Integration model of stock inventory with multi-echelon logistic and predictive maintenance

Ari Agung Prihandoyo, T. Yuri, Romadhani Ardi

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper describes the design model integration between predictive tire scrap and inventory stock with consideration of multi echelon logistics. Cox regression model was used to investigate the relationship between a set of one or more covariates and the hazard rate of tire to predict scraping time of tire. The result of prediction was used to calculate stock in every equipment user, distribution center and factory. Economic Order Quantity was used to calculate stock. This paper adopts the SPSS Modeler based analytical and simulation method to obtain the optimal configurations cost model of maintenance and stock inventory. The equipment and logistics challenges of mining companies provide a real context for the presentation of this research.

Original languageEnglish
Title of host publicationICIBE 2018 - 2018 4th International Conference on Industrial and Business Engineering
PublisherAssociation for Computing Machinery
Pages41-47
Number of pages7
ISBN (Electronic)9781450365574
DOIs
Publication statusPublished - 24 Oct 2018
Event4th International Conference on Industrial and Business Engineering, ICIBE 2018 - Macau, Macao
Duration: 24 Oct 201826 Oct 2018

Publication series

NameACM International Conference Proceeding Series

Conference

Conference4th International Conference on Industrial and Business Engineering, ICIBE 2018
CountryMacao
CityMacau
Period24/10/1826/10/18

Keywords

  • Cox Regression
  • Maintenance and Inventory integration
  • Multi echelon
  • Tire Prediction Scrap

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