TY - JOUR
T1 - Plant Maintenance Modelling through Availability Analysis in Raw Mill of Cement Production
AU - Jufri, N.
AU - Siswanto, N.
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2020/12/28
Y1 - 2020/12/28
N2 - Maintenance activities are a particular concerned at PT XYZ, which is the largest cement producer in Eastern Indonesia. PT XYZ has five main factories located in Pangkep, South Sulawesi, units 1,2,3,4, and 5. In 2019, PT XYZ's five clinker production only reached 2,445,515 tons or 93, 64% of the target. The details, raw meal production was not achieved, namely 4,041,377 tons or 96.54% of the target set by the company due to the unplanned shutdowns. This research tries to control the breakdowns of raw mill machine by evaluating the availability and day of operation (calendar day). The availability analysis method used is the discrete system simulation approach because the discrete system simulation can accommodate random behavior and dependence between variables. In the existing condition, system availability is 72.83% and calendar day is 239 days. These two parameters are still less than the target. To overcome this problem, experimentation was carried out with 3 scenarios. The best simulation results shows that the preventive maintenance activities changes the value of TTF (Time to Failure), TTR (Time to Repair), and reduces the duration of overhaul activities. This can increase the availability to 83.04% and calendar day to 255 days.
AB - Maintenance activities are a particular concerned at PT XYZ, which is the largest cement producer in Eastern Indonesia. PT XYZ has five main factories located in Pangkep, South Sulawesi, units 1,2,3,4, and 5. In 2019, PT XYZ's five clinker production only reached 2,445,515 tons or 93, 64% of the target. The details, raw meal production was not achieved, namely 4,041,377 tons or 96.54% of the target set by the company due to the unplanned shutdowns. This research tries to control the breakdowns of raw mill machine by evaluating the availability and day of operation (calendar day). The availability analysis method used is the discrete system simulation approach because the discrete system simulation can accommodate random behavior and dependence between variables. In the existing condition, system availability is 72.83% and calendar day is 239 days. These two parameters are still less than the target. To overcome this problem, experimentation was carried out with 3 scenarios. The best simulation results shows that the preventive maintenance activities changes the value of TTF (Time to Failure), TTR (Time to Repair), and reduces the duration of overhaul activities. This can increase the availability to 83.04% and calendar day to 255 days.
UR - http://www.scopus.com/inward/record.url?scp=85098890977&partnerID=8YFLogxK
U2 - 10.1088/1757-899X/1003/1/012117
DO - 10.1088/1757-899X/1003/1/012117
M3 - Conference article
AN - SCOPUS:85098890977
SN - 1757-8981
VL - 1003
JO - IOP Conference Series: Materials Science and Engineering
JF - IOP Conference Series: Materials Science and Engineering
IS - 1
M1 - 012117
T2 - 2nd International Conference on Industrial and Manufacturing Engineering, ICI and ME 2020
Y2 - 3 September 2020 through 4 September 2020
ER -