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Weekly Science Research Journal

Primary Article

Down Time Analysis In Process Industry-A Case
Study

Dnyaneshwar R.Thawkar

Dnyaneshwar R.Thawkar
From

Asst. professor
M.Tech.(Industrial Engineering)

Umrer college of Engineering, Umrer

The Article is published on October
2013 issue & available at

www.weeklyscience.org

10.9780/ 2321-7871/1142013/42DOI:

ABSTRACT

The growths of present day industries are forced towards the use of more
complex system. The production system consists thousands of parts and
components and the failure of one or more component may lead to affect the
entire production system. So with increase in automation and usage of
complex systems, evaluation of reliability has recently been recognized for
effective maintenance. Reliability has been evaluated mostly for electronic
components since and presently we are going to calculate Reliability for
components in process industry. For this purpose, the break down time is
calculated from sugar Industry. The data to be analyzed and reliability is
calculated for each component by weibull distribution in probability is
analyzed and criticality of each component is found by using FMEA (Failure
Mode Effect Analysis) software to suggest some of the preventive maintenance
schedules.

Reliability, Weibull, Availability, MTBF, FMEA.Keywords:

1.0 INTRODUCTION

1.1 METHODOLOGY

1.2 MEAN TIME BETWEEN FAILURES (MTBF)

The study was carried in sugar mills limited is situated NAGAPP
ATTINAM district in Tamil Nadu. The crushing capacity of the plant is 3500
TCD (Tones of cane Crushed per day). The various processing sections of the
factory are namely a) Loading section b) Mill section c) boiling section. The
preliminary discussion with the official's concerned reveal that the plant is
often giving rise to problems due to breakdown of various components; and
hence, it is decided to carry out failure analysis in this industry, and to suggest
measures to improve the availability of the components The objective of the
study is to estimate the availability, reliability of the components system and
also to perform the FMEA analysis to identify the critical components to
prepare PM (Preventive Maintenance) schedule by officials.

The methodology followed to achieve is as follows:
1.The historical failure data, the down time and the availability of the
equipment is collected.
2.From the past failure data, the down time and the availability of the
equipment is calculated.
3.Weibull statistical distribution is used to model the failure history.
4.Using the parameters of weibull distribution the estimation of reliability has
been carried out.
5.Using FMEA software package, the criticality index of all components is
calculated.
6.The maintenance schedules are prepared in such a way that the system will
operate at or below minimum failure rate.

The mean time between failures refers to average time of breakdown
until the device beyond Repair. The mean time between failures is one of the

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useful terms in maintenance and reliability analysis.


Operating Time
MTBF = _______________

Number of failures

Failure data of the plant are collected refers to average time of breakdown until the
device beyond repair. The mean time between failures is one of the useful terms in
maintenance and reliability analysis. MTBF = Operating Time Number of failures.

It is doable to outline 3 sorts of availableness reckoning on the time parts we have a
tendency to soak up to consideration. These are,Inherent availableness is that the chance
that a system or instrumentation shall operate satisfactorily once used below expressed
conditions in a perfect support settingwithout consideration for any schedule or preventive
maintenance at any given time .deliver the goods availableness within the definition of
inherent availableness we have a tendency to thought-about MTBF that doesn't take
in to account the period caused by maintenance. If this can be conjointly taken into
consideration, we get the achieved availableness, that is outlined to the chance that a
system or instrumentation shall operate satisfactorily once used below expressed
conditions in a perfect support environment at any given time. If any real time operation, we
have a tendency to can't scale back body period and provide downtime to zero. a definite
quantity of delay can continually be caused by time parts like these, and if they're taken in
to account it. Operational Availability of the system be the probability that a system or
equipment shall operate satisfactorily and in an actual supply environment at any given
time.

MTBF
A = _____________0

MTBF + MDT

Where MTBF Mean Time Between Failures, MDT Mean Down Time

Downtime is the non-productive time of the machine. Downtime of the components
are calculated and tabulated with the help of the data collected. Table 4.2 shows the
downtime of the various components from March'04 to May'04. For example, the downtime
of the CANRCARRIER during March'04 is observed to be 6.45 hrs: min, which is the sum of
the breakdown hours on various occasions during the month of March'04. Similarly for all
other components for various periods, the want of cane time are calculated and tabulated.
Table 4.3 presents the data with respect to the number of failures for each component
month wise.

Reliability, which is a measure of quality, is an essential element at each stage of the
equipment manufacturing procedure through design and production to final delivery to the
user. Reliability, It is simplest form, means the probability that a failure may not occur in a
given time interval. A more rigorous definition of reliability is a follows “Reliability of a unit
(or product ) is the probability that the unit performs its intended function adequately for a
given period of time under the stated operating conditions or environment”. Reliability
characteristics, such as probability of survival, mean time to failure, availability, mean
down time and frequency of failures are some of the measures of system effectiveness.
Apart from the above factors, reliability does change due to other factors like quality,
workmanship, manufacturing process, material, storage, handling, engineering changes,
and deviations in production, inspection and test.

1.3 DATA COLLECTION

1.4 AVAILABILITY

1.5 ESTIMATION OF OPERATIONAL AVAILABILITY
Downtime of Components

1.6 RELIABILITY ESTIMATION
Definition of Reliability

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Application of Weibull Distribution
In 1951, Weibull suggested a simple empirical expression, which represents a great varies

of actual data. The weibull cumulative distribution function is given by
-(t – ë / á)â

F(t) = 1-e t > ë, â > 0
= 0, otherwise

Where ,

á – Scale parameter

â – Shape factor

ë – Location factor

There various functions are given as
R (t) = Reliabilities = exp[-(t- ë) / á) â]
ë (t) = Failure rate = â] / á ((t- ë) / á) â-1

The constants appearing in these expressions represent.

Mean Time Between Failures is referred to as the average time to satisfactory operation of
the system. This term is useful to carryout the maintenance and reliability analysis.

Operating time
MTBF = ________________

No. of failures

Total Available Time – Non-operating time
= _______________________________________
No. of failures

For example:
Component Name = Cane Carrier
Total available time = (31+30+31) x 24 hrs

= 2208 hrs.
Non-operating time = Total breakdown time of cane carrier

= 13.00 hrs:min[FromTable 4.2]
Number of Failures= 10[From Table 4.3] 2208- 13.00

2208 – 13.00
MTBF = _____________

10
= 219.50

The statistical mean of downtime d1, d2,d3, …….. including supply time and
administrative downtime is called mean downtime. This mean downtime is concentrated on
breakdown time maintenance time and non-availability of components Table 4.5 shows the mean
downtime of various components.

For Example:
Month = March'04
Component = Cane Carrier
Downtime due to Breakdown = 13.00 hrs: min [Table 4.2]
General down time = 156.40 hrs: min [Table 4.4]
Total down time = 13.00 + 156.40

= 163.25 hrs: min

Mean down time = 163. 25+ 71.00 + 179.50
_____________________

3
= 138.32 hrs.

MTBF of components

Mean Downtime

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Availability of components

1.7 FAILURE TIME DISTRIBUTION: CALCULATION PROCEDURES

It is possible to define three types of availability of an equipment hours in
actual environments operational availability is defined as to be the probability that a
system of equipment shall operate satisfactorily when used under stated condition in
an actual environment at any given time.

Mean time between failure
A0 = ____________________________

Mean time between failure + Mean Down Time

For Example:

Component Name = Cane Carrier
MTBF = 219.50 hrs
MDT = 138.32 hrs

219.50
Mean down time = ________________

219.50 + 138.32

= 61.34%

Thus Availability of all components is calculated and tabulated in the TABLE

4.6 ã – Locating constant defining the starting point or origin of the distribution ã can

be thought as a gurantee period in which no failure can occur or it can be thought of
as the minimum life.

á – Scaling constant, stretching the distribution along the time axis.

â – Shape parameter, which decides the shape pattern of failure.

When dealing with failure rates, the weibull shape parameter â is special
importance as it describes the mode of failure.

For example, if
â < 1, it indicates that the failure rate is a decreasing function of time and is

characterizes as an early failure phase.

â =1, it means the failure rate is constant overtime, as is the case for exponential
distribution.
â > 1, it means that the failure rate is increasing with time and can be characterized
as the out phase.

The following procedure is adopted to calculate the required parameters.
i) Class interval

max min
T – T

I = ____________________
1 + 3...31og N

Where,
T max – max. Time between failures
T min – min Time between failures
N – Total number of failures in the test time

ii) Percentage of failure
Number of failures in the time, interval

% failed = ___________________________________
Total Number of failures

iii) Cumulative percentage of failure
n

F(t)= Ó fi

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I = 1
n – Corresponding time interval sequence number.

R (t) Reliabilities = exp [-(t-ã) / á) ]â

From Weibull Graph
á = 1410
â = 1.8
ì/ á = 0.888
Therefore ì = 1252.08 hrs
T = ì + ã = 1252.08+ 0

= 1252.08 hrs.
R (t) = exp [- (1252.08-0) /- 1410) 1.8]* 100
= 44.6%

Thus Reliability is calculated for each component and it is tabulated in the TABLE.5.1.
From calculation of Reliability for all components it is found that New boiler has low Reliability

The following logical steps should be followed when an FMEA,
1.Identify the product or system components.
2.List all possible failure modes of each component.
3.Set down the effects that each mode of failure would have on the over all function of products
system.
4.List all the possible causes of each failure mode.
5.Asses numerically the failure modes on a scale from 1 to 10.
6.Experience and Reliability data from company is given a input to determine the values, on a
scale 1-10 for severity (S), Occurrence (O) 7ecion (D).

Severity is the assessment of the seriousness of the effect of potential failure of system,
subsystem or component severity is applicable only to effect of failure mode severity is rated by
ranking by which 1 is for no effect and 10 for the most severe (serious) effect.

Occurrence is the probability that one of the specific cause/mechanism of failure will
occur.The likelihood of occurrence is assessed as 1 for least chance of occurrence and 10 for
highest Chance of occurrence.

It is the relative measure of difficulty of detecting the failure before the product or service
is used by customer. If the design control certainly detect cause/mechanism of failure then it is
ranked or it is difficult to detect then it is ranked. Thus when these inputs are given, the results
generated from the software are tabulated in the table 6.1. The criticality index for each
component is generated and ranked according to the critical failure modes. This indicates the
relative priority of each failure mode and to concentrate on preventive activity of critical
components.

Availability of data regarding the equipment Reliability is of considerable benefit to
industry in many situations. Knowledge of life expectancy and wear out characteristics of the
system components leads to the development of sound Maintenance and appropriate provision
for spare parts and stand by equipment. It is possible to correlate equipment Reliability
withmaintenance requirements. Machines made by man, at any time succumb to fail. To attain
maximum productivity it is necessary that man minimize failure. This can be achieved by proper

iv) Reliability

REALIABILITY OF COMPONENTS

COMPONENT NAME: CANE CARRIER

1.8 FMEA ANALYSIS AND PROCESS

SEVERITY (S)

OCCURRENCE (O)

DETECTION (D)

1.9 CONCLUSION

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maintenance and timely replacements of some parts of machines or at times the whole
equipment. The timely replacement improves the machine Reliability as well as Availability
and made it useful for a achieving high productivity. An attempt had made in this thesis to
study the failure pattern and down time of the components. The critical components have
also been identified by carrying out FMEA analysis. It would be economical if the failures of
these critical components are minimize by proper preventive maintenance measures.

1.Govil. A.K. (1983), Reliability Engineering, Tata, Mcgraw Hill Company Ltd., New Delhi.
2.Lewis W.W.(1987),” Introduction to Reliability Engineering”, John Willey & sons, Newyork.
3.Malik M.A.K(1979),” A note on the physical Meaning of the Weibull Distrubition”, IEEE
Trans. On Reliability, Vo 1. 24, No.1, Page:95.
4.Sinha S.K.(1980),” Life Testing And Reliability Estimation”, Willey Eastern Limited, India.
5.Srinath. L., “Reliability Engineering” . Balagurusamu E.,” Reliability Engineering”.

TABLE 4.7 : VALUE OF TMAX AND TMIN

Table 4.1: Failure Data (fro example) Data Wise – March “04”

2.0 REFERENCES

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Sr. No. NAME OF THE COMPONENT TMAX (HRS)
TMIN

(HRS)
1 CANE CARRIER 601.45 39.15
2 MILLS 44.20 1.50
3 RAKE/INTER CARRIER 395.20 0.30
4 BAGASSE CARRIER 568.45 32.00

5 NEW BOILER 1478.00 9.00
6 ELECTRICALS 1313.25 14.30
7 OLD BOILER 767.00 1.25
8 LOW PRESSURE BOILER 785.75 267.15
9 POWER TURBINE 881.45 153.00

10 OTHER UNITS IN BOILER 1541.40 14.35

11 RAW JUICE PUMP 819.00 1.05
12 EVAPORATOR 776.15 1.15
13 PAN 1132.60 0.45
14 SYRUP STORAGE TANK 943.45 9.30
15 OTHER UNITS IN BOILING HOUSE 522.20 27.20



DATE FROM TO TOTAL HOURS REASON

02.03.04
7.25 7.45 0.20 To reduce Juice Level in the Evaporator

8.40 9.15 0.35 To reduce Juice in the evaporator
03.03.04 -- -- -- Holiday
04.03.04 -- -- -- Holiday

05.03.04

8.30 8.55 0.25 Boiler water Scarcity
9.25 9.40 0.15 Kicker Jamming
9.50 16.50 7.00 11

nd
mill top roller shell circumference

crack.

Page 7

TABLE 4.2 : DOWN TIME OF COMPONENTS

TABLE 4.3: NUMBER OF FAILURES OF COMPONENTS

TABLE 4.4: GENERAL DOWN TIME

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S.NO. NAME OF THE COMPONENT MARCH
(HRS)

APRIL
(HRS)

MAY
(HRS)

TOTAL
(HRS)

1 CANE CARRIER 6.45 5.10 1.05 13.00
2 MILLS 10.25 6.25 1.35 18.25
3 RAKE / INTER CARRIER 3.45 4.35 2.30 10.50
4 BAGASSE CARRIER 0.45 4.15 0.40 5.40
5 NEW BOILER 63.25 -- 0.30 63.55

6 ELECTRICALS 0.30 2.05 3.15 5.50
7 OLD BOILER 2.00 2.05 1.10 5.15
8 LOW PRESSURE BOILER -- 2.50 0.55 3.45
9 POWER TURBINE 8.45 0.25 1.10 10.20

10 OTHER UNITS IN BOILER 2.55 -- 0.55 3.50
11 RAW JUICE PUMP 9.00 2.45 1.55 13.40
12 EVAPORATOR 1.45 0.15 1.55 3.55

13 PAN 5.00 -- 6.25 11.25
14 SYRP STORAGE TANK 2.15 1.30 2.55 6.40
15 OTHER UNITS IN BOILIBG

HOUSE
1.30 2.05 3.20 6.55



SR.
NO.

NAME OF THE
COMPONENT

MARCH
(HRS)

APRIL
(HRS)

MAY
(HRS)

TOAL No.
OF

FAILURES
1 CANE CARRIER 2 5 3 10
2 MILLS 6 6 2 15

3 RAKE / INTER CARRIER 6 7 2 15

4 BAGASSE CARRIER 2 5 2 9
5 NEW BOILER 12 -- 1 13
6 ELECTRICALS 1 1 4 6
7 OLD BOILER 3 3 2 8
8 LOW PRESSURE BOILER -- 2 1 3

9 POWER TURBINE 2 1 2 5
10 OTHER UNITS IN BOILER 4 -- 2 6
11 RAW JUICE PUMP 5 4 3 12
12 EVAPORATOR 4 1 5 10
13 PAN 7 -- 4 11
14 SYRP STORAGE TANK 3 1 4 8

15
OTHER UNITS IN BOILIBG
HOUSE

1 3 3 7



MONTH
GENERAL

CLEANING
(HRS)

WANT OF
CANE (HRS)

HOLIDAY
(HRS)

TOTAL
HOURS

MARCH “04” 19.35 65.05 72.00 156.40
APRIL “04” 15.45 2.05 48.00 65.50

MAY “04” 58.45 58.45 120.00 178.45

Page 8

TABLE 4.5 : MEAN DOWN TIME OF COMPONENT

TABLE 4.6 : AVAILABILITY OF COMPONENTS

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S.
NO

NAME OF THE
COMPONENT

TOTAL DOWN TIME (HRS : MIN) MEAN DOWN
TIME

(HRS:MIN)
MARCH
(156.40)

APRIL
(65.50)

MAY
178.45)

1 CANE CARRIER 163.25 71.00 179.50 138.32
2 MILLS 167.05 72.15 180.20 140.20
3 RAKE / INTER CARRIER 160.25 70.25 181.15 137.22

4 BAGASSE CARRIER 157.25 70.05 179.25 135.52
5 NEW BOILER 220.05 65.50 179.15 155.30
6 ELECTRICALS 157.10 67.55 182.00 135.55
7 OLD BOILER 158.40 67.55 179.55 135.17
8 LOW PRESSURE BOILER 156.40 68.40 179.40 135.13
9 POWER TURBINE 165.25 66.15 179.55 137.38

10 OTHER UNITS IN
BOILER

159.35 65.50 179.40 135.15

11 RAW JUICE PUMP 165.40 68.35 180.40 138.05
12 EVAPORATOR 158.25 66.05 180.40 135.30
13 PAN 161.40 65.50 185.10 137.33

14 SYRP STORAGE TANK 158.55 6720 181.40 136.12
15 OTHER UNITS IN

BOILIBG HOUSE
158.10 67.55 182.05 136.30



S.
NO.

NAME OF THE COMPONENT MTBF
(HRS)

MDT
(HRS)

AVAILABILITY
(%)

1 CANE CARRIER 6.45 138.32 61.34
2 MILLS 10.25 140.20 51.08
3 RAKE / INTER CARRIER 3.45 137.22 51.64
4 BAGASSE CARRIER 0.45 135.52 61.40
5 NEW BOILER 63.25 155.30 51.57

6 ELECTRICALS 0.30 135.55 73.03
7 OLD BOILER 2.00 135.17 67.08
8 LOW PRESSURE BOILER -- 135.13 84.47
9 POWER TURBINE 8.45 137.38 76.19

10 OTHER UNITS IN BOILER 2.55 135.15 73.11
11 RAW JUICE PUMP 9.00 138.05 57.04
12 EVAPORATOR 1.45 135.30 61.97

13 PAN 5.00 137.37 59.30
14 SYRP STORAGE TANK 2.15 136.12 66.91
15 OTHER UNITS IN BOILIBG

HOUSE
1.30 136.30 69.76

Page 9

TABLE 5.1 : RELIABILITY OF COMPONENTS

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S. NO. NAME OF THE
COMPONENT

á â AVAILABILITY
(%)

1 CANE CARRIER 1410 1.8 44.6
2 MILLS 1300 1.4 41.07
3 RAKE / INTER CARRIER 1000 1.97 45.4
4 BAGASSE CARRIER 1350 2.5 49.16
5 NEW BOILER 410 0.60 24.68

6 ELECTRICALS 1500 2.27 48.24
7 OLD BOILER 1200 1.6 43.03
8 LOW PRESSURE BOILER 1600 2.59 50.32
9 POWER TURBINE 1500 2.61 55.12
10 OTHER UNITS IN BOILER 610 1.00 36.79
11 RAW JUICE PUMP 1100 2.00 45.69
12 EVAPORATOR 1300 1.2 38.59

13 PAN 1048 1.8 44.52
14 SYRP STORAGE TANK 1200 1.8 44.45
15 OTHER UNITS IN BOILIBG

HOUSE
1400 2.25 47.69

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