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Production downtime and factory productivity are closely related, as a factory can lose up to 20% of its productivity due to downtime.
The most common cause of production downtime is a malfunction or failure of equipment. However, with a predictive maintenance strategy that leverages the Internet of Things (IoT), cloud computing, and analytics, it is possible to reduce device failures and keep downtime to a minimum.
Device and environment data is collected via sensors. The data is used to proactively predict and troubleshoot device failures. Over time, advances in machine learning can improve the accuracy of prediction algorithms and allow you to create advanced prediction models.
Also see: How cloud-agnostic hardware could be the future of IoT
Why minimize downtime?
A study shows that 46% of manufacturers fail to provide services to customers due to an unexpected equipment failure. Unplanned downtime also results in lost production at critical assets and impacts manufacturers’ ability to service or support specific assets or equipment.
Unplanned downtime affects all industries, and for some its impact extends beyond the financial. According to an article in Petro Online, a single, unplanned shutdown at an oil refinery or petrochemical plant releases a year’s emissions into the atmosphere.
Why does predictive maintenance use IoT?
It pays to understand what monitoring the IoT entails to understand its impact on downtime. An IoT monitoring system consists of four elements:
1. Sensors
The first step in IoT monitoring is collecting data from the physical environment, which requires sensors. Sensors have specialized electronics that capture inputs from the physical environment and convert them into data for machine or human interpretation. Inputs include heat, light, moisture, sound, pressure, or electromagnetic fields.
2. Connectivity
Sensors collect the data and send it over the cloud for analysis. There are several methods available to transfer the data, including WiFi, satellite, cellular, Bluetooth, or connecting directly 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 the data reaches the cloud, it is processed by software. There are many software solutions for different IoT use cases. The solutions analyze the data and make it available to end users in an easy-to-understand format. For example, you can set up sensors to display device vibration and temperature data every three seconds. Or you can perform sophisticated analysis on a massive amount of IoT data and trigger appropriate actions.
4. User Interface
The end user can receive the data via a web, email or text notification. For example, your operations manager can receive a text/web/email notification when the temperature sensor reading exceeds a certain threshold. The manager can then remotely adjust the temperature via their web or mobile app, or trigger any other remedial action that will bring the temperature to a safe level.
Also see: 4 reasons to be excited about the Internet of Things
What role does IoT play in reducing production downtime?
IoT can be the key to minimizing downtime and maintaining high levels of productivity. Here is a discussion of why to implement an IoT-based predictive maintenance strategy.
1. You can monitor devices in real time
With real-time monitoring of asset health and performance, you can anticipate problems before they occur. Any required maintenance can be performed immediately after an alert, preventing a costly outage or impact on plant performance. Timely maintenance is also helpful in maximizing equipment life – you can avoid having to replace equipment too soon and get the full return on your investment.
2. You can optimize the time it takes to repair devices
Predictive maintenance runs in the background and keeps you up to date on machine health and performance. You will be alerted to deviations from optimal conditions, giving you insight into whether or how your equipment is aging or deteriorating. The information allows you to accurately predict when the system is likely to fail and determine when it will need repairs.
Since anomalies are reported shortly after they are detected, a problem with a machine is unlikely to go unnoticed and become worse. When deemed necessary, repairs in the early stages of equipment deterioration do not consume the hours normally associated with unplanned and planned maintenance.
3. You can spend less on repairs and replacement parts
Data-driven and analytical, predictive maintenance allows you to identify the root cause of a problem rather than just treating its symptoms. Knowing what can cause equipment failure is helpful in avoiding wear and tear that causes equipment failures. For example, sub-optimal humidity alerts help reduce the electrostatic discharge that occurs in a low-humidity environment. Component deterioration can be avoided, and equipment repair costs and spare parts inventory can be optimized to desired levels.
4. You can protect workers
Using sensors to detect equipment problems bodes well for workplace safety. For example, checking for bearing failures, a common cause of downtime, may require workers to access hard-to-reach 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 requiring direct human intervention.
When to use IoT
- Reduce unplanned downtime
- Reduce machine repair costs
- Increase occupational safety
- Decrease the time to repair machines
- Enable better equipment utilization
- Increase equipment ROI
It is useful for critical assets that have the greatest impact on production rate and profitability. IoT monitoring is valuable even when the smallest 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 in rotating machinery.
Data from IoT devices can be integrated into workforce solutions to develop work schedules that can reduce workers’ exposure to hazardous conditions. As a passive security solution, IoT can help boost worker trust and morale.
See also: The “Internet of Things” is changing the way we look at the global product value chain
