This is a brief introduction to how R can be useful in the manufacturing sector to calculate the frequency of faults and then developing the model so that preventive maintenance can be done

1. Pumps
Aadish Chopra
January 23, 2018
knitr::opts_chunk$set(echo = TRUE,cache = TRUE,autodep = TRUE)
R Markdown
This is an R Markdown document. Markdown is a simple formatting syntax for authoring
HTML, PDF, and MS Word documents. For more details on using R Markdown see
http://rmarkdown.rstudio.com.
Loading the data sets into a statistical programming language. In this case we are using R
programming language.
R version 3.4.1 (2017-06-30) Platform: x86_64-w64-mingw32/x64 (64-bit) Running
under: Windows >= 8 x64 (build 9200)
We are using R Studio as an IDE for R. All the packages attached are listed with the code
setwd("D:/UIC/MyResearch")
library(readxl)
library(magrittr)
library(dplyr)
Attaching f in prefix because loading the name in dataset
path="D:/UIC/MyResearch/Pumps/KIRLOSKER PUMP BREAKDOWN DETAILS (1).xlsx"
for(i in 1:length(excel_sheets(path))){
assign(x =paste0("f",excel_sheets(path)[i]), value =read_excel(path =
path,sheet = excel_sheets(path)[i]))
}
# drop a column
fP301A<-within(fP301A,rm("System status"))
Kirlosker<-rbind(fAGA951,fAGA952A,fAGA955,fCGA201A,fCGA302A,f11P19A,fP301A)
Let's identify the equipments notifn
knitr::kable(table(Kirlosker %>% group_by(`Notifictn type` ) %>%
select(`Notifictn type`,Equipment) ,dnn = c("Notification Type","Freq
equipment")),caption="Matrix for Pumps and Notification")

2. Matrix for Pumps and Notification
11P19A AGA951 AGA952A AGA955 CGA201A P301A UGA302A
M1 12 5 12 11 1 3 0
Z1 0 0 0 0 7 8 8
Z1 category is preventice maintenance. Thus we see that if a pump is maintained
preventively chances are less of suffering a fault.
Extracting data from the second excel sheet
# To automate the extraction of sheets from excel
path="D:/UIC/MyResearch/Pumps/KSB PUMPS BREAKDOWN RECORD (2).xlsx"
for(i in 1:length(excel_sheets(path))){
assign(x =excel_sheets(path)[i], value =read_excel(path = path,sheet =
excel_sheets(path)[i]))
}
# Rbinding difficult due to different names
`11P24A`<-within(`11P24A`,rm("System status"))
P701A<-within(P701A,rm("System status"))
UGA1107A<-within(UGA1107A,rm("System status"))
colnames(P901A)<-names(P701A)
# Now again aggregating all the data from different sheets and putting them
in a KSB dataset
KSB<-rbind(`11P24A`,P701A,P702A,P2001A,P901A,UGA1107A,UGA2201A)
knitr::kable(table(KSB %>% group_by(`Notifictn type` ) %>% select(`Notifictn
type`,Equipment) ,dnn = c("Notification Type","Freq
equipment")),caption="Matrix for Pumps and Notification")
Matrix for Pumps and Notification
21P24A AGA901A P2001A P701A P702A UGA1107A UGA2201A
M1 1 4 4 2 3 0 9
Z1 0 3 0 0 9 8 7
Z3 6 0 0 5 0 0 0

3. Extracting data from the third excel sheet
path="D:/UIC/MyResearch/Pumps/MAINTENANCE HISTORY - compressor and turbile-
K1&TK1.xlsx"
for(i in 1:length(excel_sheets(path))){
assign(x =paste0("c",excel_sheets(path)[i]), value =read_excel(path =
path,sheet = excel_sheets(path)[i]))
}
# All these pumps have extra atrributes which 1st are not common across all
pumps and secondly
# may not be relevant in analyzing the data
# What is important is the notification date because that might help us in
knowing the frequency
# The third data set is of compressor and turbine. We will be stripping of
unwanted columns
# Let's us change the names of columns so they are in a readable format
# X_3 is useful in 11ko1. We ll rename the column to Execution date
c11K01<-rename(c11K01,Execution.date=X__3)
cP607C<-rename(cP607C,Execution.date=X__1)
# In the equipment the equipment column should have a constant name
throughout the dataset
c11K01$Equipment<-rep("11K01",nrow(c11K01))
cK431$Equipment<-rep("K431",nrow(cK431))
Compar<-data.frame(Ko1=colnames(c11K01))
Compar[14,]<-rep(x = NA,1)
Compar1<-data.frame(TKo1=colnames(c11TK01))
Compar1[11:14,]<-rep(x = NA,4)
Compar2<-data.frame(P607C=colnames(cP607C))
Compar3<-data.frame(K431=colnames(cK431))
Compar3[13:14,]<-rep(x = NA,2)
NetNames<-cbind(Compar,Compar1,Compar2,Compar3)

4. knitr::kable(NetNames,caption = "column names")
column names
Ko1 TKo1 P607C K431
Notifictn type Notifictn type Notifictn type Notifictn type
Notification Notification Notification Notification
Notif.date Notif.date Notif.date Notif.date
Order Order Order Order
Equipment Equipment Equipment Equipment
Description Description Description Description
Functional loc. Functional loc. Functional loc. Functional loc.
System status System status System status System status
X__1 User status Execution.date User status
X__2 Main WorkCtr X__2 Execution Date
Execution.date NA User status Job Details
X__4 NA PartnerResp. Main WorkCtr
PartnerResp. NA DescEmpl.Resp. NA
NA NA Main WorkCtr NA
rm(Compar,Compar1,Compar2,Compar3)
# We will delete the unwanted variables from the dataset
# From the netnames we see that first 8 variables are common along the
dataset. We will delete the rest
for(i in 1:length(excel_sheets(path))){
assign(x=paste0("c",excel_sheets(path)[i]),value=get(paste0("c",excel_sheets(
path)[i]))[,1:8])
}
# They have different date formats so we need to convert to a common date
format
#The below code is not working. The dates format are not proper
# ?c11K01$Notif.date<-as.Date(c11K01$Notif.date,format = "%d.%m.%y")
# ?c11TK01$Notif.date<-as.Date(c11TK01$Notif.date,format = "%d.%m.%y")
c11K01$Notif.date<-lubridate::dmy(c11K01$Notif.date)
c11TK01$Notif.date<-lubridate::dmy(c11TK01$Notif.date)
cP607C$Notif.date<-as.Date(cP607C$Notif.date,format = "%d.%m.%y")

5. cK431$Notif.date<-as.Date(cK431$Notif.date,format = "%d.%m.%y")
# Comnbining for analysis
CompTurbine<-
rbind(get(paste0("c",excel_sheets(path)[1])),get(paste0("c",excel_sheets(path
)[2])),get(paste0("c",excel_sheets(path)[3])),get(paste0("c",excel_sheets(pat
h)[4])))
knitr::kable(table(CompTurbine %>% group_by(`Notifictn type` ) %>%
select(`Notifictn type`,Equipment) ,dnn = c("Notification Type","Freq
equipment")),caption="Matrix for Pumps and Notification")
Matrix for Pumps and Notification
11K01 11TK01 K431 P607C
M1 9 50 16 10
Z1 0 0 0 8
Z3 6 30 0 0
CompTurbine %>% group_by(`Notifictn type`,Equipment ) %>% select(`Notifictn
type`,Equipment) %>% tally()
## # A tibble: 7 x 3
## # Groups: Notifictn type [?]
## `Notifictn type` Equipment n
## <chr> <chr> <int>
## 1 M1 11K01 9
## 2 M1 11TK01 50
## 3 M1 K431 16
## 4 M1 P607C 10
## 5 Z1 P607C 8
## 6 Z3 11K01 6
## 7 Z3 11TK01 30
It is assumed that installation date of every pump is to be considered the previous year's
date in April
4 dates were formatted in excel itself before loading. Their format was changed from
%m/%d/%y and %m.%d.y
We will arrange the dates in descending order ( in the order in which they are listed ) and
then group them according to the notification type

6. Kirlosker$Notif.date<-lubridate::dmy(Kirlosker$Notif.date)
KSB$Notif.date<-lubridate::dmy(KSB$Notif.date)
After converting all the dates in a common format, we will
Analyzing the Kirlosker dataset first
We know that start date of any pump is the previous year and april 1 which would be
dates_from_subtd<-Kirlosker %>% group_by(Equipment) %>%
summarise(Date=min(Notif.date))
#For every pump we got the min date and hence subtracting one year from the
date we can get our date for analysis
date_installed<-as.data.frame(paste((lubridate::year(dates_from_subtd$Date)-
1),"04-01",sep="-"))
colnames(date_installed)<-"Date Installed"
dates_from_subtd<-cbind(dates_from_subtd,date_installed)
rm(date_installed)
dates_from_subtd<-dates_from_subtd[,c(1,3)]
Kirlosker<-left_join(Kirlosker,dates_from_subtd)
## Joining, by = "Equipment"
rm(dates_from_subtd)
dates_from_subtd<-Kirlosker %>% select(Equipment,Notif.date,`Date Installed`)
dates_from_subtd$`Date Installed`<-as.Date(dates_from_subtd$`Date Installed`)
dates_from_subtd<-dates_from_subtd %>% mutate(diff_date=(Notif.date - `Date
Installed`))
dates_from_subtd %>% group_by(Equipment) %>% summarise(Date=min(diff_date))
## # A tibble: 7 x 2
## Equipment Date
## <chr> <time>
## 1 11P19A 330 days
## 2 AGA951 322 days
## 3 AGA952A 414 days
## 4 AGA955 365 days
## 5 CGA201A 556 days

7. ## 6 P301A 308 days
## 7 UGA302A 576 days
The above table gives us the the days between which the pump had fault for the first time
Can use %in% operator to selectively filter some of the values
Kirlosker<-Kirlosker %>% select(`Notifictn type`,Equipment,Notif.date,`Date
Installed`)
Kirlosker<-Kirlosker %>% group_by(Equipment,Notif.date) %>%
arrange(Equipment,desc(Notif.date))
Kirlosker<-as.data.frame(Kirlosker)
Kirlosker<-Kirlosker %>% mutate(diff_days=Notif.date -lead(Notif.date))
Kirlosker$diff_days<-as.numeric(Kirlosker$diff_days)
for(i in 1:(nrow(Kirlosker)-1)){
if(Kirlosker$diff_days[i]<0)
{
Kirlosker$diff_days[i]<--1
}
else{
Kirlosker$diff_days[i]<-Kirlosker$diff_days[i]
}
}
We need to manually put the dates which are set to zero because it has to be subtracted
from the data installed
Although we can easily replace it with few rows I want to write code which is generic
For this we have to know how many rows each category has and will then replace them will
the last one because they are the ones which are zero or NA
insertionM<-(Kirlosker %>% group_by(Equipment) %>% tally())
# We get the count of each equipment and we know that last we have to
calculate manually
Kirlosker[is.na(Kirlosker[,5]),5]<--1
# Now wherever there are zeroes we can replace them with the date installed
subtracted from the first fault occurence
Kirlosker$`Date Installed`<-as.Date(Kirlosker$`Date Installed`)
for(i in 1:nrow(Kirlosker)){

8. if(Kirlosker[i,5]==-1){
Kirlosker[i,5]<-Kirlosker[i,3]-Kirlosker[i,4]
}
}
We will be doing the same for KSB and CompTurbine
dates_from_subtd<-KSB%>% group_by(Equipment) %>%
summarise(Date=min(Notif.date))
#For every pump we got the min date and hence subtracting one year from the
date we can get our date for analysis
date_installed<-as.data.frame(paste((lubridate::year(dates_from_subtd$Date)-
1),"04-01",sep="-"))
colnames(date_installed)<-"Date Installed"
dates_from_subtd<-cbind(dates_from_subtd,date_installed)
rm(date_installed)
dates_from_subtd<-dates_from_subtd[,c(1,3)]
KSB<-left_join(KSB,dates_from_subtd)
## Joining, by = "Equipment"
rm(dates_from_subtd)
dates_from_subtd<-KSB %>% select(Equipment,Notif.date,`Date Installed`)
dates_from_subtd$`Date Installed`<-as.Date(dates_from_subtd$`Date Installed`)
dates_from_subtd<-dates_from_subtd %>% mutate(diff_date=(Notif.date - `Date
Installed`))
dates_from_subtd %>% group_by(Equipment) %>% summarise(Date=min(diff_date))
## # A tibble: 7 x 2
## Equipment Date
## <chr> <time>
## 1 21P24A 332 days
## 2 AGA901A 380 days
## 3 P2001A 377 days
## 4 P701A 330 days
## 5 P702A 287 days

9. ## 6 UGA1107A 448 days
## 7 UGA2201A 321 days
The above table gives us the the days between which the pump had fault for the first time
Can use %in% operator to selectively filter some of the values
KSB<-KSB %>% select(`Notifictn type`,Equipment,Notif.date,`Date Installed`)
KSB<-KSB %>% group_by(Equipment,Notif.date) %>%
arrange(Equipment,desc(Notif.date))
KSB<-as.data.frame(KSB)
# to calculate difference between successive defaults
KSB<-KSB %>% mutate(diff_days=Notif.date -lead(Notif.date))
KSB$diff_days<-as.numeric(KSB$diff_days)
# We are running the loop max-1 because there is no lead for the last item
which generates NA's and we know NA's cause lot of troubles in R
for(i in 1:(nrow(KSB)-1)){
if(KSB$diff_days[i] < 0)
{
KSB$diff_days[i]<--1
}
else{
KSB$diff_days[i]<-KSB$diff_days[i]
}
}
We need to manually put the dates which are set to zero because it has to be subtracted
from the data installed
Although we can easily replace it with few rows I want to write code which is generic
For this we have to know how many rows each category has and will then replace them will
the last one because they are the ones which are zero or NA
# setting the last NA to zero
KSB[is.na(KSB[,5]),5]<--1
# Now wherever there are zeroes we can replace them with the date installed
subtracted from the first fault occurence
KSB$`Date Installed`<-as.Date(KSB$`Date Installed`)
for(i in 1:nrow(KSB)){

10. if(KSB[i,5]==-1){
KSB[i,5]<-KSB[i,3]-KSB[i,4]
}
}
NOTE: It might be a wrong practice to carry the dates installed as it is carrying the
same data.
CompTurbine
We see that CompTurbine the dates are not arranged in a strictly decreasing order within a
category.
dates_from_subtd<-CompTurbine%>% group_by(Equipment) %>%
summarise(Date=min(Notif.date))
#For every pump we got the min date and hence subtracting one year from the
date we can get our date for analysis
date_installed<-as.data.frame(paste((lubridate::year(dates_from_subtd$Date)-
1),"04-01",sep="-"))
colnames(date_installed)<-"Date Installed"
dates_from_subtd<-cbind(dates_from_subtd,date_installed)
rm(date_installed)
dates_from_subtd<-dates_from_subtd[,c(1,3)]
CompTurbine<-left_join(CompTurbine,dates_from_subtd)
## Joining, by = "Equipment"
rm(dates_from_subtd)
dates_from_subtd<-CompTurbine %>% select(Equipment,Notif.date,`Date
Installed`)
dates_from_subtd$`Date Installed`<-as.Date(dates_from_subtd$`Date Installed`)
dates_from_subtd<-dates_from_subtd %>% mutate(diff_date=(Notif.date - `Date
Installed`))
dates_from_subtd %>% group_by(Equipment) %>% summarise(Date=min(diff_date))

11. ## # A tibble: 4 x 2
## Equipment Date
## <chr> <time>
## 1 11K01 362 days
## 2 11TK01 294 days
## 3 K431 365 days
## 4 P607C 440 days
The above table gives us the the days between which the pump had fault for the first time
Can use %in% operator to selectively filter some of the values
CompTurbine<-CompTurbine %>% select(`Notifictn
type`,Equipment,Notif.date,`Date Installed`)
CompTurbine<-CompTurbine %>% group_by(Equipment,Notif.date) %>%
arrange(Equipment,desc(Notif.date))
CompTurbine<-as.data.frame(CompTurbine)
# to calculate difference between successive defaults
CompTurbine<-CompTurbine %>% mutate(diff_days=Notif.date -lead(Notif.date))
CompTurbine$diff_days<-as.numeric(CompTurbine$diff_days)
# We are running the loop max-1 because there is no lead for the last item
which generates NA's and we know NA's cause lot of troubles in R
for(i in 1:(nrow(CompTurbine)-1)){
if(CompTurbine$diff_days[i] < 0)
{
CompTurbine$diff_days[i]<--1
}
else{
CompTurbine$diff_days[i]<-CompTurbine$diff_days[i]
}
}
We need to manually put the dates which are set to zero because it has to be subtracted
from the data installed
Although we can easily replace it with few rows I want to write code which is generic
For this we have to know how many rows each category has and will then replace them will
the last one because they are the ones which are zero or NA
# setting the last NA to zero
CompTurbine[is.na(CompTurbine[,5]),5]<--1
# Now wherever there are zeroes we can replace them with the date installed

12. subtracted from the first fault occurence
CompTurbine$`Date Installed`<-as.Date(CompTurbine$`Date Installed`)
for(i in 1:nrow(CompTurbine)){
if(CompTurbine[i,5]==-1){
CompTurbine[i,5]<-CompTurbine[i,3]-CompTurbine[i,4]
}
}
NOTE: It might be a wrong practice to carry the dates installed as it is carrying the
same data.
After calculating the fault frequency in terms of days for all the three equipments let us put
the output in a nice format
knitr::kable(Kirlosker,caption = 'Kirlosker')
Kirlosker
Notifictn type Equipment Notif.date Date Installed diff_days
M1 11P19A 2017-05-18 2009-04-01 1074
M1 11P19A 2014-06-09 2009-04-01 154
M1 11P19A 2014-01-06 2009-04-01 113
M1 11P19A 2013-09-15 2009-04-01 52
M1 11P19A 2013-07-25 2009-04-01 172
M1 11P19A 2013-02-03 2009-04-01 85
M1 11P19A 2012-11-10 2009-04-01 101
M1 11P19A 2012-08-01 2009-04-01 14
M1 11P19A 2012-07-18 2009-04-01 65
M1 11P19A 2012-05-14 2009-04-01 389
M1 11P19A 2011-04-21 2009-04-01 420
M1 11P19A 2010-02-25 2009-04-01 330
M1 AGA951 2017-01-11 2010-04-01 391
M1 AGA951 2015-12-17 2010-04-01 576
M1 AGA951 2014-05-20 2010-04-01 664
M1 AGA951 2012-07-25 2010-04-01 524
M1 AGA951 2011-02-17 2010-04-01 322
M1 AGA952A 2016-10-28 2008-04-01 27
M1 AGA952A 2016-10-01 2008-04-01 90
M1 AGA952A 2016-07-03 2008-04-01 122

13. M1 AGA952A 2016-03-03 2008-04-01 629
M1 AGA952A 2014-06-13 2008-04-01 314
M1 AGA952A 2013-08-03 2008-04-01 9
M1 AGA952A 2013-07-25 2008-04-01 562
M1 AGA952A 2012-01-10 2008-04-01 113
M1 AGA952A 2011-09-19 2008-04-01 767
M1 AGA952A 2009-08-13 2008-04-01 73
M1 AGA952A 2009-06-01 2008-04-01 12
M1 AGA952A 2009-05-20 2008-04-01 414
M1 AGA955 2017-06-07 2008-04-01 300
M1 AGA955 2016-08-11 2008-04-01 246
M1 AGA955 2015-12-09 2008-04-01 195
M1 AGA955 2015-05-28 2008-04-01 114
M1 AGA955 2015-02-03 2008-04-01 159
M1 AGA955 2014-08-28 2008-04-01 1179
M1 AGA955 2011-06-06 2008-04-01 298
M1 AGA955 2010-08-12 2008-04-01 285
M1 AGA955 2009-10-31 2008-04-01 211
M1 AGA955 2009-04-03 2008-04-01 2
M1 AGA955 2009-04-01 2008-04-01 365
Z1 CGA201A 2017-01-02 2008-04-01 621
M1 CGA201A 2015-04-22 2008-04-01 194
Z1 CGA201A 2014-10-10 2008-04-01 240
Z1 CGA201A 2014-02-12 2008-04-01 544
Z1 CGA201A 2012-08-17 2008-04-01 302
Z1 CGA201A 2011-10-20 2008-04-01 367
Z1 CGA201A 2010-10-18 2008-04-01 374
Z1 CGA201A 2009-10-09 2008-04-01 556
M1 P301A 2017-02-16 2009-04-01 49
Z1 P301A 2016-12-29 2009-04-01 324
Z1 P301A 2016-02-09 2009-04-01 288
Z1 P301A 2015-04-27 2009-04-01 0
M1 P301A 2015-04-27 2009-04-01 441
Z1 P301A 2014-02-10 2009-04-01 368
Z1 P301A 2013-02-07 2009-04-01 372
M1 P301A 2012-02-01 2009-04-01 16

14. Z1 P301A 2012-01-16 2009-04-01 349
Z1 P301A 2011-02-01 2009-04-01 363
Z1 P301A 2010-02-03 2009-04-01 308
Z1 UGA302A 2016-05-24 2008-04-01 320
Z1 UGA302A 2015-07-09 2008-04-01 351
Z1 UGA302A 2014-07-23 2008-04-01 392
Z1 UGA302A 2013-06-26 2008-04-01 347
Z1 UGA302A 2012-07-14 2008-04-01 369
Z1 UGA302A 2011-07-11 2008-04-01 373
Z1 UGA302A 2010-07-03 2008-04-01 247
Z1 UGA302A 2009-10-29 2008-04-01 576
knitr::kable(KSB,caption = 'KSB')
KSB
Notifictn type Equipment Notif.date Date Installed diff_days
Z3 21P24A 2016-10-25 2008-04-01 976
Z3 21P24A 2014-02-22 2008-04-01 676
Z3 21P24A 2012-04-17 2008-04-01 353
Z3 21P24A 2011-04-30 2008-04-01 387
Z3 21P24A 2010-04-08 2008-04-01 382
M1 21P24A 2009-03-22 2008-04-01 23
Z3 21P24A 2009-02-27 2008-04-01 332
Z1 AGA901A 2017-04-07 2008-04-01 367
Z1 AGA901A 2016-04-05 2008-04-01 780
M1 AGA901A 2014-02-15 2008-04-01 304
M1 AGA901A 2013-04-17 2008-04-01 489
M1 AGA901A 2011-12-15 2008-04-01 358
M1 AGA901A 2010-12-22 2008-04-01 615
Z1 AGA901A 2009-04-16 2008-04-01 380
M1 P2001A 2017-05-29 2010-04-01 24
M1 P2001A 2017-05-05 2010-04-01 710
M1 P2001A 2015-05-26 2010-04-01 1504
M1 P2001A 2011-04-13 2010-04-01 377
Z3 P701A 2016-10-18 2008-04-01 711
M1 P701A 2014-11-07 2008-04-01 242
M1 P701A 2014-03-10 2008-04-01 703
Z3 P701A 2012-04-06 2008-04-01 343

15. Z3 P701A 2011-04-29 2008-04-01 384
Z3 P701A 2010-04-10 2008-04-01 409
Z3 P701A 2009-02-25 2008-04-01 330
Z1 P702A 2017-02-24 2008-04-01 232
M1 P702A 2016-07-07 2008-04-01 26
M1 P702A 2016-06-11 2008-04-01 5
M1 P702A 2016-06-06 2008-04-01 125
Z1 P702A 2016-02-02 2008-04-01 376
Z1 P702A 2015-01-22 2008-04-01 365
Z1 P702A 2014-01-22 2008-04-01 330
Z1 P702A 2013-02-26 2008-04-01 473
Z1 P702A 2011-11-11 2008-04-01 330
Z1 P702A 2010-12-16 2008-04-01 315
Z1 P702A 2010-02-04 2008-04-01 387
Z1 P702A 2009-01-13 2008-04-01 287
Z1 UGA1107A 2017-04-12 2008-04-01 190
Z1 UGA1107A 2016-10-04 2008-04-01 599
Z1 UGA1107A 2015-02-13 2008-04-01 663
Z1 UGA1107A 2013-04-21 2008-04-01 408
Z1 UGA1107A 2012-03-09 2008-04-01 283
Z1 UGA1107A 2011-05-31 2008-04-01 354
Z1 UGA1107A 2010-06-11 2008-04-01 353
Z1 UGA1107A 2009-06-23 2008-04-01 448
M1 UGA2201A 2017-06-01 2008-04-01 415
Z1 UGA2201A 2016-04-12 2008-04-01 357
Z1 UGA2201A 2015-04-21 2008-04-01 313
M1 UGA2201A 2014-06-12 2008-04-01 23
M1 UGA2201A 2014-05-20 2008-04-01 13
Z1 UGA2201A 2014-05-07 2008-04-01 332
M1 UGA2201A 2013-06-09 2008-04-01 16
Z1 UGA2201A 2013-05-24 2008-04-01 252
M1 UGA2201A 2012-09-14 2008-04-01 136
M1 UGA2201A 2012-05-01 2008-04-01 705
Z1 UGA2201A 2010-05-27 2008-04-01 5
Z1 UGA2201A 2010-05-22 2008-04-01 167
M1 UGA2201A 2009-12-06 2008-04-01 74

16. M1 UGA2201A 2009-09-23 2008-04-01 127
Z1 UGA2201A 2009-05-19 2008-04-01 92
M1 UGA2201A 2009-02-16 2008-04-01 321
knitr::kable(CompTurbine,caption = 'CompTurbine')
CompTurbine
Notifictn type Equipment Notif.date Date Installed diff_days
M1 11K01 2014-09-29 2009-04-01 183
M1 11K01 2014-03-30 2009-04-01 34
M1 11K01 2014-02-24 2009-04-01 74
M1 11K01 2013-12-12 2009-04-01 170
Z3 11K01 2013-06-25 2009-04-01 46
Z3 11K01 2013-05-10 2009-04-01 523
M1 11K01 2011-12-04 2009-04-01 244
Z3 11K01 2011-04-04 2009-04-01 0
Z3 11K01 2011-04-04 2009-04-01 217
M1 11K01 2010-08-30 2009-04-01 96
M1 11K01 2010-05-26 2009-04-01 22
M1 11K01 2010-05-04 2009-04-01 3
M1 11K01 2010-05-01 2009-04-01 33
Z3 11K01 2010-03-29 2009-04-01 0
Z3 11K01 2010-03-29 2009-04-01 362
Z3 11TK01 2017-02-02 2008-04-01 0
Z3 11TK01 2017-02-02 2008-04-01 69
M1 11TK01 2016-11-25 2008-04-01 9
M1 11TK01 2016-11-16 2008-04-01 4
M1 11TK01 2016-11-12 2008-04-01 115
M1 11TK01 2016-07-20 2008-04-01 37
Z3 11TK01 2016-06-13 2008-04-01 2
M1 11TK01 2016-06-11 2008-04-01 80
Z3 11TK01 2016-03-23 2008-04-01 0
Z3 11TK01 2016-03-23 2008-04-01 0
Z3 11TK01 2016-03-23 2008-04-01 5
Z3 11TK01 2016-03-18 2008-04-01 0
Z3 11TK01 2016-03-18 2008-04-01 12
Z3 11TK01 2016-03-06 2008-04-01 239
M1 11TK01 2015-07-11 2008-04-01 145

17. M1 11TK01 2015-02-16 2008-04-01 30
Z3 11TK01 2015-01-17 2008-04-01 39
Z3 11TK01 2014-12-09 2008-04-01 74
M1 11TK01 2014-09-26 2008-04-01 4
M1 11TK01 2014-09-22 2008-04-01 24
M1 11TK01 2014-08-29 2008-04-01 64
M1 11TK01 2014-06-26 2008-04-01 9
M1 11TK01 2014-06-17 2008-04-01 1
M1 11TK01 2014-06-16 2008-04-01 9
M1 11TK01 2014-06-07 2008-04-01 10
M1 11TK01 2014-05-28 2008-04-01 3
M1 11TK01 2014-05-25 2008-04-01 0
M1 11TK01 2014-05-25 2008-04-01 19
Z3 11TK01 2014-05-06 2008-04-01 1
Z3 11TK01 2014-05-05 2008-04-01 38
M1 11TK01 2014-03-28 2008-04-01 3
M1 11TK01 2014-03-25 2008-04-01 72
M1 11TK01 2014-01-12 2008-04-01 42
Z3 11TK01 2013-12-01 2008-04-01 33
Z3 11TK01 2013-10-29 2008-04-01 0
Z3 11TK01 2013-10-29 2008-04-01 46
M1 11TK01 2013-09-13 2008-04-01 0
Z3 11TK01 2013-09-13 2008-04-01 32
M1 11TK01 2013-08-12 2008-04-01 18
Z3 11TK01 2013-07-25 2008-04-01 26
Z3 11TK01 2013-06-29 2008-04-01 4
Z3 11TK01 2013-06-25 2008-04-01 19
Z3 11TK01 2013-06-06 2008-04-01 54
M1 11TK01 2013-04-13 2008-04-01 95
Z3 11TK01 2013-01-08 2008-04-01 0
Z3 11TK01 2013-01-08 2008-04-01 69
M1 11TK01 2012-10-31 2008-04-01 38
M1 11TK01 2012-09-23 2008-04-01 68
M1 11TK01 2012-07-17 2008-04-01 33
M1 11TK01 2012-06-14 2008-04-01 43
M1 11TK01 2012-05-02 2008-04-01 10

18. M1 11TK01 2012-04-22 2008-04-01 72
Z3 11TK01 2012-02-10 2008-04-01 9
M1 11TK01 2012-02-01 2008-04-01 23
Z3 11TK01 2012-01-09 2008-04-01 35
M1 11TK01 2011-12-05 2008-04-01 92
Z3 11TK01 2011-09-04 2008-04-01 55
M1 11TK01 2011-07-11 2008-04-01 0
M1 11TK01 2011-07-11 2008-04-01 20
Z3 11TK01 2011-06-21 2008-04-01 1
Z3 11TK01 2011-06-20 2008-04-01 25
M1 11TK01 2011-05-26 2008-04-01 7
M1 11TK01 2011-05-19 2008-04-01 10
M1 11TK01 2011-05-09 2008-04-01 39
Z3 11TK01 2011-03-31 2008-04-01 33
M1 11TK01 2011-02-26 2008-04-01 151
M1 11TK01 2010-09-28 2008-04-01 4
M1 11TK01 2010-09-24 2008-04-01 121
M1 11TK01 2010-05-26 2008-04-01 25
M1 11TK01 2010-05-01 2008-04-01 0
M1 11TK01 2010-05-01 2008-04-01 4
M1 11TK01 2010-04-27 2008-04-01 24
M1 11TK01 2010-04-03 2008-04-01 58
M1 11TK01 2010-02-04 2008-04-01 54
M1 11TK01 2009-12-12 2008-04-01 30
Z3 11TK01 2009-11-12 2008-04-01 111
M1 11TK01 2009-07-24 2008-04-01 15
M1 11TK01 2009-07-09 2008-04-01 76
M1 11TK01 2009-04-24 2008-04-01 94
M1 11TK01 2009-01-20 2008-04-01 294
M1 K431 2015-11-05 2009-04-01 622
M1 K431 2014-02-21 2009-04-01 155
M1 K431 2013-09-19 2009-04-01 24
M1 K431 2013-08-26 2009-04-01 65
M1 K431 2013-06-22 2009-04-01 78
M1 K431 2013-04-05 2009-04-01 228
M1 K431 2012-08-20 2009-04-01 31

19. M1 K431 2012-07-20 2009-04-01 0
M1 K431 2012-07-20 2009-04-01 86
M1 K431 2012-04-25 2009-04-01 44
M1 K431 2012-03-12 2009-04-01 265
M1 K431 2011-06-21 2009-04-01 205
M1 K431 2010-11-28 2009-04-01 0
M1 K431 2010-11-28 2009-04-01 146
M1 K431 2010-07-05 2009-04-01 95
M1 K431 2010-04-01 2009-04-01 365
M1 P607C 2016-10-13 2008-04-01 104
M1 P607C 2016-07-01 2008-04-01 88
Z1 P607C 2016-04-04 2008-04-01 365
Z1 P607C 2015-04-05 2008-04-01 43
Z1 P607C 2015-02-21 2008-04-01 189
M1 P607C 2014-08-16 2008-04-01 184
M1 P607C 2014-02-13 2008-04-01 188
M1 P607C 2013-08-09 2008-04-01 119
M1 P607C 2013-04-12 2008-04-01 8
Z1 P607C 2013-04-04 2008-04-01 0
Z1 P607C 2013-04-04 2008-04-01 336
M1 P607C 2012-05-03 2008-04-01 65
Z1 P607C 2012-02-28 2008-04-01 97
M1 P607C 2011-11-23 2008-04-01 156
M1 P607C 2011-06-20 2008-04-01 90
M1 P607C 2011-03-22 2008-04-01 45
Z1 P607C 2011-02-05 2008-04-01 600
Z1 P607C 2009-06-15 2008-04-01 440