Why IIoT monitoring in manufacturing will improve the bottom line

Opinions expressed in this article are those of the author.

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Daniel Sultana - APAC Regional Director at Paessler. Image Provided
Article by Daniel Sultana, Regional Director for Asia Pacific at Paessler

Most manufacturers are aware the collection of data is critical to help improve operations, but they may not be sure exactly how the Industrial Internet of Things (IIoT) can drive manufacturing productivity and profitability to impact their business’s bottom line.

IIoT adds value by collecting data from sensors attached to the physical assets in a plant, feeding this data into software where analytics can drive actionable insights. This enables faster and better decision-making around how equipment is performing as well as how each asset is being utilised.

An IIoT network can include sensors, computers and machines used in manufacturing. Now manufacturers are realising the benefits such as a rise in bottom-line performance due to the insights obtained from historical and real-time analysis of this enormous data repository.

IIoT is mainly used for predictive maintenance

The failure of a single piece of equipment can bring an entire production line to a grinding halt. For every hour that production is stopped, it can cost a manufacturer hundreds of thousands of dollars. When such downtime occurs, the overhead costs are on the rise, but the production value is zero.

Production delays caused by a maintenance bottleneck can lead to disappointed customers, cancelled contracts and upheaval in the supply chain, which heavily impacts the bottom-line performance of a manufacturing company.

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At the same time, equipment is becoming more complex and it’s not always obvious when is the best time to perform maintenance checks and repairs. But what if manufacturers could use data from IIoT devices to predict when their assets need maintenance?

Predictive maintenance uses installed or embedded devices to collect data about a machine’s actual health and performance, such as temperature, pressure and vibration frequency. Once collected, the data is combined with metadata (such as the machine’s model, operational settings and configuration), equipment usage history, maintenance data and more. This combined data is then analysed and run through machine learning algorithms to identify any abnormal patterns that could lead to machine failures.

This not only predicts what needs to be done but also when it can or should be done. For example, depending on the equipment, minor adjustments can be automated during run-time until a full repair can be made during the next scheduled downtime. Or repairs can be performed when maintenance or technology involvement is most cost-effective, such as during changeovers.

Once a potential failure is identified, the relevant people in the plant receive notifications which prompt maintenance action, enabling manufacturers to be more proactive and less reactive. IIoT applications can also monitor maintenance programs across the supply chain and enable remote communication to notify of any issues at any point that could cause any delays.

What other benefits does IIoT offer manufacturers?

In the manufacturing industry, IIoT is used for supply chain management and supports real-time communication between suppliers, manufacturers, storage facilities, delivery companies and customers. IIoT can actually minimise human error in inventory management.

IIoT also enables the centralised management of assets and since it requires less human labour it ultimately reduces the costs of goods and services. When applied at scale, IIoT can result in considerable savings on assets, increased efficiencies and a longer life-cycle for equipment assets.

How can monitoring keep IIoT operational?

A network has three main layers: the physical layer that includes sensors and physical devices, the network layer that connects devices and that is the IoT or IIoT gateway and the application layer that delivers the data. IIoT devices and sensors communicate through a gateway that allows them to share data over a network.

Basic IIoT device management includes verifying the authenticity of enrolled devices, resetting decommissioned devices, reconfiguring new devices, diagnosing software bugs and operational anomalies, updating software, suggesting maintenance schedules and monitoring data usage and uptime.

Some of the functions of device connectivity and network management include limiting data usage, throttling data where necessary, providing usage measurements and alerts, customising content, securing content, limiting access to business-critical information, and allowing custom features based on roles.

The same vulnerabilities that affect computer hardware and software outside of IIoT systems affect the IIoT as well. Hardware defects, firmware and software bugs, lack of maintenance, faulty parts, and the use of devices in extreme conditions can contribute to device failures.

Despite efforts to combat cybercrime, the number of cyberattacks increases daily. Critics argue that the IIoT is particularly vulnerable to cybercriminals. One reason for this is that smart devices can be accessed, operated and managed remotely.

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