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- Title
A Decision Support System for Empty Hopper Car Management.
- Authors
Freeman, Nickolas K.; Narayanan, Arunachalam; Burns, Gary P.
- Abstract
The authors developed a data-driven decision support system to improve a large U.S. chemical manufacturer's management of its inventory of empty hopper cars. The system is providing the company with increased visibility into its supply chain and allowing it to make probabilistic business decisions. Chemical manufacturers in the United States use rail hopper cars to store and transport solid products. Customers also use the producer's hopper cars as storage vessels, holding the car until the contained product is consumed. Uncertainty in customer hold times and transit times makes predicting the return of empty hopper cars to production sites challenging. This prediction difficulty results in increased costs due to the transfer of empty cars to and from external storage yards, and on rare occasions, production curtailment. We develop a data-driven decision support system to improve the management of empty hopper car inventory for a large U.S. chemical manufacturer. The company's previous approach for the described task provides only reasonable estimates for cars that are in transit to the shipping facility. Our decision support system (DSS) provides a rolling forecast for a 40-day planning horizon, which improves daily and cumulative predictions by 57% and 13%, on average, when compared with the previous method. Ultimately, the DSS provides the company with increased visibility into its supply chain and allows it to make probabilistic business decisions while eliminating several data retrieval and manipulation tasks.
- Subjects
UNITED States; CHEMICAL industry; DECISION support systems; MODEL railroad hopper cars; CONSUMERS; SUPPLY chains
- Publication
INFORMS Journal on Applied Analytics, 2019, Vol 49, Issue 3, p173
- ISSN
2644-0865
- Publication type
Article
- DOI
10.1287/inte.2019.0987