How a bottling line finds $1.5M in hidden throughput
Two failure modes show identical downtime on the loss report. Fixing the bigger one returns less than it costs, while fixing the smaller one returns 62% more.
Read the worked example →More Salad Dressing Without Another Line
Demand for a national brand of salad dressing is rising. A plant model built from its own downtime records, matched to a year of actual OEE within 1%, finds many small fixes worth many points of OEE. Rebuilt in ReliaSim, it runs roughly 1200× faster.
Fischel & Lange · open access →Growing an Olive Plant’s Output
Sales are rising and the whole crop arrives in six weeks. A full-plant model shows what the plant can handle, and scheduling rules tested in it raise throughput 15% without new equipment.
Olive packer · published paper →Modeling Every Failure Mode at Once
A consumer-products maker with hundreds of failure modes on every line models them all together. Productivity rises up to 44% and savings pass $2 billion, by the company’s figures. It is the approach ReliaSim is built on.
Read the case study →Consolidating a Soap Maker’s Plants Into One
A soap maker is consolidating several plants into one making 300+ products. A whole-plant model shows the planned machine assignments would cause a quality problem, and other routings avoid a $4 million retrofit.
Read the case study →Weighing New Bag Lines Against Overtime
At a specialty chemicals plant, each bag line is tied to one bulk production line. A ten-year model weighs the configurations against overtime, including short-term storage between the two, and turns up low-capital options for growth.
Specialty chemicals · client quote →The Cereal Plant That Runs Its Model Before Every Shift
A major cereal maker’s planners run a model of their make-store-pack plant before each shift to see what could go wrong, and change the plan first. The pieces built for it are standardized as SDI’s Plant Builder library.
Cereal plant · shift model →Sizing Grit Storage Between a Cereal Plant’s Cookers and Ovens
Stabilizing partially cooked corn grit decouples a cereal plant’s cookers from its toasting ovens. The modeled configuration gives 19.8% more effective production in peak periods with no new capacity, and you can run the model in a browser.
Run the simulator yourself →From a Snapshot to a Video
A major food manufacturer moves production decisions from spreadsheets to a dynamic model. It runs six months of data in minutes and returns results in as little as 15. Company-wide, its simulation manager estimates $5 million saved across 40 models.
Food manufacturer · published article →Forecasting New-Vehicle Flow Across a Continental Network
A rail and truck network moving 2.5 million vehicles a year is simulated every week from where every vehicle actually is. One set of recommendations saves $21.7M in carrying costs and cuts transit time 19%.
Vehicle-logistics company · published paper →Postponement: Choosing Where to Pack and Where to Hold Cycle Stock
A consumer goods maker runs bulk on cycles of up to 91 days, then packs it early and allocates it on a forecast. Moving packing downstream pays off for some product categories but not others, and cycle stock belongs at the plants.
Read the case study →Sizing Overseas Capacity Before the Peak Is Known
An electronics maker has to commit overseas component capacity months ahead for a two-year product. A model crosses three capacity levels with three sales outcomes, and even a correct forecast calls for a moderate prebuild at the peak.
Read the case study →A Brewpub Plans Kegging and Bottling
Either new line would overrun the fermenting and serving tanks unless more tank capacity goes in too. The model shows it before the equipment is bought.
Published paper →On attribution
Most of this work predates ReliaSim as a product. Our team did it with the same method ReliaSim now packages, and each page says which tool ran the model. Where an account rests on our project record rather than a published paper, the page says so. We describe each client by its business, not its name. The software in the Sandbox didn’t produce these results. The same method now runs a thousand one-year simulations of the Buffer-Options bottling demo line in about thirty seconds.
Looking for the explanations rather than the examples? Those are in the guides.