{"title":"DEVELOPMENT OF MODEL-DRIVEN DECISION SUPPORT SYSTEM TO SCHEDULE UNDERWATER HULL CLEANING","authors":"A. Dinariyana, Pande Pramudya Deva, I. Ariana","doi":"10.21278/brod73302","DOIUrl":null,"url":null,"abstract":"Maritime industries are constantly searching for a method to enhance ship efficiency, with increasing concern about the environmental impact and rising fuel prices. Marine biofouling is one of the factors that increase ship fuel consumption. However, removing the fouling of the ship requires effort for hull maintenance. Due to the trade-off between conducting maintenance and performance degradation, this study presents the development of a Model-Driven Decision Support System (MD-DSS) to predict the optimum time for underwater hull cleaning for biofouling management. Five stages (sub-models) are employed to develop a DSS, namely: ship resistance estimation, estimation of additional resistance due to biofouling, an iterative-based method for determining the best time to conduct the hull cleaning, and an analysis report. The implemented algorithm was validated by comparing its result with a manually scheduled maintenance date. The DSS is able to determine the best time (date) for maintenance in all given scenarios. By giving two scenarios of different maintenance costs and different fuel prices, the optimisation results produce the same number of maintenances. Within 60 months, four to five hull cleanings are required. It is also found that when the optimal number of maintenances is known, then increasing this number will not have any impact on reducing the hull cleaning costs because the reduction in fouling does not significantly reduce the costs incurred for maintenance. During several trials of the DSS, it is shown that the system can generate maintenance schedules for different time intervals of ship operation within an acceptable time. It takes approximately 52 minutes, 12 minutes, and 5 minutes consecutively to determine the maintenance schedules for ship operation intervals of 5 years, 2.5 years, and 1 year.","PeriodicalId":55594,"journal":{"name":"Brodogradnja","volume":null,"pages":null},"PeriodicalIF":3.9000,"publicationDate":"2022-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Brodogradnja","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.21278/brod73302","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MARINE","Score":null,"Total":0}
引用次数: 6
Abstract
Maritime industries are constantly searching for a method to enhance ship efficiency, with increasing concern about the environmental impact and rising fuel prices. Marine biofouling is one of the factors that increase ship fuel consumption. However, removing the fouling of the ship requires effort for hull maintenance. Due to the trade-off between conducting maintenance and performance degradation, this study presents the development of a Model-Driven Decision Support System (MD-DSS) to predict the optimum time for underwater hull cleaning for biofouling management. Five stages (sub-models) are employed to develop a DSS, namely: ship resistance estimation, estimation of additional resistance due to biofouling, an iterative-based method for determining the best time to conduct the hull cleaning, and an analysis report. The implemented algorithm was validated by comparing its result with a manually scheduled maintenance date. The DSS is able to determine the best time (date) for maintenance in all given scenarios. By giving two scenarios of different maintenance costs and different fuel prices, the optimisation results produce the same number of maintenances. Within 60 months, four to five hull cleanings are required. It is also found that when the optimal number of maintenances is known, then increasing this number will not have any impact on reducing the hull cleaning costs because the reduction in fouling does not significantly reduce the costs incurred for maintenance. During several trials of the DSS, it is shown that the system can generate maintenance schedules for different time intervals of ship operation within an acceptable time. It takes approximately 52 minutes, 12 minutes, and 5 minutes consecutively to determine the maintenance schedules for ship operation intervals of 5 years, 2.5 years, and 1 year.
期刊介绍:
The journal is devoted to multidisciplinary researches in the fields of theoretical and experimental naval architecture and oceanology as well as to challenging problems in shipbuilding as well shipping, offshore and related shipbuilding industries worldwide. The aim of the journal is to integrate technical interests in shipbuilding, ocean engineering, sea and ocean shipping, inland navigation and intermodal transportation as well as environmental issues, overall safety, objects for wind, marine and hydrokinetic renewable energy production and sustainable transportation development at seas, oceans and inland waterways in relations to shipbuilding and naval architecture. The journal focuses on hydrodynamics, structures, reliability, materials, construction, design, optimization, production engineering, building and organization of building, project management, repair and maintenance planning, information systems in shipyards, quality assurance as well as outfitting, powering, autonomous marine vehicles, power plants and equipment onboard. Brodogradnja publishes original scientific papers, review papers, preliminary communications and important professional papers relevant in engineering and technology.