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Production Planning and Control of Flooring Using Aggregate Planning Method

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  • Rusindiyanto

Abstract

PT. X a is a private company engaged in the wood processing industry. To avoid production excesses or shortages in the company, production planning using the Aggregate Planning Method can be utilized to meet all consumer demands. The variables used include demand data, production costs, setup costs, and manufacturing time. Through this research, the company can fulfill consumer demands and minimize production costs by implementing aggregate planning. Additionally, the company can forecast future demand, enabling them to anticipate fluctuations in consumer demand. By using aggregate production planning, a total production time of 8657 hours can be scheduled to fulfill a demand of 7121 m3. The cost savings achieved after implementing aggregate planning. The total proposed production cost using aggregate planning is IDR.1.383.921.682 and actual cost is IDR 1.477.900.968. So that the company can save production costs of IDR 93,979,286 or 6.35%. For the total production cost of the upcoming year 2023 by implementing aggregate planning based on the forecasting data, the cost is IDR 1.534.711.812.

Suggested Citation

  • Rusindiyanto, 2023. "Production Planning and Control of Flooring Using Aggregate Planning Method," Technium, Technium Science, vol. 16(1), pages 397-404.
    • Handle: RePEc:tec:techni:v:16:y:2023:i:1:p:397-404
    DOI: 10.47577/technium.v16i.10018
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    References listed on IDEAS

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    1. Gansterer, Margaretha, 2015. "Aggregate planning and forecasting in make-to-order production systems," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 521-528.
    2. Yufu Ning & Na Pang & Xiao Wang, 2019. "An Uncertain Aggregate Production Planning Model Considering Investment in Vegetable Preservation Technology," Mathematical Problems in Engineering, Hindawi, vol. 2019, pages 1-10, June.
    3. Juan Pablo Usuga Cadavid & Samir Lamouri & Bernard Grabot & Robert Pellerin & Arnaud Fortin, 2020. "Machine learning applied in production planning and control: a state-of-the-art in the era of industry 4.0," Journal of Intelligent Manufacturing, Springer, vol. 31(6), pages 1531-1558, August.
    4. Jiewu Leng & Weinan Sha & Zisheng Lin & Jianbo Jing & Qiang Liu & Xin Chen, 2023. "Blockchained smart contract pyramid-driven multi-agent autonomous process control for resilient individualised manufacturing towards Industry 5.0," International Journal of Production Research, Taylor & Francis Journals, vol. 61(13), pages 4302-4321, July.
    5. Demirel, Edil & Özelkan, Ertunga C. & Lim, Churlzu, 2018. "Aggregate planning with Flexibility Requirements Profile," International Journal of Production Economics, Elsevier, vol. 202(C), pages 45-58.
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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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