Blog
Insights on production scheduling, lean manufacturing, and manufacturing software from 35+ years of industry experience.
How the platform actually works: scheduling, optimization, the shop floor and ERP data.
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.
Finite vs Infinite Capacity in Practice: What Actually Changes
Finite vs infinite capacity in practice: infinite planning tells you if you are overloaded, finite scheduling tells you when each job actually finishes, with worked numbers.