Key production indicators: OEE, lead time, quality indicators (PPM)

Accurately measuring process efficiency is key to making informed decisions and achieving continuous improvement in production. What should you pay attention to? Key metrics include OEE (Overall Equipment Effectiveness), lead time, and quality indicators. These metrics help technicians and managers understand what’s working well and what needs improvement. A CMMS system —though not directly used to calculate all of these metrics—can provide significant support in this area. What’s worth knowing?

What is OEE and why is it worth measuring?

OEE stands for “Overall Equipment Effectiveness.” In Polish, it roughly translates to “overall equipment efficiency.” In practice, it’s a metric that combines three key aspects:

• availability of machines,
• production efficiency,
• quality of products.

Simply put, OEE measures how efficiently a machine park is utilized. A figure close to 100% means that equipment is operating continuously, at full speed, and without product defects. In reality, this level is, of course, extremely difficult to achieve – results around 85% are considered very satisfactory. However, the real problems begin when OEE values are low . This can signal a range of issues, from frequent breakdowns, to inefficient processes, to high levels of production waste. Monitoring OEE therefore allows you to identify bottlenecks and areas that merit optimization.

Components of OEE: Availability, Performance, Quality

Each component of the OEE metric is important for assessing production efficiency. Availability is the percentage of time a machine is ready for operation compared to the total planned production time. Efficiency, on the other hand, measures whether production is proceeding at the planned speed. Efficiency measurement takes into account short downtimes or slowdowns. The final element is quality. It is measured as the percentage of good units compared to the total number of products produced. Importantly, each of these metrics can be broken down into even more detailed metrics – for example, MTTR (Mean Time to Repair) or MTBF (Mean Time Before Failure) – to assess availability. This makes OEE a useful, multi-dimensional tool. With access to reliable data, measuring OEE can lead to reliable and specific recommendations for maintenance activities.

Lead time, i.e. the time from order to delivery

Another important production metric is lead time. This measure reflects the duration of the entire production process. What does the entire process mean? It begins with the acceptance of an order. The end is the delivery of the finished product to the customer. Lead time therefore includes, among other things, the waiting time for materials, the time it takes to complete tasks on machines, and even the waiting time between operations.

Why is this important? Long lead times can mean downtime. This, in turn, can result from insufficient coordination, excessive material inventories, or process imperfections. Reducing lead times is therefore a priority for many companies. Reducing this time translates into increased production flexibility, higher levels of customer service, and better utilization of company resources.

Quality Indicators – PPM and more

PPM (Parts Per Million) is a measure of the number of defective parts per million produced. It provides a quick way to assess the quality of production. However, it’s worth considering the broader picture. Every defect has a cause. Therefore, it’s a good idea to analyze rejects and categorize them by defect type and source.

PPM isn’t the only quality metric in manufacturing. DPMO can also be useful. This acronym stands for “Defects Per Million Opportunities.” Measuring DPMO allows you to account for the number of potential failure points in a given process. Importantly, these don’t always translate into actual defects. Nevertheless, controlling the potential for errors is crucial to maintaining quality. A joint analysis of PPM and DPMO yields very beneficial results – this approach paves the way for effective preventative measures, reduced production losses, and improved customer satisfaction.

CMMS and data for KPI analysis

How does a CMMS help measure production metrics? The system itself doesn’t directly calculate OEE or lead time. However, it still provides crucial support in this area. In this context, a CMMS primarily provides a collection of reliable information about machine operation and maintenance activities. The system can record failures, service duration, the number of replaced parts, and inspection schedules. In this way, a CMMS creates a comprehensive maintenance knowledge base. This is where technicians and managers can obtain data for further analysis.

Using a CMMS offers real opportunities for controlling production metrics. For example, breakdown times can be easily compared with production times. CMMS data can also be used as a basis for measuring detailed metrics such as MTTR or equipment downtime. CMMS also offers the ability to connect with other systems. Integration with ERP software or an MES module provides a comprehensive picture of operational efficiency at any point in the plant’s operation.

How to use CMMS data when calculating OEE?

What is needed to calculate OEE? The first step is availability. The basis here is planned operating time and the time during which the machine was unavailable. Unavailability time includes both emergency and planned causes. This data is recorded in the CMMS. Efficiency, on the other hand, requires comparing the number of units produced with the assumed theoretical capacity. Here, it’s worth referring to production records in the MES system and machine documentation in the CMMS. All that remains is quality analysis. In this area, it’s best to combine CMMS data on the number of interventions with the number of damaged products. This will allow us to understand whether equipment failures are affecting product quality.

Presentation of indicators – preparation of reports, data visualization

Determining indicator values isn’t the end of the story. Interpreting them is also crucial. Visualization is the starting point for this. Key production indicators can be presented in reports or dashboards. A CMMS provides significant support in this area – visualizations of MTTR, MTBF, and rejection rate trends make it easier to spot recurring patterns. It’s also worth adding data from ERP and MES to monitor various KPI changes in real time.

This allows the Maintenance team to immediately respond to deterioration in parameters. Managers have access to reliable information and arguments. This makes making investment or change decisions much easier.

Practical benefits of KPI monitoring

Why is it worth monitoring KPIs with a CMMS? Regular analysis of metrics like OEE and lead time offers numerous benefits. Higher machine availability, reduced inventory utilization, and better utilization of human resources are just some of the benefits. Tracking quality indicators also helps identify defects at their source, allowing for timely adjustments to the production process or material procurement. CMMS data also allows for the planning of preventive maintenance at optimal times, avoiding unplanned downtime. This offers numerous benefits for the organization. This allows the plant to achieve higher levels of on-time order fulfillment and improved product quality – all at lower costs.

KPIs like OEE, lead time, and PPM are the foundation of production management. While CMMS doesn’t directly measure them, it provides solid data as a starting point for analysis. Integration with other systems also allows you to quickly respond to problems, optimize processes, and continuously improve your company’s operational efficiency. If you want to strengthen your KPI strategy and transform CMMS data into tangible benefits, contact QRmaint experts – we offer support in software development, implementation, and utilization of the information collected by our system.