Anticipate maintenance and peaks in the demand at the right time
COSTS & REVENUES
Variability in the demand of final products and planned stoppages for maintenance of production units requires a right production planning to avoid lost sales and delays in the delivery.
Each unit has its own capacity and productivity, in shift or as a continuous process, restricted by calendar constraints (week-ends, inspection, public holidays, etc.).
A unit operates within a list of preset production modes that result in a certain type of product (final or intermediate), with a certain cost and production pace. Our model follows the whole production flow, from the extraction to the delivery.
It takes into account all the production yields and the size distribution of every single product at every step of the process.
The productivity model insures a realistic production per period, including days-off.
The optimization suggests a planning, per production unit, in terms of shifts per period (or tonnes per hour in a period) for all possible production modes.
The model runs on periods of week or month (or a combination of both).
Stocks of intermediate and final products are the buffers that can be used to insure a smooth process and delivery, despite of the variability of the demand and maintenance.
But stocks are constrained by a physical capacity and cause an increase in the total cost (due to handling costs).
A safe stock level is also required to prevent any unplanned stoppage or sudden change in the sales.
Our model uses the different stocks of material, in the limit of their
capacity, to fulfill the demand at the right time.Stock level is the main variable that is used to anticipate maintenance on a production unit or a peak in the demand.
The critical decision is related to how long in advance the stock should be increased.
The model is also challenging the safety stocks, which represent a non-negligible cost.
A cost that should be balanced with the risk of losing sales.
The productivity, yield and cost at a production unit may depend on the type of product that it will process.
There may be many alternative routes to transform the raw material in a final product. In some cases, some production units can be completely by-passed, saving some costs but increasing consequently the downstream costs.
The objective of our model is economic, mixing real cost of production, transport and storage with penalties of unmet demands and under-target stock levels.
The optimization seeks for the minimum overall cost.
The model will consider all the potential routes of production and suggest the cheapest ones.