How Independent Parallel Splits a Job Across Machines

Independent-parallel scheduling is how EDGEBIC by User Solutions runs several machines on one operation at the same time to finish it faster. The engine searches for a window where every machine in the group can start together, then schedules each machine independently against its own capacity, splitting the work so the operation completes in a fraction of the single-machine time. Unlike mirroring, where partner machines copy a parent's timing and skip the capacity check, independent parallel treats each machine as a real, finite resource: the work is shared, but every hour is genuinely reserved.

This is the tool for the situation "I have three assembly lines and one big job, and I want them all on it." It is about throughput, and it comes with one firm rule: the machines start together or not at all.

Sharing an operation across real machines

A routing step configured as independent parallel lists a primary work center and one or more partners, each marked as consuming finite capacity. That marking is the whole distinction: it tells the engine these machines each do separate, real work, so each one must pass a capacity check and consume the hours it uses.

Because the machines share one operation, they should also share a start. The engine does not let one machine begin the work while another lags behind; a staggered start would make the split uneven and the finish unpredictable. Instead it looks for a single moment when all the machines can begin together, commits every machine to that moment, and lets each one run its share against its own shift.

The payoff is elapsed time. An operation that would take a long single-machine span is divided across the group and completes when the machines finish their shares, which, on evenly matched machines, is roughly the single-machine time divided by the number of machines.

Finding a moment they can all start

The heart of independent parallel is the search for a shared start. The engine walks the calendar forward from the operation's earliest start, and on each day it looks for a shift that all the machines have in common. A date where the machines share no common shift is skipped, because there is no moment when they could all be running.

For each candidate date and shift, the engine applies four checks, and all four must pass for every machine before the shared start is accepted:

• Individual capacity. Each machine has spare hours available from the proposed start time.
• Simultaneous start. The proposed start falls inside every machine's shift window, with no existing booking blocking that exact moment.
• Instance conflicts. Each machine has enough physical instances, and no instance is double-booked across the group.
• Continuous capacity. There are no gaps between the shared start and the projected finish that would fragment the run.

If any check fails for any machine, the whole candidate is rejected and the search advances to the next shift or the next day. This is the all-or-nothing rule made concrete: the group only starts when every machine can honestly start together.

A worked example: two lines on one operation

Take an assembly step configured as independent parallel, with two identical lines, each on an 8-hour day shift. The operation needs 16 hours of work and can start Monday.

The engine searches for a shared start. Monday's day shift is common to both lines, both have their full 8 hours free, the start at 08:00 fits both shifts, there are no instance conflicts, and the capacity is continuous. All four checks pass, so Monday 08:00 is the shared start.

Now each line is scheduled independently for its share. Sixteen hours of work split across two lines is 8 hours each, and each line runs Monday 08:00 to 16:00. Both lines' 8 hours are checked against and consumed from their own capacity buckets, so nothing is double-booked. The operation completes at the end of Monday's day shift, instead of stretching two days on a single line. Throughput on that step effectively doubled.

Now change one thing: one line is down for maintenance Monday and Tuesday. The engine tests Monday and fails the capacity check for the down line, tests Tuesday and fails again, and only on Wednesday, when both lines are free, does it find a shared start. All the work then runs Wednesday. The group waited rather than letting one line start alone, because a synchronized shared start is the guarantee independent parallel exists to provide.

Independent parallel versus the alternatives

The decision that trips people up is independent parallel versus an alternate work center. They look similar because both involve more than one machine, but they answer different questions.

Independent parallel means "run this operation on all these machines at once to go faster." It requires the machines together and consumes each one's capacity. Use it when splitting the work is the goal and coordinating a shared start is acceptable.

An alternate work center means "run this operation on whichever of these machines can do it soonest." The engine picks a single winner before scheduling and does not require simultaneity. Use it for flexibility and resilience, when you want the job to route to an open machine rather than wait for a whole group.

And dependent parallel is the third relative: machines physically coupled in one setup, where partners mirror the parent's timing and skip the capacity check. The full comparison lives in dependent versus independent parallel.

All of these sit inside the broader pipeline described in the scheduling engine guide. Each machine in an independent-parallel group is placed by the same multi-shift allocation that handles single machines, and the whole idea only works because the engine treats capacity as genuinely finite.

To see how splitting an operation across your machines shortens its span, bring your data to a demo and watch the shared-start search on your real shifts.