To begin with, it’s too complex. Take a look at a typical routing detail for a labor step in your ERP or MES system. In the accompanying example, each of the following fields must be completed with reasonable accuracy for every routing step in order for the AP&S to even calculate a schedule that has any hope of being correct—and, even then, it is only correct in theory:
- Move Hours
- Queue Hours
- Set Up Hours
- Reset Hours
- Pieces before Reset
- Scrap Pieces
- Scrap Percent
- Efficiency Rate
There are a several of problems with this data hygiene requirement:
- Most companies do not know what most of these various values should be with any reasonable accuracy.
- In most companies, their processes are not standardized enough, so set-up times, run times, move times, queue times and efficiencies are statistically out of control. No matter what times they choose to put into these fields, the actual performance times will vary wildly, so the schedule will not hold in any event.
- People who work in production already know that any schedule produced by the system will be incorrect (when compared to reality) and out-of-date before it can even reach the shop floor.
Because of the inherent complexity, massive data dependency, out-of-control processes, and invalid base data being fed into the system, fewer than five (5) percent of companies that buy traditional AP&S systems actually implement and use them. This holds true whether they have purchased from Sage, JD Edwards, SAP or any other traditional AP&S system.
Some of the roughly five percent that do implement them, do so because executive management has insisted by saying something like, “Look! We’ve spent tens of thousands of dollars to buy this system to help make our operations better. You are going to use it.”
As a result, in a good many companies, the AP&S system is, in fact, run every day and the reports dutifully produced. Nevertheless, the shop floor is still managed the same way it was before they purchase the AP&S system—largely by the seat of the pants, best guesses and massive expediting efforts. Flow is not positively affected in any way.
Since the “Clairvoyance” component of AP&S systems is “still in development” and is not likely to see the light of day anytime soon, there is no AP&S system that can adjust the schedule because Jane got sick and left 3.3 hours early from her post on the shop floor, and Ron had a fight with his teenage son last night and is only operating at 47.4 percent efficiency today.
Equally as important, three different people in the same company, looking at data streaming from an AP&S system, may very easily have three different opinions as to what should be the “top priority” at any given work center. This is because, apart from calculated schedule start-times (which are likely to be wrong relative to reality anyway), the AP&S system has no clear way to communicate production priorities. There is no single signal that indicates priorities properly.
Due-dates are generally not a good signal for priorities.
Because, AP&S calculated due-dates do not necessarily tell you which shipments to customers may be jeopardized (or in jeopardy already) by a decision made at Work Center X on Item ID ‘ABC’.
Companies with AP&S systems are just as likely to have one or more staff expeditors whose full-time jobs amount to 1) spending half their days trying to figure out the priorities are, and 2) spending the other half the day figuring out where to “break the schedule” that their expensive and costly-to-run AP&S system created for them.
There are far, far better—non-traditional—ways to determine what should be made when, and to set effective priorities on the shop floor. But, that discussion will have to wait for another day.
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