Using simulation to assess the reliability of forecasts in high-tech industry

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

Abstract

In a high-tech production environment, capacity investment and production planning are often based on the demand information from manufacturers within a supply chain. A supplier solicits forecast information from a manufacturer, and the manufacturer provides demand forecasts that are updated on a rolling horizon basis. Problems arise with this setup if the manufacturer provides volatile forecast quantities due to the market's fluctuating demand or internal bias. As a result, suppliers' mistrust regarding forecast quantities grows, leading to adjusted production plans based on planners' anecdotal experience. The paper presents a decision model to determine the reliability of forecasts provided by manufacturers to facilitate better production planning. The study also suggests alternate forecasting techniques in case of low reliability. To evaluate the effectiveness of the proposed approach, a simulation study is conducted for different manufacturers and scenarios. Our experiments showed an average cost reduction of 14% across all instances.
Original languageEnglish
Title of host publication2023 Winter Simulation Conference, WSC 2023
EditorsC.G. Corlu, S.R. Hunter, H. Lam, B.S. Onggo, J. Shortle, B. Biller
PublisherInstitute of Electrical and Electronics Engineers
Number of pages12
ISBN (Electronic)979-8-3503-6966-3
DOIs
Publication statusPublished - 31 Jan 2024
Event2023 Winter Simulation Conference - San Antonio, United States
Duration: 10 Dec 202313 Dec 2023
https://meetings.informs.org/wordpress/wsc2023/

Conference

Conference2023 Winter Simulation Conference
Abbreviated titleWSC 2023
Country/TerritoryUnited States
CitySan Antonio
Period10/12/2313/12/23
Internet address

Fingerprint

Dive into the research topics of 'Using simulation to assess the reliability of forecasts in high-tech industry'. Together they form a unique fingerprint.

Cite this