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.
Hours-Based vs Piece-Based Capacity Modeling
Hours-based vs piece-based capacity modeling: when to size a work center by time, when by output rate, when by both, and worked capacity numbers.
How a Frozen Routing Snapshot Protects a Running Job
Why EDGEBIC saves an exact copy of the routing each job was scheduled with, so a mid-order engineering change never silently re-routes an operator's remaining steps.
How a Quote Simulation Produces a Realistic Date
Why an EDGEBIC quote date holds up: the simulation borrows the live scheduling engine, runs against real capacity in memory, writes nothing, and reports the same date the real run gives.
How a Schedule Accounts for Holidays and Downtime
How EDGEBIC turns shifts, three levels of holidays, downtime windows, and capacity overrides into the effective hours a work center has on any given day.
How a Scheduler Decides Which Job Runs First
How a scheduler decides which job runs first: the priority, start date, due date sort, deterministic tie-breaking, and how dispatch rules fit in, with worked numbers.
How a Scheduler Nets Demand Against Inventory
How EDGEBIC checks on-hand stock before it schedules a build: the append-only ledger, consume-from-stock netting, and how it avoids double-allocating the same units.
How a Scheduler Preserves Completed Work
Why a reschedule in EDGEBIC never moves finished operations: the three-zone model that freezes completed work, forward-shifts partial work, and re-plans only what has not started.
How a Scheduler Recovers From a Mid-Shift Disruption
How a scheduler recovers from a mid-shift disruption: the three zones of a reschedule, why completed work never moves, and worked reschedule numbers.
How Finite Capacity Scheduling Handles a Shared Bottleneck
How finite capacity scheduling handles a shared bottleneck: why the constraint runs one job at a time, how load factor finds it, and how jobs queue, with numbers.
How Mathematical Optimization Improves a Schedule
How EDGEBIC searches for a better job order: a multi-run heuristic layer guaranteed never worse than the baseline, and a CP-SAT solver that reports a proven optimality gap.
How Multi-Shift Allocation Fills Capacity
How EDGEBIC spreads one operation across shifts, days, and machine instances: the per-shift capacity bucket, the priority search, and the three ways it splits work.
How Operator Skills Constrain a Schedule
How EDGEBIC adds people as a second finite resource: a per-operator hours ledger that stops one certified welder from being scheduled on five machines at once.