This module is a part of “Engine Carbon Brushes Replacement” project. The purposes of the module are:
a) to build convenient for further work datasets based on the provided raw data;
b) preliminary separate exploratory data analysis of carbon brushes replacement of Raw Material Mill A engine;
c) care by outliers.

The input of the module is a csv file. The file contains an unordered dataset, with provided information of engine inspections since 2004 for each engine carbon brush. In case carbon brush was replaced due to deterioration - the event is signed by “1”, otherwise by “0”.

The outputs of the module are convenient for further work datasets based on the provided raw data.

Statistic information of maintenance periods and cases of carbon brushes replacement due to deterioration:

## Cement Mill 11 (January 2004 - February 2018)
## Maintaneince days summary:
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    1.00   20.00   24.00   27.19   28.00  525.00
## 
## Maintaneince days Outleirs:
##   lowerFarOut lowerOutliers upperOutliers   upperFarOut 
##            -4             8            40            52
## 
## Replacement periods summary:
##    Min. 1st Qu.  Median    Mean 3rd Qu.    Max. 
##    14.0   391.0   554.0   659.5   804.0  2046.0
## 
## Replacement periods upperOutliers:
## upperOutliers   upperFarOut 
##        1423.5        2043.0

Graphical Presentation of the Data:

Box Plots of the “maintenance periods” and “cases of carbon brushes replacement”

Low “FarOut” Actually, low farOuts points (days of carbon brush replacement) mean that carbon brushes were replaced on the same day or after few days. In both cases, low farOuts might be entered same information twice- and must be removed from dataset.

Low “FarOut” 

## [1] Mill      C         R         brushName brushType phase     fromDate 
## [8] toDate    Days     
## <0 rows> (or 0-length row.names)


First quantile - most frequently replaced carbon brushes.

Here, it is easy to find out places, where carbon brushes were replaced significantly more frequently than a majority of carbon brushes of this engine. Presumably, these carbon brushes were affected by local factors (like a local clamping spring) more than common reasons (for this engine). But here, the situation significantly better than in the other mills- there are no cases of frequently replaced carbon brushes.


Fourth quantile - most rarely replaced carbon brushes.

This chart provides information about “frozen” (rarely replaced) carbon brushes. Probably “frozen” brushes have a relatively weak clamping spring - as result, the carbon brush, apparently, did not do the job at all. -For example carbon brush C2R04 - was not deteriorated for more then five years (The criterion for replacement is the size (deterioration) of the carbon brush).


We should take into account, that there are upper outliers in the maintenance list - the reason for extremely long intervals between maintenance is probably data loss of maintenance cases:

##   dateDiff  fromtDate     toDate
## 1       47 2004-03-18 2004-05-04
## 2       45 2006-01-26 2006-03-12
## 3       42 2006-03-12 2006-04-23
## 4       49 2009-01-29 2009-03-19
## 5       42 2009-09-21 2009-11-02
## 6       49 2011-01-02 2011-02-20
## 7       52 2013-01-13 2013-03-06
## 8      525 2013-12-22 2015-05-31
## 9      154 2016-05-25 2016-10-26

There is a chance that deteriorated carbon brushes had been replaced during those periods, but we have no information - and as result, we see the lifespan of them as outliers:

##   brushName   fromDate     toDate Days
## 1     C1R05 2013-03-06 2017-09-19 1658
## 2     C2R01 2013-03-06 2017-08-29 1637
## 3     C2R02 2008-03-25 2012-04-24 1491
## 4     C2R02 2013-03-06 2017-08-29 1637
## 5     C2R04 2004-11-15 2010-06-23 2046
## 6     C2R06 2013-03-06 2017-09-19 1658
## 7     C3R04 2013-03-06 2017-05-07 1523
## 8     C3R06 2013-03-06 2018-02-04 1796

In order to exclude the uncertainty- whether carbon brushes lifespan outliers are true, or results of information loss- we can test which of these time periods are overlapping (outliers of periods between maintenance and outliers of periods between carbon brushes replacement).

According to the table, lifespan outliers might be a result of the lost information. For example, it looks like carbon brushes C2R04 was not replaced for about five years, but this periods are overlapped with four periods of lost information, during which carbon brushes might have been replaced for several times.

All 8 outliers are better to be removed from the dataset.

Current condition
In the same way possible to analyze current data in order to predict probable problem (“burned” or “frozen” carbon brushes). This chart is based on current data, taken at February 2018.

“Importance” (to put attention) provides visual information about the number of days since last replacement- lower than second quintile, or upper then third quintile. The importance is calculated by the following principles: Maximum value - 10, is equivalent to the maximum distance from the second quantile down (for the low values -“burned” brushes) and from the third quantile up (for the upper values- “frozen” brushes) found in the whole engine history. The minimum value “1” - the number of days since last replacement, lays in the second or third quantiles.

Colors:
green- the number of days since last replacement lays in third or second quintile;

red- “burned” brush - the number of days since last replacement and lifetime of the previous brush in this place lay in the first quintile;

blue- “frozen” brush- the number of days since last replacement lays in the fourth quintile.