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DOWNTIME ANALYSIS OF EXPELLER MACHINES – A CASE STUDY

Table 2: Steady state probability of of breakdown per day during the study
breakdown, working and mean down time period. Majority of the machine breakdown
(in minutes) of expeller machines time follows 3-parameter Weibull
distribution. The limiting probabilities that
Machine Down Working Mean
No time Probability Down the machine getting breakdown were higher
Probability time in machine no 29, 6, 31 and 19 than other
(mint) selected machines. Production loss of virgin
2 0.408 0.592 14.052 coconut oil due to breakdown of selected
3 0.044 0.956 13.703 machine during the study period was
6 0.552 0.448 16.472 significant and it was around 60 liters per
8 0.328 0.672 16.229 day. Among the selected 12 expeller
9 0.424 0.576 14.324 machines no 6, 8, 10 and 29 were identified
10 0.290 0.710 16.116 as low productive machines since those
19 0.492 0.508 14.775 machines possess high mean breakdown
23 0.334 0.666 11.257 time. The above situation reveals the
26 0.328 0.672 15.230
28 0.313 0.687 13.783 necessity of implementing immediate
29 0.662 0.338 16.750 actions such as preventive maintenance
31 0.493 0.507 13.629 system to reduce production loss due to
expeller machine breakdown embedded in
Table 3: Production loss of expeller the production process to achieve the
machines expected profit.

Machin Mean Down time Production REFERENCES
e No (mint) Loss
(VCO  Ab-Samat H., Jeikumar L.N., Basri, E.
Quantity /ι) I., Harun, N.A., & Kamaruddin, S.,
2 14.052 4.5 (2012). Effective Preventive
3 13.703 4.39 Maintenance Scheduling: A Case Study.
6 16.472 5.27 In Proceedings of the 2012 International
8 16.229 5.19 Conference on Industrial Engineering
9 14.324 4.58
10 16.116 5.16 and Operations Management, 3-6.
19 14.775 4.73  Chandrakar, J. & Kumar, R., (2015).
23 11.257 3.6 Reduction of breakdowns in food
26 15.229 4.87 processing plants through failure analysis.
28 13.783 4.41 International Journal of Advanced
29 16.750 5.36 Engineering Research and Studies, E-
31 13.629 4.36 ISSN2249–8974.

According to the results, machines 6,  Kiran, M., Mathew, C., Kuriakose, J.,
8, 10 and 29 are having higher mean down (2013). Root Cause Analysis for Reducing
times and accordingly higher production Breakdowns in a Manufacturing Industry.
loss occurred in these machines. International Journal of Emerging
Technology and Advanced Engineering,
6 CONCLUSION 3(1).

The present study depicts that  Kumar, P.R., & Rudramurthy (2013).
machine breakdown time directly impacts Analysis of Breakdowns and
on reducing the production of virgin coconut Improvement of Preventive Maintenance
oil (VCO) in the company. The study on 1000 Ton Hydraulic Press. Journal of
revealed that, approximately 50% of Emerging Technology and Advanced
expeller machines utilized per day to Engineering. 3(8), 636-645.
produce VCO. That is, in this company,  Mobley R. K., (2002). An introduction
around half of the machines were in the state to predictive maintenance. Butterworth-
Heinemann.

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