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

Bhoomica M. Nataraja; Tanmay Aggarwal; Nitish Singh; Ivo J.B.F. Adan; Koen Herps

doi:10.1109/WSC60868.2023.10408324

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

Bhoomica M. Nataraja, Tanmay Aggarwal, Nitish Singh, Ivo J.B.F. Adan, Koen Herps

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Citation (Scopus)

17 Downloads (Pure)

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 language	English
Title of host publication	2023 Winter Simulation Conference, WSC 2023
Editors	C.G. Corlu, S.R. Hunter, H. Lam, B.S. Onggo, J. Shortle, B. Biller
Publisher	Institute of Electrical and Electronics Engineers
Number of pages	12
ISBN (Electronic)	979-8-3503-6966-3
DOIs	https://doi.org/10.1109/WSC60868.2023.10408324
Publication status	Published - 31 Jan 2024
Event	2023 Winter Simulation Conference - San Antonio, United States Duration: 10 Dec 2023 → 13 Dec 2023 https://meetings.informs.org/wordpress/wsc2023/

Conference

Conference	2023 Winter Simulation Conference
Abbreviated title	WSC 2023
Country/Territory	United States
City	San Antonio
Period	10/12/23 → 13/12/23
Internet address	https://meetings.informs.org/wordpress/wsc2023/

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10.1109/WSC60868.2023.10408324

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Nataraja, B. M., Aggarwal, T., Singh, N., Adan, I. J. B. F., & Herps, K. (2024). Using simulation to assess the reliability of forecasts in high-tech industry. In C. G. Corlu, S. R. Hunter, H. Lam, B. S. Onggo, J. Shortle, & B. Biller (Eds.), 2023 Winter Simulation Conference, WSC 2023 Article 10408324 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/WSC60868.2023.10408324

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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.",

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Nataraja, BM, Aggarwal, T, Singh, N , Adan, IJBF & Herps, K 2024, Using simulation to assess the reliability of forecasts in high-tech industry. in CG Corlu, SR Hunter, H Lam, BS Onggo, J Shortle & B Biller (eds), 2023 Winter Simulation Conference, WSC 2023., 10408324, Institute of Electrical and Electronics Engineers, 2023 Winter Simulation Conference, San Antonio, Texas, United States, 10/12/23. https://doi.org/10.1109/WSC60868.2023.10408324

Using simulation to assess the reliability of forecasts in high-tech industry. / Nataraja, Bhoomica M.; Aggarwal, Tanmay; Singh, Nitish et al.
2023 Winter Simulation Conference, WSC 2023. ed. / C.G. Corlu; S.R. Hunter; H. Lam; B.S. Onggo; J. Shortle; B. Biller. Institute of Electrical and Electronics Engineers, 2024. 10408324.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Using simulation to assess the reliability of forecasts in high-tech industry

AU - Nataraja, Bhoomica M.

AU - Aggarwal, Tanmay

AU - Singh, Nitish

AU - Adan, Ivo J.B.F.

AU - Herps, Koen

PY - 2024/1/31

Y1 - 2024/1/31

N2 - 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.

AB - 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.

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DO - 10.1109/WSC60868.2023.10408324

M3 - Conference contribution

BT - 2023 Winter Simulation Conference, WSC 2023

A2 - Corlu, C.G.

A2 - Hunter, S.R.

A2 - Lam, H.

A2 - Onggo, B.S.

A2 - Shortle, J.

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PB - Institute of Electrical and Electronics Engineers

T2 - 2023 Winter Simulation Conference

Y2 - 10 December 2023 through 13 December 2023

ER -

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

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