Gain insight into the impact of planned and unplanned downtimes to create reliable capacity forecasts, design robust processes, and build effective maintenance schedules. In the processing industry, downtimes in production, whether planned or unplanned, can be extremely costly. Thus, having an effective failure and maintenance strategy is vital, but how can you develop an efficient plan surrounding a rather unpredictable process?
The best way to avoid unplanned downtime like equipment failures is to effectively manage your planned downtime (i.e., maintenance). Input historical data into your model to accurately build a predictive maintenance schedule based on factors such as equipment age or ideal time slots found in production using INOSIM Gantt. Furthermore, quickly test the resiliency of your plan by running several virtual experiments and adjusting maintenance parameters such as duration, frequency, etc.
In addition to modeling planned downtimes like maintenance, INOSIM also supports a variety of stochastic functions to model failure frequencies and durations, enabling you to thoroughly evaluate the impact of unplanned downtimes on your production goals and answer important questions such as:
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