Broadly speaking, the Industrial Internet of Things, also known as Industrial IoT or IIoT, is the application of instrumentation, connected sensors, and other devices to machinery and processes in industrial settings.

According to the BCG, 50% of IoT spending will be driven by discrete manufacturing, transportation and logistics, and utilities by 2020.

But what drives the adoption of IoT in manufacturing? After all, companies don’t have IoT problems – they have business problems.

IoT Spending by Industry BCG
IoT Spending by Industry


According to IDC, the leading use case for IoT in manufacturing is manufacturing operations. In 2016, this accounted for $102.5 billion out of $178 billion in total spending.

In this post, we’ll go over eight specific business use cases and applications in manufacturing operations, production asset management, and field services that are driving the adoption of Industrial IoT in manufacturing. 

1. Production Visibility

Industrial IoT can connect machines, tools, and sensors on the shop floor to give process engineers and managers much-needed visibility into production. For example, manufacturers can automatically track parts as they move through assemblies using sensors such as RFID and break beams. Furthermore, by connecting with the tools the operators use to perform their jobs and with the machines involved in production, Industrial IoT applications can give supervisors and plant managers a real-time view of their teams’ yield. This level of visibility can be used by manufacturers to identify bottlenecks, find the root cause of problems, and improve at a faster rate.

Industrial internet of thing production visibility dashboard application use case
IIoT production visibility dashboards can help manufacturers identify bottlenecks and track yield in real time

2. Higher operator productivity

Industrial IoT can increase the productivity of the manufacturing workforce in several ways. Let’s start with the operators. Using IIoT enabled tools, operators can go through workflows faster without compromising quality. For example, pick-to-light devices can help operators find the piece they need much more quickly and thus reduce their cycle time. Likewise, using IoT enabled tools such as torque drivers can speed up work by automatically adjusting the tool’s settings according to the operation they should be doing.

3. Faster improvement cycles

Operators aren’t the only ones who benefit from IIoT. Process engineers (as well as manufacturing engineers, quality engineers, and in general all frontline engineers in the shop floor) benefit as well. Without IoT, shop floor engineers must manually collect, aggregate, and analyze data. An IoT enabled shop floor, on the other hand, gives them the ability to automate data collection so they have more time to spend improving processes.

4. Reduce the cost of quality management systems

Quality management systems (QMS) are hard to implement and maintain. Industrial IoT can help reduce the costs associated with them by automating and streamlining the process control plan. Using sensors, manufacturers can automatically check variables that are critical to quality, thus reducing the time and resources dedicated to the QMS. Rather than manually performing quality inspections, they can use IoT sensors to streamline the process.

5. Improve quality through continuous monitoring

Environmental sensors can continuously monitor conditions critical to quality and alert management when quality thresholds are crossed. For example, in a pharmaceutical operation, temperature can be critical to quality. By using IoT connected temperature and humidity sensors, managers can monitor those variables and be instantly alerted if they go outside the expected parameters.

Tulip machine monitoring dashboard for new machine monitoring features
Continuous monitoring, like machine monitoring, can help you ensure asset health and performance in real-time

6. Increase machine utilization

Industrial IoT enables manufacturers to connect their machines to the internet. This capability lets manufacturers not only monitor their machines, but also measure important KPIs such as overall equipment effectiveness (OEE) and overall process effectiveness (OPE) in real-time. Tracking these metrics lets manufacturers identify and fix causes of unplanned downtime, provide preventive maintenance to their equipment, and thus increase machine utilization throughout the shop floor. In fact, a recent McKinsey article reported that sensor data used to predict equipment failure in a manufacturing environment can reduce maintenance costs by as much as 40 percent and cut unplanned downtime in half.

Dashboard for viewing OEE in real time with IIoT
Monitor the KPIs that matter most to you

7. Better facility management

Leveraging sensors in manufacturing facilities can improve their management and therefore reduce the operational costs of a factory. For example, using sensors such as RFID tags to monitor facilities, manufacturers can gain insights to help them optimize space usage. Another way in which IoT enabled sensors can help manufacturers better manage their facilities is by ensuring environmental variables such as temperature, humidity, or others, stay within the prescribed range. Lastly, manufacturers can conserve energy, reduce costs, and increase operational efficiency by using sensors to monitor machinery and ensure they are operating within their prescribed working environment.

8. Supply chain optimization

IoT enabled sensors to permit monitoring of events across a supply chain, providing access to real-time information by tracking inputs, equipment, and products. RFID tags and other sensors can be used to track inventory as it moves around the supply chain. This provides manufacturers visibility into inventories and more realistic timelines for material availability, work in progress, and so on. Using this data, manufacturers can identify interdependencies, map material flow, and track manufacturing cycle times. This data helps manufacturers predict issues. It also reduces inventory and potentially reduces capital requirements.

IIoT helps with supply chain optimization
All of your inventory information is stored in no code tables. When inventory is used during operations, the tables automatically update.

Getting started

There are no shortages of use cases and applications for Industrial IoT in manufacturing. However, a study by Cisco revealed that 60% of IoT projects fail at the proof of concept stage.

Two reasons are often cited for this failure.

First, manufacturers often lack the IoT skillset needed to build these systems from the ground up. To address this challenge, manufacturers can turn to IoT platforms or app platforms that let non-engineers develop IoT applications.

A second reason IoT projects tend to fail is that they don’t achieve ROI. One way manufacturers address this issue is by starting small.

Rather than trying to completely cover your operation with sensors, pick one specific area you want to tackle. Once you are able to show a return on investment, you can scale up. Off-the-shelf IoT sensors or quick-start kits like Tulip’s Factory Kit can help you achieve this.

Read our Case Studies to see how companies concretely applied Industry 4.0 use cases with Tulip.