TY - JOUR
T1 - Risk Analysis of Engine Room Module Installation with Integration of Bayesian Network and System Dynamics
AU - Baroroh, Intan
AU - Ariana, I. M.
AU - Dinariyana, A. A.B.
N1 - Publisher Copyright:
© 2022 Praise Worthy Prize S.r.l.-All rights reserved.
PY - 2022
Y1 - 2022
N2 - The hospital auxiliary ship has been built using a modular system that can speed up ship manufacture by up to 50%. However, in actual shipbuilding, the engine room module has a 29% longer time allotment than the other zones. Therefore, the zone might potentially have the most delay during the entire process of manufacturing a modular ship. Production delays are brought on by incorrect block dimension accuracy, the delivery of pictures that are out of order, the state of damaged machines, the loading of blocks that aren’t scheduled, and the amount of drawing changes in addition to equipment and basic material shipping delays. The workshop where the engine room installation has been built has experienced a delay. By using the Bayesian Network and System Dynamics integration technique, the main cause of delay in this study can be predicted sooner. The Electrical Outfitting workshop has the most potential delay, according to the simulation results. The production index has fallen by 45%, and production has taken 51% longer than originally planned. This is due to the delay in revising the drawings, cable materials, equipment, and cable cutting data.
AB - The hospital auxiliary ship has been built using a modular system that can speed up ship manufacture by up to 50%. However, in actual shipbuilding, the engine room module has a 29% longer time allotment than the other zones. Therefore, the zone might potentially have the most delay during the entire process of manufacturing a modular ship. Production delays are brought on by incorrect block dimension accuracy, the delivery of pictures that are out of order, the state of damaged machines, the loading of blocks that aren’t scheduled, and the amount of drawing changes in addition to equipment and basic material shipping delays. The workshop where the engine room installation has been built has experienced a delay. By using the Bayesian Network and System Dynamics integration technique, the main cause of delay in this study can be predicted sooner. The Electrical Outfitting workshop has the most potential delay, according to the simulation results. The production index has fallen by 45%, and production has taken 51% longer than originally planned. This is due to the delay in revising the drawings, cable materials, equipment, and cable cutting data.
KW - Engine Room Module
KW - Integration of Bayesian Network and System Dynamic
KW - Most Potential Delay
KW - Production Delays
KW - Production Index
KW - Risk Analysis
UR - http://www.scopus.com/inward/record.url?scp=85139418792&partnerID=8YFLogxK
U2 - 10.15866/ireme.v16i6.22456
DO - 10.15866/ireme.v16i6.22456
M3 - Article
AN - SCOPUS:85139418792
SN - 1970-8734
VL - 16
SP - 299
EP - 308
JO - International Review of Mechanical Engineering
JF - International Review of Mechanical Engineering
IS - 6
ER -