Sizing Grit Storage Between a Cereal Plant’s Cookers and Ovens
19.8% More Effective Production at Peak, With No New Cooker or Oven

A food-process technology developer has a patented way to shelf-stabilize partially cooked corn grit, so a cereal plant can store it and flake it later. That means a plant doesn’t have to hold its cookers back to whatever the toasting ovens can take. Before a cereal maker will invest, someone has to size the system: how many off-ramps and on-ramps, and how much storage. SDI and the developer build a discrete-rate model of the process to answer that. The modeled configuration gives 19.8% more effective production during key demand periods, with no new cooking or oven capacity.

The business

A food-process technology developer with a corn grit reconstitution technology, and its cereal-maker customers

The question

How should the off-ramp, storage and on-ramp be sized, and what is the system worth?

The model

Cooking, grit stabilization, in-process storage and reconstitution, run over a year of production

What it is worth

19.8% more effective production in key demand periods, from one off-ramp and one on-ramp

Source

SDI project record · live model you can run

What the plant is up against

In flaked-cereal production, corn grits are cooked, dried, flaked and toasted, then packed. Those stages are physically tied together. If the toasting ovens can’t take what the cooker is making, the cooker slows down. During peak demand that costs real output on equipment the plant has already paid for.

The usual fixes all take capital. A plant can add oven capacity, add a cooker, or add conventional wet storage. For a partially cooked product, wet storage brings a shelf-life problem of its own.

The technology the developer brings

The developer holds patented technology that shelf-stabilizes partially cooked corn grit. Processing can pick up later, even at a different location. Picking the grit back up is called reconstitution. In the plant it works in three stages:

• Off-ramp. Excess production goes to a dryer that stabilizes the grit to roughly 10–11% moisture.
• Store. The stabilized grit goes into totes. At this point the two halves of the line are decoupled.
• On-ramp. When oven capacity frees up, a module reconstitutes the stored grit and feeds it back into production.

The developer sees this as a way for cereal makers to find more production capacity without building it, with possible savings in the tens of millions of dollars across the industry. Customers need to see what it means for their own plants first.

Why sizing it needs a model

Intuition can’t answer the sizing questions. Run the off-ramp too eagerly and the plant pays to dry grit the ovens could have taken anyway. Run it too cautiously and the cooker still throttles. The right size depends on how the demand pattern, the changeover schedule and the reliability of both halves of the line play out together over a full year.

How it is modeled

SDI and the developer build a discrete-rate simulation of the process and wrap it in a web application. The app uses the plant’s terms, not the simulator’s. Its inputs cover cooking, grit stabilization for off-ramping, in-process grit storage, and reconstitution and on-ramping. Its results show what each configuration does to inventory and production capacity.

What the model shows

The modeled configuration has one off-ramp and one on-ramp, with no new cooker or oven capacity. It gives 19.8% more effective production during key demand periods. Running the simulation across a range of conditions shows the throughput gain can be reached with high confidence.

The 19.8% is a peak-period figure, not an annual average. Decoupling pays when the line is demand-constrained and the cookers and ovens disagree. In a slack period there’s nothing to store and nothing to recover.

What changes

The model lets the developer design and size the system to run over a range of conditions before a customer commits. The developer then uses the cloud version to explore the options with customers, on their own production data. Neither side has to be a simulation modeler.

The model is live. The Decoupling System Simulator runs in a browser, and you can set the configuration and run annual production scenarios yourself.

Where this work comes from

Built by Simulation Dynamics, the team behind ReliaSim®, with the technology developer, as a web application on the ReliaSim discrete-rate engine · evidence: SDI project record and the live model.