Implementation of Weibull Analysis Method in Designing Predictive Maintenance for Medical Mask Machine

Weibull analysis has three main functions in the predictive maintenance calculation process. These functions have their respective functions and purposes used to make predictions. Reliability, Failure Rate, and Mean Time Between Failures. These functions have a function to determine later a system is used within a period, then work to determine the level of failure of a condition or a component based on three main conditions: Early Life, Useful Life, or Wear out life. The last function has a function to determine the average time a component can run before the damage.In the production process, there is a problem where machine breakdowns occur every day. These machine breakdowns are caused by malfunctions of different moving parts every day with no known cause of damage and a lack of maintenance planning due to random and unpredictable trends in machine breakdowns. Based on this, Weibull Analysis helps make a prediction that is expected to reduce machine downtime due to random failures and reduce the trend of random failures because it can predict the actual condition, rate, and average time a component can run.The results of the analysis in the manual and automated calculation processes vary. The time data between failures show the values of the variables of form and scale are 0.69, 0.65. function reliability is a component that will decrease over time, the failure rate function is a component that is in the early life phase, and a function of the mean time between failure is seven days. The average error of automated and manual calculations is 1.8%.