Solving the Task Allocation Problem for Multiple Lasers

When many laser machines are running at the same time, conflicts in task allocation can cause a drop in efficiency.It provides three practical methods: prioritization, dynamic strategy adjustment, and intelligent algorithm assistance. These methods help users quickly resolve conflicts over task assignment, optimize equipment scheduling, and reduce production wait times.

Why is your laser machine always fighting?

Many of my friends told me that when several laser machines were working together, they often "fought" over jobs, either repeating the same job or sitting idle waiting for instructions.In fact, the problem usually lies in the logic of task allocation.Below we'll talk about how to use three techniques to straighten out this problem.

First, prioritize your tasks.

First, you must understand the rhythm of your work.

For example, if there are rush orders, or thicker boards to cut, or complicated graphics to carve, it would be advisable to set a special priority for these tasks.In practice, you can add a symbol (such as "#urgent" or "#routine") to the name of the task, and the system will automatically sort the tasks accordingly.

A golden combination at a fixed time period.

The morning shift deals with overnight urgent jobs, and the noon shift handles regular work in bulk.My own experience is that by grouping the work according to type, and matching it to the strengths of each machine (for example, one machine is good at cutting thin sheets), you can reduce conflicts by more than 40 %.

The second step was to teach the machines to "sew in the gaps.

Setting up flexible buffer zones.

Don't schedule the machines too tightly. Leave 15-20 minutes of buffer time for each machine.I've come across cases where a factory didn't leave any buffer time, so when a machine finished its current task it had to wait for half an hour for new instructions.

The secret of dynamic adjustment.

I recommend using a Kanban system, which displays tasks that are "pending," "underway," and "completed" on a screen.When a machine finishes a task, the next job is assigned to it 30 seconds in advance, just as a restaurant waiter keeps an eye on the progress of diners so he can bring them the next course at the proper time.

The third step: Get an "intelligent butler" to help.

Recommendations for beginners.

If your budget is limited, you can try open source tools like TaskRouter.It can automatically allocate tasks according to machine status, and can also produce daily efficiency reports.I installed one for a friend last week, and he says he can complete two more orders before quitting time now.

Hidden functions.

Some laser cutting systems, for example, have built-in conflict detection modules.It is important to make sure that the "anti-collision" option has been enabled. This function is unknown to many old hands who are wasting a ready-made solution.

Where is the boundary between human and machine?

Although the intelligence systems are very useful, in a crisis it is still the people who have to make the decisions.For example, if a shortage of materials occurs, the system may still be sending orders based on the original plan, and manual intervention is needed to adjust the situation.Remember: the computer is an aid to decision making, not a substitute for human judgment.