Mathematical models for orders forecasting and management and big data analysis for orders pre-configuration
Project identification number:
Order-to-Delivery process entails all the activities from the recognition of a customer need to the delivery of the product to the customer (need satisfaction). The efficient management of the OTD process has to trade-off the lead time reduction and the production resource saturation, and this is a rather complex problem especially in multi-product environments. The trade-off between a small lead time and an efficient use of the production resources stem from the fact that while the lead time perspective only considers customer orders (received or expected), the production resources perspective must take into account also how and where product are processed. In particular, plant saturation is usually an indication of efficiency and a good saturation is usually defined as being not too small (for the economical point of view of the investment for building the plant) but also not too large (leading to large lad time due to the well-known Little’s law). An appropriate saturation can be achieved by loading the various line of a plant in a proper way, i.e., by realising in production a correct mix of products. The objective of the research activity is the development of mathematical models, based on predictive algorithms, to support the definition and the management of orders through the OTD process. In practice, using both demand forecast and order received for the various product and all the information related to market margins, configuration grids and both make/buy and process capacity, the models aim at optimizing plant load in term of utilization but without neglecting the lead time dimension. Also, inventory levels (with respect to the different products and their market) have to be considered to avoid building inventories that will be hardly absorbed by the market demand just to increase the plant saturation.
- Massimo Poncino. (Responsabile Scientifico)
|Total cost:||€ 24,450.00|
|Total contribution:||€ 24,450.00|
|PoliTo total cost:||€ 24,450.00|
|PoliTo contribution:||€ 24,450.00|