AggFlow Production Scheduler

All aggregate producers must plan production to some degree. But how thorough are their methods, and how accurate are their plans? Because different plants can make products in different combinations and at different rates, operations need to have a plan to match production to their sales volumes.

The goal, of course, is to schedule production based on a sales forecast – so as to meet sales demands within scheduled hours. In order to make a profit, producers must reduce costs, waste, byproducts and unsalable inventory, while they produce the best mix of all salable products – and sell what they produce.

Producers use a range of production scheduling practices.

Some producers schedule production based on the best-guess approach, and then see if there are profits down the road. With this style of scheduling, inventory levels become a problem that lead to re-handling costs. There is contamination risk in handling excess inventory, and producers often experience shortfalls of certain products. The result is that the operation is ultimately driven by daily sales demands – forcing the operation to run extra hours of overtime to meet those demands.

Other producers will tour their plants and visually size up the stockpiles. If a pile is low, they switch to a different operating mode to produce more; if a pile is high, they cut back on production of that product. This is a short-term, reactive approach that doesn’t consider future sales fluctuations or allow for other activities, such as plant maintenance.
A better, but by no means ideal production scheduling method often used involves the use of Microsoft Excel spreadsheets, where the producer enters possible production schedules against a sales forecast. Using formulas in the spreadsheet, if a cell turns red, the plant has not made enough of that product and inventory shortfalls are expected.

The user must repeatedly enter different production hours until the amount of red cells is minimized. These spreadsheet methods do not result in the optimum solution of production scheduling to a sales forecast.

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Source: Pit & Quarry Magazine