context

As an organization you naturally want to get the most out of your assets. Asset utilization is the indicator with which it is possible to gain insight into how your organization is performing, also compared to the competition. This is quantified as the ratio between the realized output and the maximum theoretical output, i.e. normal working time. There can be innumerable reasons for not meeting normal working hours. These can almost all be included in the Overall Equipment Effectiveness (OEE). The OEE consists of three categories, which in turn are subdivided into the six KPIs that determine asset utilization. These KPIs are also known as the 'Six Big Losses':

availabilty

1. Asset failures (unplanned)
2. Changeover times, adjustments and maintenance (planned)

Performance

3. Waiting and small interruptions
4. Low production rate

Quality

5. Starting up the asset
6. Defects and Rework

If an asset is in a poor state of maintenance, this is more likely to lead to production defects, loss of speed or even asset failures. This has a negative impact on the OEE, and thus the asset utilization. Assets in use do not escape wear and tear and their condition deteriorates over time. We call this asset degradation. But how can you manage this in such a way that the costs of your maintenance remain acceptable? Below is a description of how the degradation can be mapped by means of a simulation and the optimal maintenance strategy can subsequently be determined. A fictitious case shows the effects of a number of asset characteristics.

Simulation

Although a simulation is a simplified representation of reality, it can still provide good advice for the maintenance strategy. The goal is to find out at what level of asset degradation ideally preventive maintenance should be planned, i.e. the optimal limit value M. Historical asset data is extrapolated over a significantly larger time horizon, making analysis of the data more reliable. Before the simulation can be performed, there are a number of preconditions that must be met.

Conditions

In order to determine an optimal maintenance strategy, it is necessary that at least the following data is available over a representative period of at least three months. More available data leads to a more accurate simulation and fewer assumptions. In any case, it concerns:

1. Condition of the asset;
2. Timestamps of the times when both corrective and preventive maintenance took place;
3. Cost of maintenance, both corrective and preventive.

The simulation will be completed in a number of steps.

Characteristics

Based on historical data, common asset characteristics can be identified such as: asset failures, the effect of preventive maintenance, variation in degradation levels and the ratio between the costs of corrective and preventive maintenance. All these characteristics have an impact on the optimal limit value M and the average costs per hour for the life of the asset. In reality, many more characteristics can be of influence, the chosen variables are therefore illustrative. The characteristics are discussed below.

1. Asset failures

From the historical data, it is possible to find out what the asset's degradation is and how it has changed over time. It also charts how often the asset suffered a failure (failure level), what the time interval is and how stable this level is. Disruptions can occur around the same degradation level (stable) or at random times (unstable). The latter can be seen in figure 2.

2. Effect of preventive maintenance

This analysis also provides insight into the effectiveness of maintenance. Maintenance can be 'perfect', in which the condition of the asset is brought back to new condition, or 'imperfect', in which it is only partially restored. An example of the degradation progression is shown in figure 2. The maintenance is perfect, as the degradation level is always reduced to 0 with each maintenance.

3. Relegation Level Variation

Asset degradation does not always take place evenly, a certain degree of variation always applies. Figure 3 shows that the degradation shoots up in big leaps with some regularity. Think of a train that drives over a stone or a machine with oil leakage, the condition of the asset deteriorates enormously in a short time.

4. Cost ratio between preventive and corrective maintenance

Finally, the realized maintenance costs can be mapped out. We naturally want to see this minimized, while asset utilization does not suffer as a result. To properly make this trade-off, it is important to understand how the two types of maintenance (corrective vs. preventive) are related to the 'Six Big Losses', and thus the OEE. Green means that the type of maintenance makes a positive contribution to the relevant 'Loss', orange has virtually no effect, while red has a negative impact and thus increases the 'Loss'.