Framework for predictive sales and demand planning in customer-oriented manufacturing systems using data enrichment and machine learning
- Publisher:
- Elsevier
- Publication Type:
- Journal Article
- Citation:
- Procedia CIRP, 2023, 120, pp. 1107-1112
- Issue Date:
- 2023
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Companies with Make to Order MTO manufacturing have always faced the conflict of meeting a large volume of individual customer orders on time while remaining as flexible as possible Unlike Make to Stock MTS manufacturing planning the production requirements for MTO is a challenging task since incoming orders may vary in time and quantity while also being subject to a number of variables In some cases the delivery time allocated by the customer can be less than the required Order Lead Time to fulfil the order Manufacturers can respond to this with either with approached from production management or from data science This paper presents a framework to leverage the benefit of both domains We conduct a literature review and present the results of an expert workshop We propose criteria for a suitable data enrichment and the application of Machine Learning ML methods in sales and demand forecasting In conclusion the proposed framework helps to equip manufacturing companies with a structured strategy for data management and to utilize the benefit of ML for sales and demand forecasting
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