Scrutinizing high scrap jobs. (Small Foundry Management).

Why is scrap so high?

I'll bet there isn't a day that goes by when some foundry manager doesn't ask that question. I'll also bet that the answer he receives is, "We were running jobs that always have high scrap" or some equivalent.

It's a frustrating exchange for managers. They really want to chew out some employees because they're upset about the answer, but they also realize that some jobs just have high scrap. The high scrap jobs most likely push the envelope of the foundry's capability. If enough high scrap jobs run at the same time, higher scrap totals are expected.

Managing "Tough Jobs"

What can a manager do when told that "tough jobs" are the culprits of high scrap?

* He could merely assume he was being told the truth. Most likely, he then would shrug his shoulders and grumble that "it seems like we're always running high scrap jobs lately." Not a very satisfactory response.

* He could assume that he's being lied to. His response then would be something like, "Don't give me that ****! These castings aren't any worse than other jobs!" In my experience, when someone takes this approach, records are pulled showing that the jobs running normally have high scrap. The manager is frustrated because nothing has been solved, and those he was yelling at are convinced he's a jerk.

* He could use data to predict scrap rates. With the speed and data handling capabilities of today's computers, it's easy to predict what the scrap will be based on the history of the jobs run. Comparing the scrap actually experienced to what was predicted allows a manager to make a meaningful evaluation of his operation.

Predicting Scrap Rates Is Not Enough

Even if the scrap rate is low in the overall picture, if it's higher than or the same as what was predicted, the manager shouldn't be happy. Scrap rates on par with predictions are an indication that effective steps aren't being taken to improve the operation. Conversely, if the scrap is high but below the prediction, the manager should take some satisfaction. His people are improving techniques either on the general processes or on individual jobs.

It is reasonable to expect that the actual scrap always would be near the predicted rate if efforts to improve aren't made. That isn't the case. If a foundry doesn't work toward improvement, actual scrap will creep higher. Patterns wear, procedures slip and scrap rises when effort isn't expended. On the other hand, if effective effort is put into improving an operation, the actual scrap typically will be lower than predicted.

Many of the scheduling packages currently used in foundries make use of the knowledge that comes from predicting scrap. The programs automatically schedule additional castings to be poured based on the scrap history of the specific job. Taking that same information and applying it to all jobs and quantities run during a time period should be an easy programming task.

If you don't have such a program or can't afford one, don't worry. While having a program that calculates the prediction from existing records is the easier way, a simple spreadsheet program can be used to accomplish the same end.

The Unknown Scrap Factor: New Jobs

What about new jobs that have no production or scrap history? New jobs can be handled in two ways. Most operations don't track the scrap history of new jobs, so an average of all jobs is used. However a better method is to track the scrap of all new jobs and use that average. Why is that better? If new jobs typically have significantly higher scrap, this new method should draw attention to the process of starting new jobs and lead to improvements. An effective process for starting new jobs will help eliminate the need for a learning curve.

Using predicted scrap rates draws attention to specific jobs that do have high scrap. These jobs deserve more attention to improve. After all, it's almost always easier to see substantial improvement when working on a job that historically has had 50% scrap instead of one that has had 0.5%

Comparing actual scrap rates to predictions based on previous history isn't going to solve problems for managers. It still takes action to solve the problems, but the comparisons provide an additional tool to determine the direction of operations.