Engine Room Module Installation System Risk Analysis Based on Bayesian Network

Abstract

Implementation of system installation risk on engine room module aims to anticipate ship production delays. However, in its implementation, there is the problem of ship delivery delays in various shipbuilding companies. This research will analyze the risk analysis of the installation of the engine room module system by identifying risk factors and parameters that affect performance as a hazard identification that has the potential to cause delivery delays. The object of the research is the Indonesian Navy's Auxiliary Hospital Ship, which has 6 zones with a pilot project developed in zone 2. This includes an engine room that contains important constructions in the form of a main motor foundation, auxiliary motor, and other machinery, where the system was integrated. Moreover, there are some works consisting of construction, outfitting, and commissioning which are very complicated and require high accuracy. The aim of the implementation of risk analysis of the installation system in the engine room’s module is to assess potential risks, the effect of risk on project delays, and project cost overruns. The research method uses a Bayesian network because it is able to assess the most potential risks and predict the possibility of delays at network nodes. The primary risk is associated with electrical activities, specifically electrical outfitting on wiring, clamping, and compound sub-components with a probability of (0.0002560) in the Machinery Outfitting and Electrical Department. This risk stems from inappropriate steps during drawing revisions, which have the potential to cause delays in equipment installation, cable material procurement, and the generation of cable cutting data. Therefore, early coordination with production planning control, design, and the supply chain is crucial.

Keywords

• bayesian network
• installation engine room module
• risk analysis