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Production downtime and factory productivity are closely related because factories can Losses up to 20% Downtime causes its productivity to drop.
The most common cause of production downtime is equipment failure or malfunction. However, through predictive maintenance strategies using the Internet of Things (IoT), cloud computing and analytics, equipment failures and downtime can be reduced.
The collection of equipment and environmental data takes place through sensors. This data is used to proactively predict and repair equipment failures. Over time, advances in machine learning can improve the accuracy of forecasting algorithms and allow you to build advanced forecasting models.
Related: How cloud-agnostic hardware is the future of IoT
Why reduce downtime?
A study showed that 46% of manufacturers Unable to provide service to customers due to unexpected equipment failure. Unplanned downtime can also result in lost production time for critical assets and hinder a manufacturer’s ability to service or support a specific asset or equipment.
Unplanned downtime affects all industries, and its impact extends beyond the financial scope of some industries. According to an article in Petro Online, the single, Unplanned downtime A year’s worth of emissions into the atmosphere at a refinery or petrochemical plant.
Why use IoT for predictive maintenance?
It is necessary to understand IoT monitoring needs to understand its impact on downtime. An IoT monitoring system consists of four elements:
The first step in IoT monitoring is to collect data from the physical environment, which requires sensors. Sensors have special electronics that sense input from the physical environment and convert it into data for interpretation by machines or humans. Inputs include heat, light, moisture, sound, pressure, or electromagnetic fields.
Sensors collect data and send it to the cloud for analysis. There are several ways to relay data, including WiFi, satellite, cellular, Bluetooth, or a direct connection to the internet via Ethernet. The type of connection used depends on factors such as power consumption, range, bandwidth and security.
3. Data processing
When the data arrives in the cloud, it is processed by the software. There are many software solutions available for different IoT use cases. These solutions analyze data and present it to end users in an easy-to-understand format. For example, you can set the sensor to display device vibration and temperature data every three seconds. Alternatively, you can run complex analytics on large volumes of IoT data and trigger appropriate actions.
4. User Interface
End users can receive data via web, email or text notification. For example, your plant manager may receive a text/web/email alert when a temperature sensor reading exceeds a certain threshold. Managers can then remotely adjust the temperature via their web or mobile app, or trigger another remedial action to bring the temperature to a safe level.
Related: 4 Reasons Why the ‘Internet of Things’ Is Exciting
What is the role of IoT in reducing production downtime?
IoT can be the key to minimizing downtime and maintaining high productivity levels. The reasons for implementing an IoT-based predictive maintenance strategy are discussed below.
1. Can monitor equipment in real time
Real-time monitoring of asset condition and performance enables you to predict problems before they occur. Any required maintenance can be performed as soon as the alarm occurs, helping to prevent costly breakdowns or any impact on plant performance. Timely maintenance also helps maximize the life of your equipment – you can avoid premature equipment replacement and get the full return on your investment.
2. Equipment maintenance time can be optimized
Predictive maintenance runs in the background, keeping you informed of machine condition and performance. You will be alerted to deviations from optimal conditions, which will tell you if or how your equipment is aging or degrading. Using this information, you can accurately predict when a system is likely to fail and determine when to fix it.
Since exceptions are forwarded soon after they are discovered, any problems with the machine are less likely to go unnoticed and worsen. If deemed necessary, repairing in the early stages of equipment degradation will not take the time normally associated with unplanned and planned maintenance.
3. You can spend less on repairs and parts
Predictive maintenance is data-driven and analytical, enabling you to find the root cause of a problem, not just treat its symptoms. Understanding what can cause equipment failure can help prevent the wear and tear that causes equipment failure. For example, alerts about poor humidity can help reduce electrostatic discharge in low-humidity environments. Component degradation can be avoided, and equipment repair costs and spare parts inventories 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) may require workers to access difficult or dangerous bearings. With predictive maintenance, workers can check the condition of bearings without touching them. Smart sensors can collect information about the pressure and temperature of liquids flowing through pipes without direct human intervention.
When to use IoT
- Reduce unplanned downtime
- Reduce machine maintenance costs
- Enhance worker safety
- Reduce time to repair machines
- make better use of equipment
- Improve equipment ROI
It is useful for critical assets that have the greatest impact on productivity and profitability. IoT monitoring is also valuable when small changes in environmental conditions can significantly impact product quality or worker safety. For example, sensors detect the presence of an operator in a hazardous environment or the failure of rotating machinery.
Data from IoT devices can be integrated with workforce solutions to develop work schedules that reduce worker exposure to hazardous conditions. As a passive safety solution, IoT can help boost worker confidence and morale.
Related: The ‘Internet of Things’ is changing the way we look at the global product value chain