Blog
Insights on production scheduling, lean manufacturing, and manufacturing software from 35+ years of industry experience.
Everything we have published.
How Sequence-Dependent Setup Shapes a Schedule
How EDGEBIC uses a per-machine setup matrix to price changeovers by what ran before, turning a deceptive plan into an honest one and an honest one into an efficient one.
How Transit Time Between Plants Affects a Schedule
How EDGEBIC models the days a job spends leaving the building: calendar-day versus working-day transit, and how it composes with queue time and lot streaming.
Load Balancing vs Dedicated Instance Scheduling
Load balancing vs dedicated instance scheduling: how a finite capacity engine splits work across machines, when one job per instance wins, and worked numbers.
Piece Count vs Time Lag Lot Streaming: Which to Use
Piece count vs time lag lot streaming: when to overlap operations by transfer batch pieces, when a start-to-start hour lag fits, and worked numbers.
Push vs Pull Scheduling in a Finite Capacity System
Push vs pull scheduling in a finite capacity system: forward start-as-soon-as-possible against backward JIT right-alignment, the trade-off, and worked dates.
What the Never-Worse Guarantee Means for Planners
Why running the EDGEBIC optimizer is risk-free: the clamp that compares every candidate plan against your baseline and returns the baseline unless the candidate is strictly better.
When to Use a Machine Pool vs an Alternate Work Center
Machine pool vs alternate work center: when a reusable work center group beats a per-step alternate list, how each picks a machine, and worked numbers.
Why a Scheduler Searches Forward in Time for Capacity
Why finite capacity scheduling walks the calendar day by day instead of assuming a machine is free: how EDGEBIC finds the next real slot and what a forward search guarantees.
Why Schedule Stability Can Beat Schedule Optimality
Why schedule stability can beat schedule optimality: how nervousness erodes floor trust, when to freeze the near term, and how to weigh stability against gains.