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Minimize equipment downtime across your production floor 

In the manufacturing sector, equipment downtime is one of the largest sources of lost production time, which in turn causes operational delays and loss of revenue.  Downtime is any period of time when a machine is not in production. Unplanned equipment downtime at any point in the production line can result in lost productivity and money. When a machine breaks down, it significantly impacts production. This will lead to delayed orders, increased costs of repair, loss of customer trust, damaged reputation, and increased labor costs.

Can manufacturers predict machine failures and prevent unplanned equipment downtime?

The answer is “Yes”. With the advent of IoT applications, manufacturers now have the resources to apply predictive maintenance on their machines, which is an antidote for unplanned downtime delays. Corrective maintenance can be extremely time-cost consuming as failure is unpredictable while planned periodic maintenance can result in over-maintenance of assets, wasting time, money, and resources. The performance of any asset is influenced by internal factors such as usage of the asset and external factors such as environment. Organizations that track, monitor and analyze asset health data, will be able to better predict when maintenance is required and plan it effectively.

Industry 4.0 innovations to tackle unplanned downtime

In a smart factory much of the assets are interconnected, thanks to IoT sensors and IoT devices.  These connected industrial assets will be able to tell you that a failure is about to occur, before the event. Smart IoT sensors are used throughout the chain to provide this information. For e.g., sensors installed in heavy machinery can notice values of temperature crossing the threshold values, implying that the part may fail soon. Once the data is collected through sensors, intelligent IoT solutions can perform predictive analytics to proactively figure out the outcomes. With visibility and real time analytics, manufacturers can know when an asset is going to fail and how it is going to fail and can take preventive measures to avoid downtime.

How can IoT technology reduce equipment downtime?

IoT technology aims to reduce equipment downtime on the production floor in the following ways:

Proactive maintenance

Manufacturers can now monitor the status of all machines in every one of their factories. They can now prevent any potential issues before they get problematic enough to cause downtime.

In-depth assessment

Not just the machines as a whole, monitoring of critical parts of an equipment can also be done. Analytics can predict when certain parts will fail and replace them before they ever occur.

Parameter-based real-time maintenance

Monitor machine condition such as status, loads, temperature, vibration, pressure, speed, feeds and other vital parameters in real-time to determine if thresholds are exceeded.  When they breach the agreed thresholds IoT capabilities will trigger actions to ensure effective maintenance and maximize their uptime.

Analytics for preventive actions and planning

It also tracks precisely when, where, and how a downtime happens. To prevent and troubleshoot downtime problems, this kind of speed and accuracy are crucial. Analyzing and diagnosing alerts so maintenance scheduling can be optimized.

Understanding and optimizing equipment utilization rates can help improve the process. Similarly, understanding the common problems or machines that need frequent attention by evaluating alarm frequency can alert equipment that can possibly cause issues.

Conquering equipment downtime complications with IoT solutions

Zero downtime might still be far from becoming a norm. But IoT driven applications have taken manufacturing verticals closer to eliminating unplanned downtime. The most significant advantage of proactive maintenance is speed. It allows manufacturers to fix downtime issues before they happen, instead of weeks later. IoT enabled asset management and predictive maintenance strategies can help in significant reductions in unplanned downtime, advancing the company’s manufacturing capabilities and efficiencies.

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