Supplychainpy is a Python library for supply chain analysis, modelling and simulation. The library assists a workflow that is reliant on Excel and VBA.
From the exploration I did so far, it seems to me that the model and approaches are more optimal in case of a retail scenario, where we have the lead time and other such details, however things get complicated when we try to do it for Manufacture where we also have to take account of raw material availability, lead time for production, order to delivery time, SKU abc_xyz classification as well as material's.
Any thoughts on how to deal with calculating ROP, EOQ in a manufacturing setting.
From the exploration I did so far, it seems to me that the model and approaches are more optimal in case of a retail scenario, where we have the lead time and other such details, however things get complicated when we try to do it for Manufacture where we also have to take account of raw material availability, lead time for production, order to delivery time, SKU abc_xyz classification as well as material's. Any thoughts on how to deal with calculating ROP, EOQ in a manufacturing setting.