Title :
Research on Ship Spare Parts Inventory Based on Selective Maintenance
Author :
Zhou, Bin ; Fan, Shidong ; Da Li
Author_Institution :
Sch. of Energy & Power Eng., Wuhan Univ. of Technol., Wuhan, China
Abstract :
According to selective maintenance theory, this paper attempts to discuss the ship spare parts inventory based on different maintenance models to minimize cost of the spare parts in the context of safe operation of the ship. For the equipment which adopts corrective maintenance, a multi-period stochastic storage model strategy is applied to solve the optimal inventory. Then, this paper take a certain time, periodic interval and lead time into account to obtain the best inventory for the equipments of periodical maintenance. The last, the grey prediction method is utilized to the equipment of condition-based maintenance in order to solve the best inventory.
Keywords :
grey systems; maintenance engineering; ships; stochastic processes; stock control; grey prediction method; multi-period stochastic storage model strategy; selective maintenance theory; ship spare parts inventory; Context modeling; Costs; Defense industry; Maintenance; Marine safety; Marine vehicles; Metals industry; Power engineering and energy; Prediction methods; Stochastic processes;
Conference_Titel :
Intelligent Systems and Applications (ISA), 2010 2nd International Workshop on
Conference_Location :
Wuhan
Print_ISBN :
978-1-4244-5872-1
Electronic_ISBN :
978-1-4244-5874-5
DOI :
10.1109/IWISA.2010.5473709