Predictive Production Performance
What should we expect from next week's lots?
The manufacturing problem
Purchasing and planning often rely on one standard conversion factor, even though raw material changes across a season. When a late-season lot delivers less than the plan assumed, the shortfall surfaces at the end of the run as a service problem.
What Yieldstem is designed to analyze
Historical performance joined with the characteristics of incoming material, such as soluble solids, moisture, size or defect levels, along with product and line. The output is a range of expected output for a planned lot, with its width tied to how much comparable history exists.
Why it matters operationally
A range is more useful to a planner than a single figure, because it shows how much contingency is warranted. It also separates a confident estimate from one made on an unfamiliar variety or supplier.
The decision it supports
How much raw material to commit against an order, how to sequence lots across lines, and when a lot needs closer attention before it runs.
L-91
Single variety, 13.4 °Bx
16,032 kg
L-92
Late-season fruit, 12.6 °Bx
15,648 kg
L-93
Single variety, 13.1 °Bx
15,912 kg
L-94
New variety mix, little history, 12.9 °Bx
15,792 kg
L-95
Single variety, 13.5 °Bx
16,080 kg
L-94 carries a wider range because comparable history is thin. The range says so instead of presenting false precision.
Start with the problem that costs you most.
Few operations need all of this at once. If one of these questions is already being argued about in your plant, it is a practical place to begin the conversation.