What should be the Big Y for a scrap reduction proj?

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    I am currently running a scrap reduction project in a process industry. The scrap is measured in kgs. Can some one help me on,
    the Y should be output / production?
    how would you do a guage R&R for an outpout?



    I did a project several years ago related to increasing yield, which ended up being decreasing scrap. Without getting too long, it involved finding out what types of scrap we were getting, such as cracks, porosity, machining errors, etc. I then set up a weighted Cause & Effect Matrix to determine what conditions were generating the most rejections, or what was most important related to quality. Again, with that matrix I was also able to look at what parameters fed them.
    Along the way there were process flows, various analyses, checking of spectrometers and x-rays (basically R&R’s) and DOE’s.
      What ended up being improved was Rolled Throughput Yield, so maybe that was the big “Y”. Don’t know if this helps, but I think you’re going to have to go digging to define “scrap” and head on out from there.


    Mike Carnell

    Pramod,I would need to understand more about your operation to help you very much. The use of kgm’s won’t work well unless your scrap is all one type of material. if you drive kgm’s alone and one process scraps 100kg in wood and another 100kg of gold they would be considered equal opportunity and that would not make any sense.Just my opinion


    Michael Mead

    It seems you are at the “define” stage yet talking
    about the “measure” stage. In almost every case,
    scrap comes in different flavors. I’d find out the
    defect type of the scrap, maybe a Pareto
    diagram…look at combining them as clusters based
    on cause or corrective action. That is the analyze


    Chris Seider

    Mike Carnell’s assertion is spot on….
    If you do group your products among groups and you want to track a “Y”, then you must at a minimum then track the kg/some production unit.  That production unit should make sense for your process (e.g. rolls or tons or kg or meter or …).  The reason you should at least make it a ratio is if your production volumes change much over the weeks, months, etc. then your kg of scrap would change even if you had the same % scrap.  You wouldn’t want to be a “hero” if your kg scrap decreased from one month to the next IF your production volume was cut in half?  Also, you would be a “villian” if your kg increased from one month to the next if your production volume increased by a factor of 2.  Make it a ratio….



    Thanks for all the comments. I would try breif my process a little bit, so that it helps to have clear responses.
    This is a plastic co-extrusion process which invloves extrusion, compression moulding and offset printing. Typically for an scrap reduction project the Y is desirably the RTY in the scenario described, however we wanted to drive Scrap as the key measure. This was due to other factors such as scrap reconciliation was to be improved. The scrap in the process is as high as 30 % in which there are many inherent scraps such as purging etc.
    There are many “low hanging fruits” in the process, which you fix it and eliminate the gaps for which I am also using the Lean methodology. I hope this makes the picture clear.
    I would appreciate the valuable comments.
    Best Regards,


    Kevin Cox

    Cost of poor quailty (CPQ) is a great place to start. You may nor be able to get all of the losses calculated right off but a few of the big ones will give you something to work on.



    I wish to contradict some of the advice you have. Many people often are mistaken to believe that ‘Normalising’ metrics (dividing by volume) are better.
    This is based on the presumption that the process is stable. I suggest you plot scrap vrs volume over time and look at control charts of scrap and volume to confirm whether the relationship exists otherwise you might as well use lottery numbers as a project metric  ;).
    In my experience the presumed relationship was never found. Often instead of scrap being the result of ignored common cause errors (e.g. poor moulds, uneven curing, poor measurement systems) it is predominantly the result of special causes (catastrophic failures, wetting a line, undertrained assoicates)…
    As for metrics unless volume is a key input – everyone understands scrap $ / weight (kg). Keep it simple to help generate buyin
    Maybe secondary metrics to consider include: labor hours, cycle times or throughput..
    Additional Key tools to consider are: 5S, Chi-sqaure benchmarks with your toolmakers/suppliers, Paretos, some Fractional DOE to test prototypes. Can you save additonal money by recycling or reducing cost of recylcing scrap? Have fun!

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