Industrial and manufacturing companies must be as efficient and competitive as possible in today's global economy.
The significance of maintenance to a business cannot be underestimated. The use of smart and cost-effective equipment management solutions is crucial because they affect equipment reliability and availability, production throughput, and, ultimately, the company's bottom line. To maximize its effectiveness, predictive maintenance must be carried out carefully.
Understanding Predictive Maintenance
Predictive maintenance (PdM) is a proactive maintenance technique that uses real-time monitoring of an asset's condition and performance to predict when maintenance is necessary to prevent unexpected breakdowns. It examines data from several sources, including sensors, the Internet of Things (IoT), machine learning, data analytics, and modeling, to identify potential failure indicators.
Instead of taking wild guesses about when to perform maintenance, you can do it precisely when the equipment or machinery needs it. With regular and proper use, predictive maintenance can reduce the need for expensive repairs and equipment downtime, saving businesses thousands of dollars over time.
Predictive Maintenance: Guide For Implementation
Making sure you successfully implement an effective maintenance management plan involves several steps, from selecting priority assets to integrating your IoT devices with a range of software systems, such as the computerized maintenance management system (CMMS).
The implementation process can begin once you have acquired buy-in from all relevant parties, calculated your budget, defined your Key Performance Indicators (KPIs), and selected the appropriate software deployment model (cloud-based, mobile, or on-premise).
Here are the steps in implementing a successful predictive maintenance program:
Select The Right Assets To Monitor
Some equipment will be simpler to incorporate into a preventative maintenance program than others. Still, it's equally vital to assess how crucial a piece of equipment is to operations and whether or not a predictive approach is warranted in the first place.
Make your selections based on factors such as:
Criticality. The more crucial an asset is to your operation, the greater your efforts should be to prevent failure.
Replacement Cost. Because of the high replacement cost, high-value assets are frequently the focus of PdM programs.
Failure History. Prior record of failure makes an asset a candidate.
Maintenance Cost. If you're currently spending money on maintenance for an asset, switching to PdM can save you money by reducing the need for maintenance checks. If you're already using preventive maintenance, the transition will be a little less challenging.
Ease Of Access. The more difficult an asset is to reach, the more likely it is to be neglected or skipped over during routine maintenance inspections. Since this is the case, you might want to keep an eye on it.
Ultimately, this comes down to calculating how much money can be saved by applying PdM on the asset. You can use this information to decide which ones are worth protecting the most.
Have The Right Resources
The next thing to do is look at what it will take to get a predictive maintenance program up and running. You can break items down into these primary categories:
Labor. Estimate how long your program will take to run. This should cover management, planning, and craft hours by employment sector and skill level. These should include clerical help and material handling.
Materials. Depending on the vital asset you choose, you'll need to identify materials. This covers what to stock, how much, and when to replenish.
Facilities. It's crucial to examine the actual location where all the predictive maintenance activities will take place.
Technology. Today's society has access to numerous tools and technological advancements. Figure out what kind of sensors, infrared cameras, data collectors, and analysis software will be required.
Training. It will be easier for you to implement and manage your program if you invest in your team in the form of training, education, and certification.
All the aforementioned components are necessary for an initiative to be carried out successfully.
Collect, Visualize, And Analyze Data
When an asset for a pilot program has been selected, the next step is to implement the program. Prepare the asset for predictive maintenance by installing any sensors that may be required and making sure that the proper software applications are installed on the asset in order to gather, visualize, and analyze the asset's production data.
Monitoring and collecting asset data for a baseline in a timely manner helps algorithms analyze machine health and predict any irregularities. With adequate data, algorithms may learn machine statistics to anticipate maintenance needs. From there, predictive maintenance can take corrective actions.
Accurate data collection is the backbone of any successful predictive maintenance plan. Therefore, choosing the best platform for doing the analysis is also crucial. Cloud-based data storage and cutting-edge artificial intelligence technologies displaying findings on a streamlined dashboard can help analyze massive volumes of machine-health data, resulting in faster conclusions and a user-friendly solution.
Measure And Document Program Progresses
Program successes need to be consistently documented. Some businesses initially record program wins, but many falter and stop documenting the gains. To document program successes, a uniform template is recommended. This scorecard should record the number and nature of occurrences and annualized cost savings from an effective Condition Monitoring program.
You may have to talk with some of your leadership personnel to determine exactly what monetary savings should be recorded so that you can provide a solid quantification of the benefits obtained. Regularly providing this document to those who can shape your program's future is essential, regardless of the design of the template you use.
Adopt A Continuous Improvement Effort
The ability to adapt to changing circumstances is essential for any program's success. The elements of your maintenance program will inevitably need updating as time goes on. Program leadership, regular inspections, quantitative measures of performance, and data are vital parts of any improvement program.
Take steps to ensure that your Condition Monitoring program is built on a foundation of constant improvement. Keep things interesting by constantly looking for innovative uses for equipment and new methods to make it more reliable.
You can't expect all your problems to disappear after implementing a predictive maintenance plan. However, there are significant advantages to having one, such as a more stable business that promotes growth and productivity for all employees.
Improving fundamental maintenance practices is essential for realizing those benefits. If you have solid foundations, your plan can withstand any difficulties.