Preventive vs Predictive Maintenance
How to move from reactive to proactive maintenance
A plant’s overall success is heavily influenced by the effectiveness of its maintenance organization and how well maintenance activities are incorporated with the facility’s production schedule. With millions of dollars invested in equipment, manufacturers need to prioritize and even emphasize their maintenance strategy.
Today, we’re seeing that more and more facilities moving away from legacy maintenance methods where you only fix what’s broken, when it breaks. This antiquated method leads to lost productivity, disruption in production, and waves of negative effects felt throughout the entire organization. Now more than ever facilities need more control. That’s why so many are moving towards more proactive and even predictive maintenance methods.
When moving from being reactive to proactive, we need to start thinking about the maintenance organization as a profit center. To accomplish this, successful organizations use a Computerized Maintenance Management System (CMMS).
A good CMMS system will modernize and optimize a plant’s maintenance efforts. It will keep track of preventive maintenance (PM) activity, spare parts inventory, maintenance labor and materials cost history, and all aspects of maintenance efficiencies. A comprehensive CMMS will also track asset performance history, equipment failure analysis data, predict remaining asset lifespan, and many other items such as audits, safety, compliance, and more.
A high-quality CMMS will optimize and streamline your operations.
What is predictive maintenance?
Predictive maintenance is maintenance performed only when needed based on analytics on actual asset data. This can include using intelligently normalized maintenance history data to forecast suggested times for pro-active inspection or maintenance. Data Analytics can also be done on real-time conditions being monitored and then trigger pro-active or predictive maintenance once an out-of-spec analytic or condition rule has been met.
The goal of a predictive maintenance strategy is to optimize maintenance resources. Scheduling maintenance work only when needed frees up maintenance teams for more important tasks and strategic work, avoids unnecessary or excessive maintenance, and will certainly reduce maintenance costs, thus creating greater efficiency in the plant and amongst personnel.
To accomplish these approaches, condition-monitoring tools and a CMMS that can incorporate the resultant data sets into decision making are necessary. The result not only optimizes maintenance efficiencies but truly delivers actionable insights that can be consumed by operations personnel, engineering personnel, and executive management as well.
What is preventive maintenance?
In comparison, preventive maintenance is maintenance that is typically scheduled on a recurring basis. Often these recurring schedules are based on calendar periodicity such as weekly, monthly, quarterly, and yearly. At these intervals, the maintenance technician will change parts, make adjustments, and identify any potential signs of malfunction and preemptively remediate before a fault occurs.
Performing these routine maintenance checks aims to avoid machine failure, prevent unplanned downtime, and extend an assets’ lifespan. This proactive approach is more effective than being reactive. A more impactful way of creating recurring maintenance or preventive maintenance schedules is by doing so using actual machine use or machine utilization data. Essentially, performing periodic maintenance based on long a machine has been actually used. Examples of this could be to trigger a PM at every 500 hours of actual use. Or every 2500 cycles of use, or every 1000 products made, etc.
This is a smart, much more impactful way of managing maintenance tasks and routines. Still in today’s Industry4.0 environment, manufacturers that wish to excel must also adopt predictive strategies as well.
How is predictive maintenance different from preventive maintenance?
While both maintenance approaches aim to increase the reliability of assets and reduce the likelihood of machine failure, the main difference between predictive and preventative is that predictive maintenance evaluates an asset’s actual state, and then a decision is made to perform an action. This gives the organization the benefit of a Just-in-time maintenance strategy that ultimately improves overall equipment effectiveness (OEE) levels.
How do you go from reactive maintenance to a proactive maintenance strategy?
To go from a reactive to a proactive maintenance strategy you’ll need to follow these 8 steps:
- Get the right people on board. Keeping stakeholders and anyone that will help to carry out the plan informed is critical to the program’s success.
- Establish goals and KPI’s for the program. Know what you’ll measure, what tools you’ll use, and when to measure.
- Inventory the assets. In Excel, create a list of all the equipment you are responsible for. Record the make and model of the equipment, serial number, asset number, category it belongs to (HVAC, plumbing, etc.), location of the equipment, department it falls under, and any high costs associated with the asset.
- Establish criticality, PSM, or other consequence of failure criteria that rank the impact each asset has on your operations.
- Prioritize assets by maintenance strategy. Choose maintenance strategies that match the criticality, or consequence of failure, of the asset or machine.
- Make projections for long-term and short-term maintenance needs. Document the OEM’s maintenance recommendations to help guide your plan’s timeline, recommendations, and checklists.
- Build the proactive maintenance strategy. Decide what proactive means for your operation or for each class of asset within your operation. Ensure that for each maintenance strategy that you choose to deploy, you have the right data, can get that data at the right time, and how to use that data in order to accurately trigger actions and when.
- Compile and organize all the information gathered thus far. Build out the plan for all maintenance strategies and associated tasks, resource, skills required for each asset.
- Implement the plan. Train the team to follow the plan. Be sure to gather feedback.
- Optimize. Keep goals and KPI’s in sight. Collect data, analyze the data, and adjust as needed.
To take your maintenance strategy to the next level and implement a predictive maintenance program, you’ll need a maintenance management software like LLumin. LLumin’s CMMS+ integrates with any machine’s sensors or control system to accurately track and analyze the state of the asset. Example parameters may include electrical current, vibrations, temperature, pressure, oil, noise, corrosion levels, and many, many other data points based on the role or function of that machine.
Through real-time data capture and predetermined condition-based workflows, the system produces automatic alerts that then generate actions, work orders and requisitions. When an alert is fired, the maintenance team will know it’s time to act and what the exact state or status is about the asset from the CMMS. Thereby optimizing the type of work needed to be done , minimizing any productivity disruptions in the process.
Who should implement a predictive maintenance strategy?
As Industry 4.0 technology continues to advance, organizations that don’t adopt an IIOT based approach to maintenance will be left behind. Over the coming years we expect to see a much greater adoption of the predictive maintenance model across many industrial verticals.
Early adopters that are beginning now are realizing the highest ROI. All organizations will benefit from a smart, proactive and predictive maintenance program. Especially those in competitive environments, those that need to optimize labor, those that need to stay ahead of compliance, and those that run 24×7, or simply cannot tolerate extended downtime.
Caleb Castellaw is an accomplished B2B SaaS professional with experience in Business Development, Direct Sales, Partner Sales, and Customer Success. His expertise spans across asset management, process automation, and ERP sectors. Currently, Caleb oversees partner and customer relations at LLumin, ensuring strategic alignment and satisfaction.