Operational excellence cannot be achieved overnight. Between the plant that discovers TRS and the one that optimizes it in real time, there are several stages of maturity. Understanding where you stand enables you to set the right priorities and avoid jumping the gun. In this article, we present the five levels of the OEE maturity model and the criteria for assessing your position. Discover the concrete actions you need to take to progress to the next level and sustainably transform your industrial performance. Definition of the OEE Maturity Model A Diagnostic for Performance Many plants measure their OEE without knowing where they stand in relation to best practice. An OEE of 65% may represent excellent performance for a start-up site, or a mediocre result for a mature plant. Without a maturity benchmark, it’s impossible to contextualize your results and set realistic targets on the road to operational excellence. The OEE maturity model offers just that. It distinguishes between measurement, analysis and improvement practices according to their sophistication. Each level corresponds to observable characteristics: tools used, frequency of monitoring, team involvement, integration into processes. This objective diagnosis guides your roadmap. Avoiding implementation errors Wanting to do everything at once often leads to failure. A company that installs IoT sensors before mastering the basics of manual data collection risks drowning in unusable data. Conversely, stagnating on Excel when the organization is ready for real time unnecessarily slows progress towards operational excellence. The maturity model identifies the prerequisites for each stage. It avoids investing in sophisticated tools without the accompanying culture. Each level consolidates the achievements of the previous one before adding new practices. This methodical progression maximizes the return on your investment. Level 1: Organization without Formal Measurement Characteristics and Management at Initial Level At Level 1, the OEE does not formally exist. Production is driven by volume: how many parts are going out today? Stoppages are observed but not measured. The causes remain vague, attributed to chance or bad luck. No one really knows how long the machines are actually running. Management remains intuitive. Decisions are based on intuition and experience. When a problem arises, we react. Between crises, we produce without question. This lack of measurement prevents any structured improvement. The same problems recur without anyone being surprised. Alert signals in the company Your company is at level 1 if: a
Multi Plant OEE: How to standardize performance across your manufacturing sites
How to harmonize OEE measurement across multiple sites to enable reliable comparisons, share best practices and drive continuous improvement across the group. Multi-plant OEE has become a major strategic issue for manufacturers operating in several locations. The question systematically comes up at management committee meetings: “[…]
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