predictive maintenance

ThiruThiru Member Posts: 33 Contributor II
hi all,


1) referring the process for "predictive maintenance" in rapidminer & the video in https://rapidminer.com/resource/data-science-predictive-maintenance/
https://docs.rapidminer.com/9.4/server/use/web-services/predictive-maintenance.html

 in the given data set,   the machine is characterised by the label : failure - yes/no.
Does it mean the machines of respective id is under failure - yes or no  condition,  for the given sensor data?  how does that label value is decided?

2.  In my case,   If I can build a machine learning classification model for a 'single' machine with columns  as sensor data ( eg. no of columns =5 , means no. of sensor = 5) with many rows of data.  This classification model can classify the fault as Yes or No.  
can I extend this 'classification'  model into ' prediction' of failure?  
thanks

regds
thiru





Jasmine_

Best Answer

Answers

  • hbajpaihbajpai Member Posts: 9 Contributor II
    Hi @Thiru,

    1. I believe the data is mocked up and the file I have on my end consists of 136 sample examples wherein the column "Failure" indicates whether the machine has failed or not. The data has 25 sensor values that act as attributes that help us to understand whether the machine will fail or not. In this use case, a classification model was used to learn and predict for a new set of 25 sensor values whether the machine will fail or not.

    2. Can you elaborate more on the second question? I am not sure about the data description to answer whether machine ID is should be used as an attribute or we can generalize the trend to develop a model that can be used for rescoring on all machines. Maybe @JeffChowaniec can elaborate more on this. 
    sgenzerJasmine_Thiru
  • ThiruThiru Member Posts: 33 Contributor II
    edited February 27
    hi @hbajpai ,

    thanks for your reply.  

    a.  My 2nd question is about:

    I build a "classification" model for a machine to "classify"  whether it is failure - Yes or No,  eg. Lets say using KNN. 
     This was done using inputs of 5 sensors.  these 5 sensors were columns while building the classification model. Im able to  classify the failure (it is just classification based on given data , not prediction) with these 5 columns. My question is:     is there any way to convert an  already  build  classification model into a model suitable for predictive maintenance?

    b.  Referring your answer for my 1st qn: 
       as per the example set,  25 sensor values act as attributes and labelled column says whether the machine has failed or not.  My understanding is : it is only the  normal data set typically used for any classification problem.  Looks like the operator - " determine influence factors"  & " optimize parameters (grid)" contributes in using the sample set for predictive maintenance.  ( correct me If Im wrong).


    thanks & regards
    thiru





    Jasmine_
  • ThiruThiru Member Posts: 33 Contributor II
    hi @hbajpai ,

    thanks for your reply.  

    a.  My 2nd question is about:

    I build a "classification" model for a machine to "classify"  whether it is failure - Yes or No,  eg. Lets say using KNN. 
     This was done using inputs of 5 sensors.  these 5 sensors were columns while building the classification model. Im able to  classify the failure (it is just classification based on given data , not prediction) with these 5 columns. My question is:     is there any way to convert an  already build  classification model into a model suitable  for predictive maintenance?

    b.  Referring your answer for my 1st qn: 
       as per the example set,  25 sensor values act as attributes and labelled column says whether the machine has failed or not.  My understanding is : it is only the  normal data set typically used for any classification problem.  Looks like the operator - " determine influence factors"  & " optimize parameters (grid)" contributes in using the sample set for predictive maintenance.  ( correct me If Im wrong).


    thanks & regards
    thiru
    hbajpaiJasmine_
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