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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.
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.
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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, organizations 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 the 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 organizations to identify bottlenecks, find the root cause of problems, and improve at a faster rate.
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 operation) benefit as well. Without IoT, operation engineers must manually collect, aggregate, and analyze data. An IoT-enabled operation, 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, organizations 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, the 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.
6. Increase machine utilization
Industrial IoT enables organizations to connect their machines to the internet. This capability lets organizations 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 organizations identify and fix causes of unplanned downtime, provide preventive maintenance to their equipment, and thus increase machine utilization throughout the operation. 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.
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, organizations can gain insights to help them optimize space usage. Another way in which IoT-enabled sensors can help organizations better manage their facilities is by ensuring environmental variables such as temperature, humidity, or others, stay within the prescribed range. Lastly, organizations 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 organizations visibility into inventories and more realistic timelines for material availability, work in progress, and so on. Using this data, organizations can identify interdependencies, map material flow, and track manufacturing cycle times. This data helps organizations predict issues. It also reduces inventory and potentially reduces capital requirements.
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, organizations often lack the IoT skillset needed to build these systems from the ground up. To address this challenge, organizations can turn to IoT or operations 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 organizations 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.
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