How the Internet of Things can increase productivity

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Downtime and plant productivity are closely linked, as a plant can lose up to 20% of its productivity due to downtime.

The most common cause of production downtime is equipment malfunction or failure. However, it is possible to reduce equipment failures and reduce downtime with a predictive maintenance strategy that uses the Internet of Things (IoT), cloud computing, and analytics.

The collection of equipment and environmental data is done through sensors. The data is used to proactively predict and correct equipment failures. Over time, advances in machine learning can improve the accuracy of predictive algorithms and allow you to build advanced prediction models.

Related: How cloud-agnostic hardware could be the future of IoT

Why minimize downtime?

A study reveals that 46% of manufacturers fail to provide services to customers due to unexpected equipment failure. Unscheduled downtime also results in lost production time on a critical asset and hinders manufacturers’ ability to maintain or support specific assets or equipment.

Unplanned downtime affects all industries, and its impacts extend beyond the financial aspect for some. According to an article by Petro Online, a bachelor, unscheduled downtime in an oil refinery or petrochemical plant releases a year’s worth of emissions into the atmosphere.

Why does predictive maintenance use IoT?

It helps to understand what IoT monitoring entails to understand its implications for downtime. An IoT monitoring system consists of four elements:

1. Sensors

The first step in IoT monitoring is to collect data from the physical environment, which requires sensors. Sensors have specialized electronics that detect inputs from the physical environment and convert them into data for interpretation by machines or humans. Inputs include heat, light, humidity, sound, pressure, or electromagnetic fields.

2. Connectivity

Sensors collect data and send it to the cloud for analysis. Several methods are available to relay data, including WiFi, satellite, cellular, Bluetooth, or a direct connection to the Internet via Ethernet. The type of connectivity used depends on factors such as power consumption, range, bandwidth, and security.

3. Data processing

When data arrives in the cloud, it is processed by software. There are many software solutions available for different IoT use cases. The solutions analyze the data and present it to end users in an easily understandable format. For example, you can configure sensors to display equipment vibration and temperature data every three seconds. Or you can run sophisticated analysis on a massive amount of IoT data and trigger the appropriate action.

4. User interface

The end user can receive the data via web notification, email or SMS. For example, your plant manager can receive an SMS/web/email alert when the temperature sensor reading exceeds a certain threshold. The manager can then remotely adjust the temperature from their web or mobile app or trigger another corrective action that brings the temperature back to a safe level.

Related: 4 Reasons to Be Excited About “The Internet of Things”

What is the role of IoT in reducing production downtime?

IoT can be the key to minimizing downtime and maintaining high levels of productivity. Here is a discussion of the reasons for implementing an IoT-based predictive maintenance strategy.

1. You can monitor the equipment in real time

Real-time monitoring of asset health and performance lets you anticipate problems before they occur. Any required maintenance can take place within moments of an alert, preventing costly breakdown or any impact on plant performance. Timely maintenance is also helpful in maximizing the useful life of equipment – you can avoid having to replace equipment too soon and get the full return on your investment.

2. You can optimize equipment repair time

Predictive maintenance runs in the background, keeping you informed of machine health and performance. You are alerted to deviations from optimal conditions, which tell you if and how your equipment is aging or degrading. Using this information, you can accurately predict when the system is likely to fail and determine when to fix it.

As anomalies are reported soon after they are detected, any problem with a machine is unlikely to go unnoticed and escalate. If deemed necessary, early stage corrective action to equipment degradation will not take the hours usually associated with unscheduled and scheduled maintenance.

3. You can spend less on repairs and parts

Predictive maintenance is data-driven and analytical, allowing you to get to the root cause of a problem rather than just addressing its symptoms. Knowing what can lead to equipment failure is helpful in preventing wear and tear that can lead to equipment failure. For example, suboptimal humidity alerts help reduce electrostatic discharge produced in a low humidity environment. Component degradation can be avoided and equipment repair costs and spare parts inventory can be optimized to the desired level.

4. You can keep workers safe

Putting sensors in charge of detecting equipment problems bodes well for worker safety. For example, checking for bearing failure, a common cause of downtime, can require workers to access bearings that are difficult or dangerous to reach. With predictive maintenance, workers can check the condition of bearings without touching them. Smart sensors can gather information about the pressure and temperature of liquids flowing through pipes without requiring direct human intervention.

When to use IoT

  • Reduce unplanned downtime
  • Reduce machine repair costs
  • Improve worker safety
  • Reduce machine repair time
  • Enable better use of equipment
  • Increase equipment ROI

It is useful for critical assets that have the greatest impact on production rate and profitability. IoT monitoring is also valuable when minute changes in environmental conditions can significantly affect product quality or worker safety. For example, sensors detect the presence of an operator in a hazardous environment or faults on rotating machines.

Data from IoT devices can be integrated with workforce solutions to develop work schedules that can reduce worker exposure to hazardous conditions. As a passive safety solution, IoT can help improve worker confidence and morale.

Related: “The Internet of Things” Is Changing How We View the Global Product Value Chain

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