Manufacturers tend to utilize IIoT and Predictive Maintenance to create a smart manufacturing approach. Although the software is known for its cost-effective maintenance procedure, it can also reduce stress for machine operators and maintenance managers with its effective Maintenance and Repair Operations (MROs).
Predictive Maintenance seamlessly assists in tracking the manufacturing equipment’s health, performance, and status in real-time. It plans the maintenance of the manufacturing instruments around the production schedule to reduce the cost and unexpected breakdowns.
The efficient nature of Predictive maintenance can be understood with research conducted by the US Department of Energy Research. The research stated Predictive Maintenance can reduce the maintenance cost by 25 to 30%, decline the downtime by 35 to 45%, and lower the breakdowns by 70 to 75%.
Predictive Maintenance in Action
Predictive Maintenance uses condition monitoring equipment to evaluate manufacturing assets’ performance. IIoT sensor, which is a condition monitoring equipment, can constantly record a wide range of data including temperature, vibrations, and conductivity. IoT or the Internet of Things plays a key role here by translating and analyzing the recorded data for estimating the time of executing the maintenance work to prevent earlier breakdowns. The AI/ML model which is capable of analyzing the sensor-collected data can predict the operating duration of equipment.
According to IIoT experts, it not only detects machine downtime very accurately but also prevents it with support from IIoT sensors and IoT.
3 prime features of Predictive Maintenance Software
The modus operandi of the software is based on 3 prime features and these are:
- Work Order
- Assets Monitoring
While data is immensely useful for the growth of a business; it is Report that helps in analyzing the data. It helps in identifying the issues with improvement possibilities. Reports are considered the prime source to observe all the data.
A work order is created whenever a maintenance task needs to be accomplished. Work order management helps maintenance managers to keep track of the work status so that they can update it to the end-users. Work order management helps in tracking the performance of each manufacturing asset individually.
It is mandatory to keep track of your manufacturing equipment on a 24×7 basis as these assets are expensive. Asset monitoring techniques provide crucial information on these assets, such as how long and how frequently they have been used. This asset monitoring feature comes up with benefits like improving the longevity of manufacturing equipment and much more.
These are the 3 primary features of the software.
Benefits of Utilizing Predictive Maintenance in Industry 4.0
It comes up with various advantages that can benefit the manufacturing industries.
The following points are described below:
- Improvement in safety
A sudden machine breakdown can cause concern for the workers. Predictive Maintenance ensures the workers will be nowhere when the manufacturing equipment is about to break down and technicians can complete the service before a machine starts malfunctioning.
- Improvement in productivity
The system ensures fewer emergency issues are happening so that engineers and maintenance managers can concentrate more time on productivity while focusing on their regular work.
- Improvement in ROI
It reduces manufacturing setbacks like equipment failure and downtime chances. The software helps in improving the asset uptime and performance; so the ROI (Return on Investment) can take an upsurge.
- Improvement in machine uptime
According to PTC, it can reduce machine downtime by 30%. It can identify any kind of problem like equipment failure in advance and resolve the problem before it actually happens.
- Improvement in customer satisfaction
Predictive analytics tools work with sophisticated algorithms for analyzing large volumes of historic data and they can identify problems that are not manually detectable. It helps your business to beat the competitors and improve the satisfaction level of your customers.
These five points are considered Predictive Maintenance benefits in Industry 4.0 and IIoT which are capable of reducing machine downtime.
Traditional versus Predictive Maintenance: The Differences
The Table Chart consisting of 7 points can help you to understand the differences between Traditional and Predictive maintenance and why it performs better than the traditional way.
|Attributes||Traditional Maintenance||Predictive Maintenance|
|Performance||Reacts only when malfunctions or breakdowns occur||Continuous checking of equipment and environmental factors|
|Equipment Feature||It suits only simple and standalone equipment||Works fine for complex production lines|
|Cost||This leads to high maintenance and material costs||AI (Artificial Intelligence) helps in the cost-effective maintenance procedure|
|Workload||Does not help in reducing the workload of field engineers||Supports the field engineers by reducing their workload|
|Optimization||Does not help in optimizing the performance of machines||Optimizes the performance of manufacturing equipment|
|Lifespan||Does not contribute too much to improving the lifespan of equipment||Helps in enhancing equipment’s lifespan|
|Previous Data||Cannot take any support from the previous data repository||Take cues from previous data to prevent and detect any kind of equipment malfunctioning|
The Predictive maintenance feature of IIoT (Industrial Internet of Things) has a good number of advantages ranging from reduced downtime, and fewer productivity lags, to cost-saving. This is the reason when an organization is utilizing a good number of manufacturing equipment; it is good to invest in IIoT for the purpose of Predictive Maintenance. When your end goal is to minimize maintenance expenses and increase Return on Investment (ROI); investing in IIoT solutions that include Predictive Maintenance is a good option.
Being a trusted Industry 4.0 and IIoT service provider, Youngsoft can help you with improving operations, increasing revenue, and enhancing manufacturing business models. With our Predictive Maintenance feature in IIoT, you will be able to gather and analyze data across machines and help them to be more efficient, faster, and flexible.
Founded in 1996, in Michigan, Youngsoft Inc. is an information technology company specializing in IT consulting, and staffing. For almost 3 decades, the company has delivered cutting-edge tech solutions like AEM, Liferay, Business Intelligence, and more to a global clientele. With a futuristic vision, Youngsoft has spearheaded innovations in Healthcare IT solutions and implemented Industry 4.0 in a Box program, a flagship IIoT initiative in partnership with AWS (Amazon Web Services).
Let’s discuss IIoT & Predictive Maintenance in more detail!