CHAPTER 4

RESULTS AND ANALYSIS

4.1 Overview

Analysis is the principal tool for obtaining information from the data.

Statistical theories and methods are used to analyse the information

contained in its data. The data is then tabulated and calculated using

Microsoft Excel. Then, graphs for respective pumps are plotted using

Microsoft Excel. Finally, interpretations and comments are doing

throughout the process of analysis.

4.2 Results and Analysis

The basic data (running hours) for each pump has collected from SOGT

and then interpret it through statistical theory. The mean and standard

deviation for crude oil transfer pump P802, P803 and P804 are calculated

by using Microsoft Excel. After that, the data is tabulated in Table 4.1,

Table 4.2 and Table 4.3. The graph is then plotted in order to further

present the data more clearly.

4.2.1 Data Simulation for Crude Oil Transfer Pump P802, P803 and

P804

The data is collected, then tabulated and calculated by using Microsoft

Excel.

Table 4.1: Running Hours for Crude Oil Transfer Pump P802 from

Year 2011 to Year 2012 (Simulate Using Excel)

Month Running Hours

for P802

(Hours)

Cumulative

Running

Hours

Deviation,

x−X

¿

Jan-11 744 744 304.833 92923.361

Feb-11 332 1076 -107.167 11484.694

Mar-11 744 1820 304.833 92923.361

Apr-11 707 2527 267.833 71734.694

May-11 744 3271 304.833 92923.361

Jun-11 178 3449 -261.167 68208.028

Jul-11 197 3646 -242.167 58644.694

Aug-11 594 4240 154.833 23973.361

Sep-11 0 4240 -439.167 192867.361

Oct-11 504 4744 64.833 4203.361

Nov-11 0 4744 -439.167 192867.361

Dec-11 0 4744 -439.167 192867.361

Jan-12 86 4830 -353.167 124726.694

Feb-12 23 4853 -416.167 173194.694

Mar-12 88 4941 -351.167 123318.028

Apr-12 263 5204 -176.167 31034.694

May-12 744 5948 304.833 92923.361

Jun-12 694 6642 254.833 64940.028

Jul-12 735 7377 295.833 87517.361

Aug-12 704 8081 264.833 70136.694

Sep-12 273 8354 -166.167 27611.361

Oct-12 736 9090 296.833 88110.028

Nov-12 706 9796 266.833 71200.028

Dec-12 744 10540 304.833 92923.361

Sum,∑❑ 10540 0.000 2143257.33

3

Count, n 24

Average

(mean, X )=1054024

=439.167

Variance, s2 ¿∑ ¿¿¿

Standard

Deviation, s

¿√¿¿¿

Table 4.2: Running Hours for Crude Oil Transfer Pump P803 from

Year 2011 to Year 2012 (Simulate Using Excel)

Month Running Hours

for P803

(Hours)

Cumulative

Running

Hours

Deviation,

x−X

¿

Jan-11 744 744 283.667 80466.778

Feb-11 176 920 -284.333 80845.444

Mar-11 0 920 -460.333 211906.778

Apr-11 0 920 -460.333 211906.778

May-11 0 920 -460.333 211906.778

Jun-11 475 1395 14.667 215.111

Jul-11 744 2139 283.667 80466.778

Aug-11 734 2873 273.667 74893.444

Sep-11 692 3565 231.667 53669.444

Oct-11 720 4285 259.667 67426.778

Nov-11 720 5005 259.667 67426.778

Dec-11 744 5749 283.667 80466.778

Jan-12 712 6461 251.667 63336.111

Feb-12 627 7088 166.667 27777.778

Mar-12 728 7816 267.667 71645.444

Apr-12 458 8274 -2.333 5.444

May-12 0 8274 -460.333 211906.778

Jun-12 0 8274 -460.333 211906.778

Jul-12 0 8274 -460.333 211906.778

Aug-12 40 8314 -420.333 176680.111

Sep-12 542 8856 81.667 6669.444

Oct-12 742 9598 281.667 79336.111

Nov-12 706 10304 245.667 60352.111

Dec-12 744 11048 283.667 80466.778

Sum,∑❑ 11048 0.000 2423587.33

3

Count, n 24

Average

(mean, X )=11104824

=439.167

Variance, s2 ¿∑ ¿¿¿

Standard

Deviation, s

¿√¿¿¿

Table 4.3: Running Hours for Crude Oil Transfer Pump P804 from

Year 2011 to Year 2012 (Simulate Using Excel)

Month Running Hours

for P804

(Hours)

Cumulative

Running

Hours

Deviation,

x−X

¿

Jan-11 744 744 84.250 7098.0625

Feb-11 670 1414 10.250 105.0625

Mar-11 742 2156 82.250 6765.0625

Apr-11 709 2865 49.250 2425.5625

May-11 744 3609 84.250 7098.0625

Jun-11 576 4185 -83.750 7014.0625

Jul-11 706 4891 46.250 2139.0625

Aug-11 119 5010 -540.750 292410.5625

Sep-11 720 5730 60.250 3630.0625

Oct-11 744 6474 84.250 7098.0625

Nov-11 714 7188 54.250 2943.0625

Dec-11 744 7932 84.250 7098.0625

Jan-12 730 8662 70.250 4935.0625

Feb-12 627 9289 -32.750 1072.5625

Mar-12 667 9956 7.250 52.5625

Apr-12 720 10676 60.250 3630.0625

May-12 744 11420 84.250 7098.0625

Jun-12 720 12140 60.250 3630.0625

Jul-12 647 12787 -12.750 162.5625

Aug-12 743 13530 83.250 6930.5625

Sep-12 434 13964 -225.750 50963.0625

Oct-12 420 14384 -239.750 57480.0625

Nov-12 706 15090 46.250 2139.0625

Dec-12 744 15834 84.250 7098.0625

Sum,∑❑ 15834 0.000 491016.500

Count, n 24

Average

(mean, X )=1583424

=659.750

Variance,

s2¿∑ ¿¿¿

Standard

Deviation,

s

¿√¿¿¿

Table 4.4: Mean Time between Failure (MTBF) and Cumulative

Number of failure for each pump P804 from Year 2011 to Year

2012 (Simulate Using Excel)

Month Cumulative No.

of Failures

Mean Time Between

Failure (MTBF)

Failure Rate / year

P80

2

P80

3

P80

4

P802 P803 P804 P802 P803 P804

Jan-11 0 0 0 - - - - - -

Feb-11 0 1 1 - 1.278 1.964 - 9.522 6.195

Mar-

11

0 1 2 - 1.278 1.497 - 9.522 8.126

Apr-11 0 1 2 - 1.278 1.990 - 9.522 6.115

May-

11

0 1 2 - 1.278 2.506 - 9.522 4.855

Jun-11 0 1 2 - 1.938 2.906 - 6.280 4.186

Jul-11 0 1 2 - 2.971 3.397 - 4.095 3.582

Aug-

11

1 4 2 5.889 0.998 3.479 2.066 12.196 3.497

Sep-

11

2 4 2 2.944 1.238 3.979 4.132 9.829 3.058

Oct-11 3 4 2 2.196 1.488 4.496 5.540 8.177 2.706

Nov-

11

3 4 3 2.196 1.738 3.328 5.540 7.001 3.656

Dec-

11

3 4 3 2.196 1.996 3.672 5.540 6.095 3.313

Jan-12 4 4 3 1.677 2.243 4.010 7.255 5.423 3.034

Feb-12 4 4 3 1.685 2.461 4.300 7.220 4.944 2.829

Mar-

12

4 4 3 1.716 2.714 4.609 7.092 4.483 2.640

Apr-12 4 4 3 1.807 2.873 4.943 6.733 4.235 2.462

May-

12

4 5 3 2.065 2.298 5.287 5.891 5.294 2.301

Jun-12 5 5 3 1.845 2.298 5.620 6.594 5.294 2.165

Jul-12 5 5 4 2.049 2.298 4.440 5.937 5.294 2.740

Aug-

12

5 5 4 2.245 2.309 4.698 5.420 5.268 2.590

Sep-

12

5 5 4 2.321 2.460 4.849 5.243 4.946 2.509

Oct-12 5 5 4 2.525 2.666 4.994 4.818 4.563 2.436

Nov-

12

5 5 4 2.721 2.862 5.240 4.471 4.251 2.322

Dec-

12

5 5 4 2.928 3.069 5.498 4.156 3.965 2.213

4.2.2 Graphs of the Running Hour for Crude Oil Transfer Pump

P802, P803 and P804 from Year 2011 to Year 2012

Figure (): The graph of cumulative running hours against time for pump

P803 from year 2011 to year 2012.

Figure (): The graph of running hour against time for pump P802 from year

2011 to year 2012.

Figure (): The graph of running hour against time for pump P803 from year

2011 to year 2012.

Figure (): The graph of running hour against time for pump P804 from year

2011 to year 2012.

Figure (): The graph number of failure for respective pump from year 2011

to year 2012.

Figure (): The graph number of Mean Time between Failure (MTBF) for

each pump from year 2011 to year 2012.

Figure (): The graph number of failure rate per 2 years for each pump from

year 2011 to year 2012.

4.3 Discussion and Analysis

4.3.1 Interpretation and Comparison for each pump

From Table (), pump P804 has the highest cumulative running hours

compare with pump P802 and P803 from year 2011 to year 2012. Pump

P804 has the cumulative running hour of 15834 hours whereas pump P802

and P803 have the cumulative running hours of 10540 hours and 11048

hours. Besides, pump P804 also achieves the highest average (mean)

running hours of 659.750 hours from year 2011 to year 2012 compare

with pump P802 and P803. Meanwhile, from table (), pump P802 has the

lowest average running hours of 439.167 hours compare with pump P803

and P804.

From the table (), it can be observed that all the crude oil delivery

pumps didn’t work at its optimum running hours throughout two years.

The maximum running hours can be 24 x 2 x 365 = 17520 hours

throughout the two years’ time. The minor reasons due to they can’t work

at the optimum running hours are vibrations or cavitation, gearbox issues,

engines issues, misalignment between the pump and the driver and

leakage happen. However, the problems proposed by engineers from

SOGT are pump P804 more likely act as the duty pump meanwhile pump

P802 and pump P803 act as standby pump. In a clearer meaning is the

standby pump shall continue to operate until the duty pump is placed

back into service.

From the table (), it is showed that pump P804 has the lower

standard deviation compare with pump P802 and P803. Pump P804 has

achieved the standard deviation value of 146.111 hours compare with

pump P802 of 305.262 hours and pump P803 of 324.613 hours. From the

measurement of uncertainty, the lesser the standard deviation, the lesser

the uncertainty is. Thus, the more confidence the pump and higher the

reliability of the pump (Siddharth Kalla, 2009). So, it can be concluded that

pump P804 has the higher reliability than pump P802 and P803.

4.3.2 Number of Failure, MTBF and Fail Rate for each pump

From table (), pump P802 has the highest MTBF which is 5.889 on month

of August 2011. Pump P802 can achieve the highest MTBF without 7

months of failure. However, pump P803 has the lowest MTBF on month of

August 2011 because there are 3 times failures occur within a month

period. From the above interpretation, a relationship can be obtained

where MTBF somehow proportional to number of failures occur within that

period. This prove that the justification for MTBF is somehow correct.

From the table (), the MTBF values are calculated based on the

period for one month. Initial uses of MTBF can provide us with the average

time between failures2 for a given time period, and that this can then be

manipulated to give a failure rate3 for any specified period of time. The

following calculation example can provides more understanding about

MTBF.

For one measurement of MTBF on Month of August 2011 for P802

MTBF of the primary function = 5.889

Probability of a failure for P802 in a month = 1

5.889=0.169=16.9%

Probability of a failure for P802 in a day = 1

5.889×30=5.66×10−3=0.566%

Likelihood of a failure for P802 in an hour =

15.889×30×24

=2.36×10−4=0.024%

There are several ways to improve the MTBF for crude oil delivery

pump, including all their component parts, the consensus is that the best

option is to operate as near as possible to their best efficiency point, BEP.

Besides, there are other recommended methods to help out in prolonging

the MTBF. For example, reduce impeller diameter, install by-passes, have

speed-controlled drivers, control flow rates with automatically operated

valves, put holes through impellers to equalize pressures are other ways

to improve the MTBF.

Instead of using MTBF, there is another way to be suggested by

using MTBR, or known as mean time between repairs (Robert X. Perez,

2014). Robert (2014) define MTBR as the mean number of life units

between repair activities required to bring all parts of the item back to

within their specified limits, during a particular measurements interval

under stated conditions. MTBR is similar to MTBF, but uses repair events

instead of failure events. The following equation is used to determine

MTBR:

MTBR=NR

Where N is the number of machines in the populations

R are the number of repairs in the measurement

period.

Of these three metrics, MTBR is probably the most widely used for

evaluating pump reliability. However, MTBR also encounter with

limitations and caveats. First of all, it includes the mean pump life along

with the mean time for the organization to identify, plan, and repair the

pump, which tends to inflate the value of MTBR (Robert X. Perez, 2014).

The MTBR metric is an amalgamation of repair data for all pumps, running

and idle, that are included in the population tends to greatly increase its

value compared to the true mean time to failure (Robert X. Perez, 2014).

Besides, the repair data supplied for the calculation is subject to

interpretation, therefore it is prone to errors and inconsistency (Robert X.

Perez, 2014).