Predicting Scrap

by

Roy Lobenhofer

ďWhy is the scrap so high?Ē

 

Iíll bet a day doesnít go by that some foundry manager doesnít ask that question. Iíll also bet there isnít a day when a foundry manager doesnít get the answer, ďWe were running jobs that always have high scrap.Ē

 

Itís a very frustrating exchange for managers. They really want to chew some butt for the high scrap, but they also realize there are high scrap jobs.

 

Interesting side note Ė I donít remember ever hearing a foundryman say, ďOh, weíre just running good jobs.Ē when complimented on low scrap.

 

Everyone working in a foundry for any length of time knows some jobs have higher scrap than others. Those jobs most likely push the envelope of the foundryís capability, but if enough of those jobs run at one time, higher scrap totals should be expected.

 

Foundry scrap depends upon the processes affecting every job and the idiosyncrasies of individual jobs. If the processing allows the metal to get too cold periodically, castings will misrun even if the gating is well done. On the other hand, if the ingates are too small on a particular job, misruns happen even if the metal temperature is normal.

 

What is a manager to do when given the reason for high scrap as running tough jobs?He could merely assume he was being told the truth.He would then most likely be left to shrugging his shoulders and saying something like, "It seems like we're always running high scrap jobs lately."Not a very satisfactory response.

 

A second alternative would be for the manager to assume that heís being lied to.His response then would be something like, "Don't give me that ****!The castings weíve been running arenít any worse than any others!"Itís been my experience when someone takes this approach, records are usually pulled showing that jobs that normally do have high scrap were run.The manager is frustrated, and those who were the recipient of the tirade are further convinced heís a jerk.

 

Thereís a better way now. Quit looking at total scrap.Instead, look at the difference between actual and predicted scrap. With the speed and data handling capabilities of todayís computers, itís an easy matter to predict what the scrap will be based on the history of the jobs run.

 

Even if scrap is low, if itís higher than or the same as predicted, the manager shouldnít be happy. Itís an indication that effective steps arenít being taken to improve the operation. Conversely, if the scrap is high but below prediction, the manager can take some satisfaction. His people are improving techniques either on the general processes or on individual jobs. As Plato said, ďNever discourage anyone who continually makes progress, no matter how slow.Ē

 

One should expect the actual scrap would be around the predicted if nothing has changed; however, itís been my experience that isnít the case. If a foundry doesnít constantly work on improving, actual scrap will creep higher. Patterns wear, procedures slip, and scrap rises when effort isnít expended.

 

Many of the scheduling packages currently used in foundries already take advantage of the logic of predicting scrap.They 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 of the jobs and quantities run during a time period should be an easy programming feat.

 

While having a program to calculate the prediction from existing records is the easier way, a simple spreadsheet program can be used to accomplish the same end.

 

What to do with data from jobs with no history is a legitimate question. Predicting the scrap from new jobs can be handled in two ways. Most operations donít track the scrap history of new jobs. If thatís the case, an overall average of all jobs could be used. A better way is to develop an average for new jobs. Why is that better? It points out a potential operational problem. If new jobs typically have significantly higher scrap than existing jobs, the average should draw attention to the need to improve the process of starting new jobs.

 

Another benefit of using predicted scrap is that it draws attention to the specific jobs that do have high scrap. It is those jobs that deserve the attention necessary to improve their operation. After all, itís almost always easier to see substantial improvement when working on a job that historically has 50% scrap instead of one that has Ĺ %

 

Comparing actual scrap to predictions based on previous history doesnít solve problems for managers. It always takes action to solve the problems, but the comparisons provide an additional tool for managers to determine the direction of their operations.

 

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