Comparison of the performance of machine learning models in predicting equipment failures and maintenance needs in...

 

Transcribed Image Text:

Comparison of the performance of machine learning models in predicting equipment failures and maintenance needs in an industrial environment Results found : Measures of the effectiveness of machine learning models Model Precision Random forest 0,87 SVM 0,85 Gradient boosting 0,89 MLP 0,86 Accuracy 0,86 0,83 0,88 0,84 Recall 0,85 0,82 0,87 0,83 Based on this finding results. do a root cause analysis of the problem displaying everything on a fish bone diagram and come up with any industrial engineering solution. use industrial engineering tools s pareto chart, flow chart to display the results. or also on come with countermeasure and recommendations. Comparison of the performance of machine learning models in predicting equipment failures and maintenance needs in an industrial environment Results found : Measures of the effectiveness of machine learning models Model Precision Random forest 0,87 SVM 0,85 Gradient boosting 0,89 MLP 0,86 Accuracy 0,86 0,83 0,88 0,84 Recall 0,85 0,82 0,87 0,83 Based on this finding results. do a root cause analysis of the problem displaying everything on a fish bone diagram and come up with any industrial engineering solution. use industrial engineering tools s pareto chart, flow chart to display the results. or also on come with countermeasure and recommendations.

Answer rating: 100% (QA)

To conduct a root cause analysis of the problem and come up with industrial engineering solutions we can use various tools such as the fishbone diagra... View the full answer