Blog
Insights on production scheduling, lean manufacturing, and manufacturing software from 35+ years of industry experience.
Everything we have published.
How a Scheduler Absorbs a Rush Order Without Wrecking the Plan
A finite capacity scheduler slots a rush order in by priority, preserves started and completed work, and reflows only the unstarted future, so you see exactly which jobs slip.
How a Scheduler Decides When to Start a Job
How a finite capacity scheduler sets each operation's start time: the later of release and prerequisite end, then a forward search for real capacity, with numbers.
How a Scheduler Handles a Shared Tool or Fixture
How to schedule a shared fixture, die, or mold in a finite capacity plan: give the tool a quantity, require it on the routing step, and let contention across every machine become real.
How a Scheduler Thinks About a Week vs a Day
A finite capacity scheduler treats the near term as executable and the far term as directional. Here is how horizon and granularity change what a plan is really for.
How One Late Operation Ripples Through a Job
When one operation runs late, a finite capacity scheduler cascades the delay forward only: downstream steps shift, upstream and completed steps stay, and joins wait for the latest input.
The Cost of an Unrealistic Due Date
An unrealistic due date does not make a job faster; a finite capacity scheduler shows the honest late finish instead. Here is what a bad promise really costs and why the plan tells the truth.
The Planner's Role When the Software Does the Scheduling
When a finite capacity engine places every operation, the planner's job shifts to intent, master data, exceptions, and judgment. Here is what the human still owns.
Why a Good Schedule Is Boring
A good production schedule is boring on purpose: predictable, stable, and quiet. Here is why low drama beats constant reshuffling, with the mechanisms that keep it calm.
Why Queue Time Is Not Wasted Time
Planned queue time in a routing is a protective buffer, not waste. Here is how a shift-aware queue absorbs variation, and how it differs from the WIP queue you want to cut.
Batch Size vs Flow Time: The Transfer Batch Trade-Off
Batch size vs flow time: a smaller transfer batch lets the next operation start sooner and shrinks makespan, at the cost of more handoffs, with worked lot-streaming numbers.
Dedicated Cells vs Shared Work Centers
Dedicated cells vs shared work centers: a cell cuts queue and transit for one product family, a shared functional layout raises utilization but adds contention, with numbers.
How EDGEBIC Switches Between Finite and Infinite Capacity
Where EDGEBIC by User Solutions runs finite, where it runs infinite, and the three settings that move a job between them, with worked numbers.