Keeping your industrial parts up and running is critical, especially if they have become obsolete. That’s where predictive maintenance helps you! It analyzes your current equipment for potential pitfalls and ensures you avoid breakdowns, wasted time, and frustrated customers. If you want more details on predictive maintenance and how it’s used to monitor the health of obsolete parts for their timely sourcing, keep reading!
What is Predictive Maintenance?
Predictive maintenance is a strategy that utilizes condition monitoring tools and data analysis to predict the future potential state of equipment. Unlike reactive maintenance, which occurs after equipment fails, this approach identifies, detects, and addresses issues before they become a problem. Here are some of its main pillars:
- Vibration Analysis
- Oil Analysis
- Ultrasonic Inspection
- Motor Circuit Analysis
It first appeared in the mid-20th century, when maintenance relied solely on human observation and basic tools for issue detection. However, today it’s a mix of IoT and big data analytics, helping businesses in quick decision-making regarding their obsolete parts. Its market size is also rapidly growing and is going to hit a massive USD 70.73 billion by 2032.
Ways to Use Predictive Maintenance to Monitor Obsolete Parts
Do you know that predictive maintenance can extend the lifetime of an ageing asset by 20% and decrease costs by 12%? On top of this, it improves the availability of different parts by 9%. Therefore, you must implement the following predictive maintenance technologies to track your obsolete parts:
Cloud Computing
Cloud computing is a way to access computer resources, such as hard drives, GPUs, and CPUs, without actually having to manage them. It’s an easy and proven method for manufacturers to store their critical data.
As the data is available online, manufacturers and engineers can access it at any time from any location to detect possible issues in obsolete parts. For instance, you might see that a machine component is running at a higher temperature than usual. You can analyze these patterns to understand whether it’ll fail and arrange the sourcing of obsolete parts in a timely manner to avoid downtime.
Other than this, it also informs you about overall energy consumption and maintenance requirements. All the data stored in the cloud system is secure, thanks to data encryption and firewalls that provide the much-needed peace of mind.
Internet of Things Sensors
At its core, the Internet of Things is a network of physical objects integrated with sensors and software. They connect to the internet to collect and exchange important equipment data. In an industrial setting, IoT sensors are helpful for collecting real-time data on various parameters of an obsolete part, including temperature, vibration, and pressure.
Any deviation from these will send an alert to your systems, allowing you to address maintenance and sourcing of obsolete parts promptly.
Let’s say you’ve an old motor with a bearing that’s no longer produced by the manufacturer. The IoT sensors notice an unusual shaking in the bearing, immediately sending you alerts. You can then immediately search for suppliers that might have the bearing in stock rather than waiting for a breakdown to happen.
Machine Learning Algorithms
Machine learning algorithms are specifically trained to discover patterns and relationships in data. They process the available industrial data to understand and identify the behaviours associated with equipment failure. Suppose you’ve a hydraulic pump with an obsolete seal.
ML algorithms will analyze years of data available in your systems to learn the exact conditions, such as fluid temperature and flow rates, that will cause the seal to leak. Over time, it’ll start predicting with high accuracy when a seal is likely to fail, allowing you to source them from suppliers in a timely manner and negotiate a favorable price.
Digital Dwin Technology
Digital twin, as you can understand from the name, is a digital replica of a physical object, reflecting its properties accurately. Typically, it’s characterized by:
- The level of modeling and data employed
- Physical scope of the twin
- Stages at which the digital twin is used
It gives you insights into the current state of an obsolete industrial part through simulations and modeling techniques. Let’s say you build turbines that use a type of blade that’s no longer manufactured. You can create a digital twin of the turbine to know the stress levels, airflow, and temperature on the blade. The model tells you how many hours the blade takes to deform, so you can arrange a backup without any efficiency loss.
How to Get Obsolete Parts?
After performing predictive maintenance, if any of the obsolete industrial parts fail, you should consider the following tips to source them in a timely manner:
- Contact the Manufacturer: Your first step must be to contact the original manufacturer, as they may have remaining stock of that part and offer last-time-buy options.
- Work with Reliable Suppliers: Get in touch with suppliers around the globe, as they have extensive networks and can locate hard-to-find or obsolete parts that are no longer available.
- Online Marketplaces: Visit online marketplaces like eBay, where other businesses or people might be selling the desired component to get rid of excess inventory.
- Network Within Industry: Attend industry-relevant conferences and seminars where you can connect with industry experts who provide you with insights into how to maintain obsolete parts for longevity or even access to the parts you need.
Always keep an eye on manufacturer’s announcements and start predictive maintenance of components as soon as they become obsolete, and even before, to eliminate downtime.
FAQs
How does predictive maintenance lower business costs?
Predictive maintenance lowers business costs by reducing emergency breakdowns and avoiding last-minute parts sourcing, ensuring you get the best budget deal.
Can predictive maintenance enhance the lifespan of obsolete parts?
Yes, by identifying small issues before they become big problems, predictive maintenance can enhance the efficiency and overall lifespan of obsolete parts.
Is predictive maintenance setup expensive?
Well, predictive maintenance comes with a high upfront cost. However, in the long run, it can save you money by reducing downtime and emergency repairs.
Conclusion
Predictive maintenance for obsolete parts is a necessary thing for businesses. However, if you are looking for a reliable supplier to get hard-to-find industrial parts in top-notch condition, contact Enicstra. We leverage our network of manufacturers to get the best components and also offer a warranty that guarantees our reliability.