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Planning of excavator 320D spare part inventory used ABC-FSN analysis and lot sizing method (Case study: Pt Trakindo Utama Makassar).

Authors :
Muthalib, Irwan Setiawan
Indah, Andi Besse
Asmal, Sapta
Hamzir, Ghinadhiya Zafhira Ramadhini
Source :
AIP Conference Proceedings. 2022, Vol. 2543 Issue 1, p1-7. 7p.
Publication Year :
2022

Abstract

PT Trakindo Utama is Indonesia's official dealer for heavy equipment, machinery, generators, forklifts and Cat parts from Caterpillar. The current problem is the company has used the min-max method in spare part inventory control but stock out often occurs in spare part inventory. Therefore, this research aimed to analyze the spare parts inventory to find out materials that need more supervision in order to minimize the possibility that can harm the company, along with inventory planning to obtain the optimal order quantity to minimize the total inventory cost. This research used ABC-FSN analysis of 167 types of 320D Excavator spare parts. ABC analysis is the classification of inventories based on the money value of the goods to the total annual investment of the stored goods, consisting of class A which is goods that give a high value, class B which is goods that give a medium value and class C which is goods that give a low value. FSN analysis is an inventory classification that groups materials into three categories, namely Fast-moving (F), Slow-moving (S) and Non-Moving (N) (deadstock). Then do the inventory planning for materials that are in the AF category. In inventory planning, demand forecasting and determination of optimal order quantities are made using two lot sizing methods, namely Part Period Balancing (PPB) and Wagner Within Algorithm (AWW).Results from ABC-FSN showed that there are 8 types of spare parts categorized as AF which are materials with high investment levels and fast movements. The lot sizing method gives the result that the PPB method produces a minimum total inventory cost compared to the AWW method. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
0094243X
Volume :
2543
Issue :
1
Database :
Academic Search Index
Journal :
AIP Conference Proceedings
Publication Type :
Conference
Accession number :
160259321
Full Text :
https://doi.org/10.1063/5.0095469