Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production

Merve Yilmaz; Alptekin Durmuşoğlu

Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production

Abstract

Under increasing competitive pressures and ever-changing global conditions, companies are developing strategies to forecast future trends in order to ensure their long-term sustainability. The most critical tools in these strategies are short- and long-term demand forecasts. Accurate demand forecasting provides a valuable opportunity to minimize future revenue losses, which largely depends on the effective operation of the forecasting system. Based on the forecast results, management plans for future activities are developed, and operating costs are optimized. The plastic packaging industry is highly dynamic and is particularly sensitive to demand uncertainties due to intense competition, changing consumer behavior, and fluctuations in raw material prices. In this context, the accuracy of demand forecasts is critical for the efficient planning of production processes. In this study, the Long Short-Term Memory (LSTM) algorithm, a machine learning-based approach rooted in time series analysis, is used to forecast demand in the plastic packaging industry. Sales volumes of a plastic packaging company were collected every 15 days between January 2015 and December 2024, and 70% of these 240 data points were separated as training data, while 30% were used as test data. Mean Squared Error (MSE), Root Mean Squared Error (RMSE), Mean Absolute Error (MAE), and Mean Absolute Percentage Error (MAPE) metrics were used to evaluate the suitability and performance of the LSTM model for demand forecasting in plastic packaging production. Monthly sales volumes for 2025 were calculated using the forecast model. This research will make significant contributions to critical areas such as optimizing production processes, reducing inventory costs, and increasing customer satisfaction.

Keywords

Project Number

1

References

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Details

Primary Language

English

Subjects

Industrial Engineering

Journal Section

Research Article

Authors

Merve Yilmaz ^*
0009-0004-3514-0043
Türkiye

Alptekin Durmuşoğlu
0000-0001-9800-5747
Türkiye

Publication Date

November 27, 2025

Submission Date

January 7, 2025

Acceptance Date

November 14, 2025

Published in Issue

Year 2025 Volume: 2 Number: 2

IZ

https://izlik.org/JA28YP94YB

Cite

RIS / Bibtex

APA

Yilmaz, M., & Durmuşoğlu, A. (2025). Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production. Natural Sciences and Engineering Bulletin, 2(2), 138-155. https://izlik.org/JA28YP94YB

AMA

1.Yilmaz M, Durmuşoğlu A. Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production. NASE. 2025;2(2):138-155. https://izlik.org/JA28YP94YB

Chicago

Yilmaz, Merve, and Alptekin Durmuşoğlu. 2025. “Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production”. Natural Sciences and Engineering Bulletin 2 (2): 138-55. https://izlik.org/JA28YP94YB.

EndNote

Yilmaz M, Durmuşoğlu A (November 1, 2025) Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production. Natural Sciences and Engineering Bulletin 2 2 138–155.

IEEE

[1]M. Yilmaz and A. Durmuşoğlu, “Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production”, NASE, vol. 2, no. 2, pp. 138–155, Nov. 2025, [Online]. Available: https://izlik.org/JA28YP94YB

ISNAD

Yilmaz, Merve - Durmuşoğlu, Alptekin. “Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production”. Natural Sciences and Engineering Bulletin 2/2 (November 1, 2025): 138-155. https://izlik.org/JA28YP94YB.

JAMA

1.Yilmaz M, Durmuşoğlu A. Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production. NASE. 2025;2:138–155.

MLA

Yilmaz, Merve, and Alptekin Durmuşoğlu. “Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production”. Natural Sciences and Engineering Bulletin, vol. 2, no. 2, Nov. 2025, pp. 138-55, https://izlik.org/JA28YP94YB.

Vancouver

1.Merve Yilmaz, Alptekin Durmuşoğlu. Application of the LSTM Model for Demand Forecasting in Plastic Packaging Production. NASE [Internet]. 2025 Nov. 1;2(2):138-55. Available from: https://izlik.org/JA28YP94YB