derived from collected data. 

Through vast analysis, IIoT provides a deeper understanding of production processes and consumer preferences. This data-driven approach enables informed decision-making, facilitates agile responses to market changes, and drives innovation in product development and service delivery.

The key part here is that, not only does IIoT collect the data, it also gives manufacturers the answers on how to act next. This is a big step from reactivity to proactivity.

Real life applications of IIoT

1. Predictive Maintenance at Rolls-Royce

Rolls-Royce uses IIoT for predictive maintenance of its jet engines. By embedding sensors in engines to monitor performance metrics such as temperature, pressure, and vibration, Rolls-Royce can detect anomalies and predict potential failures before they occur. 

2. Smart Manufacturing at Bosch

As a global supplier in technology and services, Bosch embraces IIoT to create smart manufacturing environments. Through its Industry 4.0 initiatives, Bosch integrates connected devices, robotics, and data analytics to optimise production processes. 

3. Remote Asset Monitoring at Caterpillar

Caterpillar (or Cat), a leading manufacturer of construction and mining equipment, uses IIoT for remote asset monitoring and management. This allows the business to track equipment health, location, and performance in real time.

4. Supply Chain Optimization at Nestlé

Being one of the world’s leading food and beverage companies, Nestlé optimises supply chain management through IIoT. Through its "Smart Agriculture" initiatives, Nestlé collaborates with farmers to implement IoT-enabled sensors that monitor crop conditions and optimise irrigation practices. farming practices, improves crop yields, and enhances transparency across the supply chain.

What is the difference between IIoT and AI in manufacturing?

Industrial Internet of Things and AI in manufacturing are fundamentally similar ideologies. However, their implementation is slightly different, with slight variations in their focus, technology, and applications.

  • Data - both systems will deal with data to assist manufacturers. However, IIot focuses more on collecting data, whilst AI assists more with the analysis.
  • Automation - whilst IIoT whilst physically automating processes, AI assists with automating decision-making and other related tasks.
  • Efficiency - both systems will help manufacturers streamline their business processes, either by providing data (IIoT) or taking action (AI). 

The line is blurred between where AI steps in, so it is important to remember that both systems will rely on each other intrinsically to reach their goals.

What’s next for industrial IoT?

IIoT's impact is profound and has revolutionised traditional processes, thus paving the way for smart factories and agile production systems. Looking ahead, there are plenty of more opportunities for IIoT to evolve, especially with edge computing and the relationship between itself and AI.

We’re excited to see what’s in store for the future of manufacturing. See the latest on the PPMA Show website and explore what’s in store for our next show.

IIoT frequently asked questions

What are the risks associated with Industrial IoT?

IIot is vulnerable to cybersecurity threats, such as data breaches and unauthorised access. Also, reliance on interconnected devices may introduce complexities related to system integrations, meaning when things go offline, it will affect all other connected areas.  

What is a real life example of IIoT?

Predictive maintenance is a key example of IIoT. Sensors embedded in equipment continuously monitor performance metrics, sending real-time data to a centralised system.

Can IIoT replace MES?

IIoT is not intended to replace MES but rather to enhance its capabilities through data integration and connectivity. Whilst IIoT provides real-time data from connected devices and machines, MES focuses instead on managing production processes.

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