As the Original Equipment Manufacturing industry grows at a breakneck pace well into the fourth industrial revolution (Industry 4.0), OEMs are under pressure from management and end-users to minimize costs and improve productivity.
In this scenario, reactive maintenance is out of the question. Even with preventive maintenance, many companies no longer find standard IoT solutions effective to meet their complex and changing needs.
The solution? Enter customized predictive maintenance. In this article, we’ll take you through the key differences between standard and customized predictive maintenance, the key elements of customized predictive maintenance, benefits, and real-world examples.
Ready? Let’s get started.
Customized vs Standard Predictive Maintenance: What’s Right for Me?
First up, how do you decide whether a standard, off-the-shelf IoT platform with predictive maintenance is right for you or whether you need to pitch a customized solution?
Complexity of Machinery
Off-the-shelf predictive maintenance solutions can work well for OEMs requiring a limited number of sensors connected to the network. It can also work for OEMs with a very simple data set that needs to be collected and already has a standardized storage method.
The more complex your machinery, the more likely you’ll need customized predictive maintenance solutions. Standardized IoT solutions with predictive maintenance could work for you if your problems are limited to a small number of sensors and they don’t interfere with the rest of the data.
Operational Variability
However, most OEMs have a larger and more complex data set, even if you’re a smaller player in the market. Depending on your production environment, each OEM has different factors affecting their equipment and longevity.
You’ll also need the domain expertise to clearly define your problems and provide the right inputs for your predictive maintenance solution for it to work well. Off-the-shelf predictive maintenance can rarely keep up with the actual complexities of industrial requirements and use cases.
In these scenarios, customized predictive maintenance solutions work better than a one-size-fits-all solution. Besides, a customized predictive maintenance solution would be a valuable add-on to your equipment for the end-users who won’t have to spend more.
Let’s take a look at the important elements of a customized predictive maintenance solution.
Key Elements of Customized Predictive Maintenance: How it is Done?
There are several layers to a customized predictive maintenance solution.
Layer 1: Data Collection
This is the first layer, where IoT sensors gather vast amounts of data on the state of the equipment. IoT sensors monitor and gather data on factors like vibration, temperature, humidity, and energy consumption to give you a 360-degree view of equipment health.
Layer 2: AI and Machine Learning
Advanced AI and Machine Learning algorithms process and analyze vast amounts of this data to detect patterns and signatures to predict potential failures and issues before they happen. Not just that, with Machine Learning, the algorithms improve their accuracy by continuously iterating the process based on historical data.
Layer 3: Integration with Your Systems
You’ll need rapid and seamless integration of your predictive maintenance solution with your current Enterprise Resource Planning (ERP) and Manufacturing Execution System (MES). Without this step, the whole process falls flat. This crucial step ensures that the right data is available at the right time to generate accurate results.
Benefits of Customized Predictive Maintenance Solutions for OEMs
Investing in a customized predictive maintenance solution saves OEMs an average of 30% of their total maintenance costs and a 19% decrease in downtime, according to Deloitte. That’s just the tip of the iceberg.
Faster and Better Decision-Making
With a wealth of real-time data and cutting-edge AI and ML analytics that are customized to your needs, you’ll get accurate insights into the state of your equipment and trends. This increases the lifespan of your equipment. You’ll also be able to allocate the right resources and take smarter, data-driven decisions for the future.
Stay Competitive in Industry 4.0
With increased operational efficiency, improved end-user trust, and better reliability, you’ll be able to stay ahead of the competition in the rapid changes of industry 4.0. For instance, 100% of European OEMs plan to offer predictive maintenance by the end of 2024. It’s no longer an added benefit, but a basic consumer expectation now.
Increased Uptime and Cost Savings
Predictive maintenance solutions can greatly reduce unplanned downtimes. Repair becomes quicker when issues are nipped in the bud. In fact, OEMs can typically see up to 87% drop in equipment defects with a reliable predictive maintenance solution.
Enhanced Staff Safety
The safety of your staff and technicians is crucial, especially to maintain trust and reliability with your end-users. By identifying equipment failures before they occur, and advanced alerts, it becomes easier to adhere to state and federal safety standards and improve the wellbeing of your talent pool.
Improved End User Satisfaction
You gain better customer and brand loyalty by identifying critical equipment issues in advance and resolving them. It improves customer satisfaction, which leads to better outcomes for all stakeholders.
Start Small, Scale Fast with Bridgera
Finding the right IoT solutions provider for customized predictive maintenance will help you stay competitive well into the future.
Each layer of our predictive maintenance solution is customized for each client. With over a decade of experience in helping OEMs, we can scale your predictive maintenance solution as you scale up.
What’s more, you can begin with a minimal investment Proof of Concept (PoC) in just two weeks or less. Don’t start from scratch — but start small with Bridgera. Contact us today to schedule a free 5-minute consultation with our IoT expert.
About Bridgera: Bridgera effortlessly combines innovation and expertise to deliver cutting-edge solutions using connected intelligence. We engineer experiences that go beyond expectations, equipping our clients with the tools they need to excel in an increasingly interconnected world. Since our establishment in 2015, Bridgera, headquartered in Raleigh, NC, has specialized in crafting and managing tailored SaaS solutions for web, mobile, and IoT applications across North America.
About Author: Krishna Varma is a writer and researcher, who enjoys writing about technology, IoT, and lifestyle. When she isn’t writing and reading, you’ll find her relaxing with a quiet cup of tea over the weekends.