Decision Support System for Railway Spare Parts Inventory Control
Hamdan Kamil Syah (a*) , Pudji Astuti (b*), Winnie Septiani (c*)

a, b, c) Department of Industrial Engineering, Trisakti University

Abstract

Decision making in inventory management plays a very important role on controlling operational cost and production effectiveness inside an industry. Electric rail trains (KRL) as a public transportation in Jabodetabek, requires good maintenance management to maintain operational reliability. In the current management of the KRL maintenance system, fast and accurate decisions on controlling the KRL spare parts inventory are needed so that the maintenance process runs smoothly and minimal operational costs are obtained. This research aims to design a decision support system (DSS) for KRL spare parts inventory control decisions. This research begins with a PIECES (Performance, Information, Economy, Efficiency, Control, Service) analysis to understand system requirements. The designed DSS consists of 4 sub-models, which are 1) spare parts demand forecasting model with Monte Carlo simulation, 2) s & Q parameter calculation model for continuous review system, 3) inventory control scenario evaluation model based on total cost and service level criteria, and 4) decision assessment model with simple additive weighting method. The data required by DSS are spare parts data, spare parts demands, inventory control cost and supplier data. Results of DSS examination on KUR 12313 and KUR 12314 spare parts shows that the system is able to provide decisions in determining needs and ordering spare parts quickly and precisely. In conclusion, the designed DSS can be implemented in the spare parts inventory control system for all types of spare parts in the KRL maintenance process.

Keywords: Decision support system- Inventory control- PIECES analysis- Monte Carlo simulation- Continuous review- Simple additive weighting

Topic: Engineering