Measuring Equipment Performance Using Maintenance KPIs and Metrics

Article Written by:

Meyyappan

Created On:

June 14, 2023

Measuring Equipment Performance Using Maintenance KPIs and Metrics

Table of Contents:

Is it according to the hunch you are making more of machines? In the absence of such hard metrics, maintenance is a costly guesswork, in which every minute of unplanned downtime is silently eating your revenues and profit margins.

There has been a rapid change in the industry of reactive firefighting into data-driven reliability. Team success now does not simply resolve failures but anticipates and avoids them and makes maintenance a strategic asset not a cost center.

Cryotos CMMS is able to help you here and convert your unrefined repair data into an intelligent engine. We assist you in deciphering your operations to spur business in the growth direction so that you no longer pay on matters that can be avoided.

The DNA of Maintenance Performance

The building blocks are the first step to developing a reliability strategy.

KPIs vs. Metrics

Although the two are used interchangeably, there is a difference. Future metrics the measures of processes (e.g. how many hours did this motor run?). KPIs (Key Performance Indicators) are a strategy that informs you whether you are achieving business goals (e.g., "Is our equipment reliability increasing each year-over-year? The data are called metrics; the scorecard is called KPIs.

Purpose-Driven Data

  • Health Check: It checks like a doctor checking vitals, KPIs identifies the actual lifespan of your assets. They give you the clue of whether a machine is growing old or running fast to disaster.
  • Justification: Information is the language of management. I feel like we need it not to work when you require a budget to acquire new parts or even more employees. It will increase the MTTR by 15 percent because of understaffing, as indicated in our data.

Why Most Fail

Despite its goodness, many teams fail. The main areas of pain that can be identified in all organizations are data silos (locked in the spreadsheet or whiteboard), manual data entry, which is not that accurate, and Analysis Paralysis: You have all this data and you do not know what to do with it.

Step-by-Step Implementation Guide

You are not to follow everything at once. Use this guide to develop sustainable data culture.

Step 1: The Audit

Determine your assets of critical importance. You do not have to trace all the light bulbs. Attend 20% of the assets that cause 80% of the trouble (the Pareto Principle). These are machines that when they break down halt the production.

Step 2: Establish Baselines

It is impossible to know how much you improved without knowing where you began. Compare yourself with historical data to determine where you are. You have no historical data, create your day 1 benchmark by taking some historical data now.

Step 3: Define "Success"

Make goals attainable and quantitative. Rather than we want fewer breakdowns, try to achieve Preventive Maintenance Compliance (PMC) to 90% in 6 months.

Step 4: Automate Collection

Pen and paper records contain flaws. Paper to mobile data logging conversion. This will guarantee real-time data capture at the point of origination, which is when a technician closes a work order, making it accurate.

Step 5: The "Monday Morning" Review

The information does not help when nobody peeps at it. Have a schedule to check on your maintenance dashboards every week. An accountability review of the KPIs every Monday morning that takes 15 minutes is a way to keep the team on track.

Common Mistakes

Mistake 1: Tracking Everything

More data isn't always better. The 50 metrics assumed in tracking results in noise. Attention to the "Vital Few"- the 3-5 KPIs that will affect your bottom line (such as MTTR, MTBF, and OEE).

Mistake 2: Ignoring Leading Indicators

Look not only in the rear-view mirror (lagging indicators such as Downtime). Pay attention to such leading indicators as PM Compliance. When you meet your PM targets today, you avoid the downtime tomorrow.

Mistake 3: Weaponizing Data

Technicians should not be punished using KPIs. In case there was a high degree of MTTR, was it because the technician caused it or was it because of unavailability of spare parts? Improve processes using data and not blame.

The Cryotos Advantage: Automating Your Intelligence

Manual spreadsheets can’t keep up with modern maintenance demands. Here is your dedicated solution.

Feature 1: The Cryotos BI Dashboard

You no longer need to make complex spreadsheets that fail every time you add a new row to your spreadsheet. MTTR (Mean Time to Repair), MTBF (Mean Time Between Failures) and OEE (Overall Equipment Effectiveness).

Feature 2: Mobile-First Data Entry

Reduce human error and lag time. The Cryotos Mobile App ensures technicians enter accurate failure codes, spare parts used, and timestamps in seconds, right from the factory floor.

Feature 3: Automated Reports

No more scrambling to compile data for the boss. Get a professional PDF performance report sent to your inbox—and your management inbox—every Monday morning automatically via the Cryotos scheduler.

Feature 4: Smart Inventory Control

Eradicate supply chain bottlenecks. Real-time tracking of spare parts is used in real-time to avoid stockouts and the administrative delays that swell to your MTTR.

Feature 5: IoT & Sensor Integration

Join up your complete ecosystem. Easily connect to sensors or ERP systems to detect live machine data, with your metrics based on real usage and not estimates.

Case Study: How a Food Processing Plant Regained 20% Production Capacity

The Scenario (Before)

One of the medium sized food processing firms had been having continuous and uncontrollable failures on conveyor belts. The management lacked information on the root cause, and this led to excessive expenses in overtime plus failure to deliver within the set deadlines. They were stuck in a rut of reactive maintenance.

The Solution (Implementing CMMS)

The team adopted Cryotos CMMS to digitize their workflow. They started tracking MTBF and instituted mandatory Failure Codes. Technicians began tagging specific issues (e.g., "Motor Overheat" vs. "Belt Snap") via mobile devices immediately after a repair.

The Outcome (After)

The data revealed a shocking trend: 70% of failures were due to a specific lubrication issue—a skipped step in a routine PM task.

  • Result: The PM schedule was altered to contain a certain lubrication checkpoint.
  • Impact: In 3 months, emergency repairs reduced by 40% and the overall uptime improved by 20 which directly improved their production capacity.

Conclusion

You can’t improve what you don’t measure. Moving data-driven maintenance isn't a luxury; it's a requirement for modern success. By tracking the right KPIs, you shift from being a cost center to a competitive advantage.

Ready to stop paying for downtime? Explore how Cryotos can automate your performance tracking to optimize your maintenance strategy and protect your assets.

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