Bazan Flores, E.P:; Fe Gamarra, C.M.; Taquía Gutiérrez, J.A.; García López, Y.J.: Demand Forecast Model and Route Optimization to Improve the Supply of an SME in the Bakery Sector. In: Herberger, D.; Hübner, M. (Eds.): Proceedings of the Conference on Production Systems and Logistics: CPSL 2023 - 2. Hannover : publish-Ing., 2023, S. 957-967. DOI:
https://doi.org/10.15488/15321
Zusammenfassung: |
This research employs the Lean Six Sigma DMAIC methodology to address enhancing product distribution efficiency in a bakery chain. Following the diagnostic phase, demand forecasting models were developed using ARIMA and Holt Winter methods, with ARIMA demonstrating higher prediction accuracy. Furthermore, route mapping was conducted using the Clark-Wright algorithm. Key performance indicators (KPIs) such as delivery time, distance traveled, and MAPE (Mean Absolute Percentage Error) will be established for process control. Implementing these improvements aims to achieve more efficient product distribution management within the bakery chain
|
Lizenzbestimmungen: |
CC BY 3.0 DE - https://creativecommons.org/licenses/by/3.0/de/deed.de
|
Publikationstyp: |
BookPart |
Publikationsstatus: |
publishedVersion |
Erstveröffentlichung: |
2023 |
Schlagwörter (englisch): |
Supply Management Improvement, Demand Forecasting, Clark-Wright, Route Optimization, ARIMA
|
Fachliche Zuordnung (DDC): |
620 | Ingenieurwissenschaften und Maschinenbau
|
Kontrollierte Schlagwörter: |
Konferenzschrift
|