The cost of equipment failure is shocking, so implementing a strong equipment maintenance strategy is critical. At the start, you can simply develop maintenance management schedules for your equipment and then automate them. But you need to do more to ensure long-term successful.
What are some factors you need to consider to increase overall equipment effectiveness (OEE)?
Here are three key elements to focus on.
Developing an equipment maintenance strategy: 3 considerations
1. How do you align maintenance tasks to different types of failures?
Each time you take apart a complex machine and put it back together, you have the potential to introduce new problems. You started with the intention of fixing it, but in the process run the risk of creating more issues.
While a good preventive maintenance program should be the cornerstone of your strategy, you need to find the optimal frequency for each type of equipment.
This is known as reliability centered maintenance, and it requires a deeper understanding of each piece of equipment and its potential failure points. Starting with failure modes and effects analysis (FMEA) is crucial to creating an effective long-term equipment maintenance strategy.
Developed in 1978, the Nowlan and Heap curves show different equipment failure patterns. Some are age-related failures, which don’t require any intervention until they reach a wear-out point. Understanding that a certain piece of equipment falls in the category of age-related failure helps you save unnecessary servicing costs while reducing the risk of introducing new problems.
Other failure patterns occur randomly, making it impossible to determine the mean time between failure (MTBF). In fact, 80% of failures fall into this intermittent category. In this case, a regular maintenance schedule can only minimize the likelihood of failures to some extent. To avoid falling into the trap of reactive maintenance for these issues, it’s more effective to rely on condition-based maintenance.
You can use inspection logs to regularly record details that indicate potential failure, such as vibration, friction, and fluid levels.
Predictive maintenance is a more advanced form of condition-based monitoring. It uses Industrial Internet of Things (IIoT) sensors embedded in equipment to continuously collect data.
Once you map the failure pattern to each piece of equipment and identify the right strategy to address it, you also need to remove any redundancies. For example, you may not need both a preventive and predictive approach for the same machine. Eliminating redundancies will make your equipment maintenance strategy more cost-effective.
2. How do you accurately anticipate failures before they occur?
While the ability to predict failures is certainly appealing, it’s important to remember that its success is closely tied to data availability. Machine learning algorithms that form the basis for predictive maintenance give better results as they learn with more data samples.
Sensors provide this data, but only 34% of manufacturing plants actually used them, according to a 2018 study by Plant Engineering. Most use a combination of manual and visual inspections instead.
To overcome the obstacles associated with predictive maintenance, follow these best practices:
- Consolidate all data from manual, automated, and real-time sources.
- Perform a gap analysis and identify any missing equipment data.
- Conduct simulation testing by creating digital versions of the equipment you need to study and generate failure data.
- Add failure data into your machine learning models.
Taking these steps can make your predictive maintenance strategy more efficient and effective.
3. Who should be involved in your equipment maintenance strategy?
Everyone at your plant ultimately contributes to the success of your equipment maintenance strategy. However, unless you have outlined clear roles and responsibilities, it’s all too easy to start pointing fingers when a machine breaks down.
Here is an example of how you might define roles on your maintenance team:
Machine operators perform routine maintenance tasks and inspection (e.g. cleaning, tightening bolts, and lubricating equipment) to reduce the likelihood of breakdowns.
Floor supervisors review and approve the maintenance log.
Safety supervisors ensure machine operators adhere to the safety checklist and point out non-compliance issues.
Service technicians, who have more training than machine operators, perform preventive maintenance.
Reliability engineers look at equipment maintenance metrics and perform data analysis to fine-tune your equipment maintenance strategy (such as adding or deleting items from the inspection checklist or changing the cadence of maintenance schedules).
Senior manufacturing leaders support these activities by establishing training and standard operating procedures, as well as investing in automated systems that simplify these processes.
While you may not have all these roles within your manufacturing plant, everyone should have a clear understanding of their role in your equipment management strategy.
How enterprise asset management software can help
Enterprise asset management software offers a unified platform for manufacturing leaders to track all information related to their physical assets throughout the equipment lifecycle, from the point of purchase until disposal.
With our equipment management software, you can easily manage preventive maintenance schedules, assign team members, and send automated reminders.
You can also use the inspections module to log operating conditions, such as temperature and friction, and maintain detailed records.
When you need to replace a part, you can use the inventory module to see in real time if you have it in stock, before searching through your warehouse or ordering a new one.
Our powerful, lightning-fast platform also includes a mobile app, which makes it easy for operators, technicians, and others to manage repairs. To see a closer look, schedule a demo today.