Digital transformation is on everyone’s lips. More and more often we hear about yet another industry reinvented through modern technology, managing to optimize dated workflows, improve overall productivity, or offer a completely new kind of product to consumers. Manufacturing is not an exception.

The Internet of Things is the biggest name among the many innovative technologies that are entering the industrial sector today. From Airbus building a “factory of the future” equipped with integrated sensors and wearables to Komatsu tracking international mining operations using IoT, it’s safe to say that major global businesses are now assigning mission-critical tasks to IoT-based systems and devices.

So what is IoT in manufacturing and how is it able to help various companies successfully implement digital transformation programs? If you are new to the topic, this article will help you get acquainted with the basics and answer the questions that might pop up along the way.

What are Industry 4.0 and IIoT?

Loosely defined, the Internet of Things is a term that describes a system of devices (or ‘things’) connected to and communicating via a common network. Beyond personal computers or smartphones, IoT includes devices that were not originally designed with such connectivity in mind — for example, refrigerators or harvesting tractors or ACs.

The proliferation of IoT is one of the key factors enabling Industry 4.0 — the new era of industrial production that favours digital tech and all-encompassing automation. IIoT is the subdivision of IoT that deals with streamlining industrial workflows and addresses Industry 4.0 challenges, such as growing customer expectations, demand for customization, and complex supply chain management.

Businesses that opt for IIoT implementation equip every step of production, from ordering raw materials to delivering the finished product to the consumer, with specialized devices and software. This allows to make the entire process more transparent and manageable than ever before.

What are the benefits of the Internet of Things in manufacturing?

To stay competitive and return a good profit in the era of Industry 4.0, enterprises need to be ​​​​​agile with tangible objectives, and react promptly to changes in supply and demand. IoT in manufacturing helps enterprises to perform this transformation on the shop floor and boost the role of data in critical decision-making. Let’s take a closer look at the tangible benefits of IIoT-driven digital transformation.

According to an IIoT study carried out by BPI Network, surveyed enterprise executives and innovation leaders see the following as the top benefits of IIoT:

The Impact of Connectedness on Competitiveness

“Operational improvements are expected to deliver the main source of increased value and business performance from IIoT. New capabilities around predictive maintenance, operational intelligence, self-diagnostics, and automation all point to a world with less equipment downtime, higher performance levels, and smarter, more efficient operations.”
© From “The Impact of Connectedness on Competitiveness” by BPI Network

All of these are in some way related either to the increase in transparency or to faster communication, which we can consider the two basic benefits of IoT in manufacturing. Sensors and devices installed throughout manufacturing facilities ensure better monitoring of operations via continuous logging of activities and machinery status. As the next step, this monitoring can be translated into better KPI adherence and enhanced supply chain traceability.

Importantly, Industrial IoT systems can collect and transfer a wealth of data in real time, which means that users are able to view the status of industrial assets anytime, no matter how remote.

The immediacy of data sharing is crucial for on-the-go decision-making, real-time alerts, and quicker response times in case of issues. Instead of regular checkups that might miss the problem, staff can schedule maintenance based on need, reducing unnecessary downtime.

“One of the priority areas to make our production tool even more efficient is the real-time management of our plants and their supply chain. This means that we can immediately respond to a problem, rather than waiting for an end-of-day assessment.”


Eric Marchiol

Director of Manufacturing Digital Transformation at Groupe Renault

Your Guide to IoT-driven Digital Transformation in Manufacturing

How we can help

Oxagile team of experienced IoT engineers can help you implement industrial IoT solutions to introduce new manufacturing efficiencies and make a decisive step into the era of Industry 4.0. Find more about our Industrial IoT capabilities.

Full-cycle IIoT development

The development of a custom Industrial IoT system is a complex process that involves multiple trials and performance checks before the solution can be considered ready for enterprise-wide scaling.

It all starts with a new product idea that requires rigorous analysis of technical requirements followed by functional and schematic design and prototyping. This results in a proof of concept with completed printed circuit board design, routing, verification and board bring-up.

At the following stage, firmware design and development lead to the production of the first device sample that undergoes comprehensive QA and testing. Provided the sample passes all tests and certifications with flying colors, the team creates a pilot device and starts preparing the shop floor for mass production and large-scale quality control.

Use cases of Industrial IoT in manufacturing

Smart factories

Smart factories, also known as connected factories, utilize the Internet of Things to optimize manufacturing processes rather than certain tasks. Sensors, smart devices, and cloud-based data analytics systems work together to support smooth factory operation and introduce new efficiencies.

One example is a Stanley Black & Decker smart factory in Mexico that managed to achieve a 24% increase in production of routers used for woodworking thanks to its IoT program. On the other side of the globe, a leading automotive company Magna Steyr employed IoT across various departments: by tracking industrial assets such as tools and vehicle components, setting up automated materials ordering, remotely monitoring components its warehouses via Bluetooth-enabled “smart packaging”, and using self-driving vehicles to transport parts to assembly lines.

Predictive equipment maintenance

One of the most popular use cases for IoT in manufacturing is sensor-driven machinery monitoring that enables workers to know exactly when and where maintenance is needed. Intelligent tools can control the performance of critical equipment 24/7, proactively identify malfunctions or wear, and issue automatic alerts. Besides serving the manufacturing process itself, this technology can be used to assess the usage of the product after shipping, protecting the manufacturer from faulty warranty claims.

ABB, a major supplier of industrial robots, is using IoT sensors to collect data about every robot’s performance, giving engineers the ability to make predictive maintenance decisions and avert equipment failure without interrupting production. Another robotics company Fanuc has developed the FIELD System that supports various Industrial IoT applications within a factory and focuses on interconnecting edge heavy devices such as machine tools, robots, PLCs and sensors.

Industrial asset management

Ineffective asset management in manufacturing can result in significant losses, and the larger the facility the bigger the damage will be. Industrial IoT systems designed for asset management typically use cheap and easy-to-manage RFID transponders or Bluetooth trackers to streamline warehouse management, inventory management, supply replenishment, and similar activities.

Caterpillar’s Asset Intelligence platform leverages vast amounts of sensor data to fuel advanced predictive analytics and provide advisory services to vessel and fleet operators. The AI-based solution turns siloed data into advanced reports and visual dashboards that give engineers deep insights into the state of critical systems. This knowledge not only helps prevent costly repairs, but can be used to optimize energy consumption.

IoT for Marine Vessel Monitoring

Workplace safety

Protecting workers is a priority for every manufacturer. In the era of Industry 4.0, keeping workers safe and healthy becomes a simpler task thanks to IIoT. Wearable worker communication solutions connect every employee on the shop floor with the centralized workplace safety system that monitors strict compliance with safety regulations and sends out safety alerts to prevent injury in potentially hazardous scenarios (e.g., a worker entering a no-go zone).

North Star BlueScope Steel deployed wearable trackers in helmets and wristbands that factory workers use. The devices are equipped with health metrics sensors as well as environment sensors to measure temperature, radiation levels, and detect toxic gases in the air.

Current trends for IoT in manufacturing

Even with the blow dealt by the pandemic, the global IoT spending is expected to return to double-digit growth in 2021 and achieve a CAGR of 11.3% over 2020-2024. New applications and use cases of Industrial IoT bring never-before-seen opportunities to manufacturers. As the technology continues to mature and expand, we can pinpoint several main trends that are driving innovation forward.

Cyber-physical systems. Such systems combine the power of embedded computers and networks with physical systems, creating feedback loops where the physical process can influence computations and vice versa.

5G connectivity. Wide adoption of 5G will serve as an additional boost for IoT-enabled manufacturing solutions. 5G will enable tighter control in critical real-time applications, for example in heavy machinery operations and remote surgeries.

Digital twins. Digital twins are exact virtual models of industrial assets or processes. As defined by GE Digital, “every digital twin includes a data model, a set of algorithms, and knowledge”. A digital twin is used to understand and improve the performance of the physical twin.

Artificial intelligence. AI-powered analytics solutions learn to identify patterns in smart sensor data and detect anomalies in the readings. While regular business intelligence solutions typically react to numeric thresholds, artificial intelligence is able to make accurate predictions faster.

Biggest challenges of IIoT adoption

Let’s look at the key issues that manufacturers face on the path to IIoT implementation.

The pitfalls of IoT implementations for manufacturers

The pitfalls of IoT implementations for manufacturers

Summing up

Industrial IoT in manufacturing is a powerful factor of innovation that nevertheless requires full commitment from all stakeholders to yield lasting results. Traditional enterprises often lack the IT expertise necessary to undertake this transformation on their own. It is common to see large-scale IIoT programs brought to life with the help of IT technology partners.