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

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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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.

Originele taal-2	Engels
Titel	2023 Winter Simulation Conference, WSC 2023
Redacteuren	C.G. Corlu, S.R. Hunter, H. Lam, B.S. Onggo, J. Shortle, B. Biller
Uitgeverij	Institute of Electrical and Electronics Engineers
Aantal pagina's	12
ISBN van elektronische versie	979-8-3503-6966-3
DOI's	https://doi.org/10.1109/WSC60868.2023.10408324
Status	Gepubliceerd - 31 jan. 2024
Evenement	2023 Winter Simulation Conference - San Antonio, Verenigde Staten van Amerika Duur: 10 dec. 2023 → 13 dec. 2023 https://meetings.informs.org/wordpress/wsc2023/

Congres

Congres	2023 Winter Simulation Conference
Verkorte titel	WSC 2023
Land/Regio	Verenigde Staten van Amerika
Stad	San Antonio
Periode	10/12/23 → 13/12/23
Internet adres	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 (editors), 2023 Winter Simulation Conference, WSC 2023 Artikel 10408324 Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/WSC60868.2023.10408324

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title = "Using simulation to assess the reliability of forecasts in high-tech industry",

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.",

author = "Nataraja, {Bhoomica M.} and Tanmay Aggarwal and Nitish Singh and Adan, {Ivo J.B.F.} and Koen Herps",

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doi = "10.1109/WSC60868.2023.10408324",

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booktitle = "2023 Winter Simulation Conference, WSC 2023",

publisher = "Institute of Electrical and Electronics Engineers",

address = "United States",

note = "2023 Winter Simulation Conference, WSC 2023 ; Conference date: 10-12-2023 Through 13-12-2023",

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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 (uitgave), 2023 Winter Simulation Conference, WSC 2023., 10408324, Institute of Electrical and Electronics Engineers, 2023 Winter Simulation Conference, San Antonio, Texas, Verenigde Staten van Amerika, 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. uitgave / C.G. Corlu; S.R. Hunter; H. Lam; B.S. Onggo; J. Shortle; B. Biller. Institute of Electrical and Electronics Engineers, 2024. 10408324.

Onderzoeksoutput: Hoofdstuk in Boek/Rapport/Congresprocedure › Conferentiebijdrage › Academic › peer review

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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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