Learn

Each page here teaches discrete-event simulation (DES), and how desflow does it, to a reader new to both. What Is DES? explains the idea with no maths. The tutorial then builds one model of a packing shop through a whole study, so read its pages in order. The Simulation Concepts pages explain the theory behind the tutorial's steps. Read them after the tutorial, or when a tutorial page links to one, because they use results from its later pages. If you already know SimPy, start with Coming from SimPy. To look up one part of desflow, see the User Guide. To do one task step by step, see How-To.

Tutorial

Group	What it covers
What Is DES?	what a discrete-event simulation is, and how it plays out a system one event at a time, with no maths
Tutorial: A First Model	a first model of the shop: how many packers it needs, random times and seeds, what a run measures and how a run ends
Tutorial: Inputs	packing times chosen and fitted from measured data, demand that changes through the day, and a recorded morning replayed
Tutorial: Shop Logic	stock, priorities, a flow of tasks, waits for signals, patience, interruptions, competing resources and filtered inventory
Tutorial: Studies	how many runs to trust, comparing designs, parameter sweeps, checking a model, and a complete study from data to recommendation
Tutorial: Running Live	parameters changed while the model runs, and records streamed out to files

Simulation Concepts

Group	What it covers
Queueing Basics	the results of queueing theory that a study uses: utilisation, Little's law, the effect of variation and the bottleneck
A Simulation Study	every step of a study, from the question to the report
Checking and Validating	verification, whether the program does what the model on paper says, and validation, whether the model is close enough to the real system
Output Analysis	how runs become an answer with a stated precision: replications, warm-up, intervals and comparing designs
Readiness and Reporting	what a model needs before someone else can trust and repeat it, with the published checklists
Common Mistakes	eight mistakes that give wrong results, in the order they happen in a study