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 Time Series Production Process Problem
Hi there

Here's a time series problem I need advice on please.

A manufacturing house manufactures 3 types of drinks A, B and C. The manufacturing is a 4 stages process: S1 (2 hrs), S2 (28 days), S3 (14 days) and S4 (4 hrs). S1, S2 and S3 require distinct manufacturing equipment. There are 10 manufacturing equipment of varying sizes available. Equip1 can only be used for S1, whereas remaining equipment can be used for either S2 or S3.

Equip1 (5000 Litre)
Equip2 (900 Litre)
Equip3 (700 Litre)
Equip4 (900 Litre)
Equip5 (800 Litre)
Equip6 (600 Litre)
Equip7 (900 Litre)
Equip8 (700 Litre)
Equip9 (700 Litre)
Equip10 (800 Litre)

Data available: Last year's data in the following shape
Invoice Num| Customer| Date Required | Quantity Ordered| Batch Id

Other data structures created to aid programming of scenario:
1) A config table managing availability of equipment
2) Inventory data structure

1) Write a function to predict demand (for a month/year in the future)
2) Write an algorithm which decides what drink type is produced next given available equipment and based on predicted demand.

I'm very new to data science and wanted to know if this a typical scenario with possible fixed approaches. Is this a multivariate time series problem? Are there any examples available to tackle it?

Would appreciate help and direction

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