Research Article
Inventory Optimization for A Case Study of the Textile Supply Chain in Indonesia Using Anylogistix
@INPROCEEDINGS{10.4108/eai.21-9-2023.2347046, author={Yelita Anggiane Iskandar and Nur Layli Rachmawati and Adji Candra Kurniawan and Daniel Fetrick Jeremias Hatorangan Sarumpaet and Evelyn Sandy Tao A and Monica Ayu Sevita and Rihot Gusron Rifaldy and Risa Febrianti and Sesilia Eka Christina}, title={Inventory Optimization for A Case Study of the Textile Supply Chain in Indonesia Using Anylogistix}, proceedings={Proceedings of the 2nd International Conference on Contemporary Risk Studies, ICONIC-RS 2023, 21-22 September 2023, Bali, Indonesia}, publisher={EAI}, proceedings_a={ICONIC-RS}, year={2024}, month={6}, keywords={textile supply chain inventory management discrete event simulation anylogistix}, doi={10.4108/eai.21-9-2023.2347046} }- Yelita Anggiane Iskandar
Nur Layli Rachmawati
Adji Candra Kurniawan
Daniel Fetrick Jeremias Hatorangan Sarumpaet
Evelyn Sandy Tao A
Monica Ayu Sevita
Rihot Gusron Rifaldy
Risa Febrianti
Sesilia Eka Christina
Year: 2024
Inventory Optimization for A Case Study of the Textile Supply Chain in Indonesia Using Anylogistix
ICONIC-RS
EAI
DOI: 10.4108/eai.21-9-2023.2347046
Abstract
Optimizing inventory involves achieving the ideal supply and demand balance. One way to lower the risk of typical inventory difficulties, such as out-of-stock products and excessive storage costs, is to optimize inventory levels. Popular apparel manufacturers are at the downstream end of a long and complicated textile supply chain facing challenges like fierce competition as the products have many substitutes. Therefore the undisrupted supply of finished products, the clothes, should be maintained to ensure the company’s sustainability. It can be attained by administering the integrated inventory from 1st tier suppliers to customers. Considering the variability and dynamic environment of the supply chain, we propose a discrete event simulation using Anylogistix to have the best inventory control. Incorporating 4 scenarios related to a varied set of initial stock, storage policy, and production speed, we found that the 4th scenario gives the best result, yielding the highest profit.
