I recently attended a training course in Six Sigma for Contact Centers. As part of the training there are a number of assessments, however, there is one that I am particularly stuck on.
The question is: "Operations Management is an important component in a Contact Centre. List the four quality components and briefly explain them".
I have managed to find the following: "Good quality does not merely mean high quality. It means a predictable degree of uniformity and dependability at a low cost with quality focused on the customer".
I assume that the four quality components are: uniformity, dependability, low cost, quality focused on the customer.
My problems are as follows:
1. I am assuming that they are the four quality components
2. I am assuming that this means consistency of service in the most cost effective way
3. How do I explain each component in relation to a Contact Centre
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Comments
hershal 11/7/2002
Patti,
The range you are getting suggests one or more influences are not under complete control.
The first issue to to characterize the CMM, so that you have a reliable and known base to determine bias and linearity.
I recommend having an accredited calibration labs perform a calibration of the CMM, if that is not already being done. Make sure the calibration is included under their scope of accreditation, and that they will provide you a certificate that includes the accreditation logo--and more importantly the actual readings with the associated uncertainties.
Make sure the environment is controlled to what is appropriate, and that you are not using the CMM at the end of its travel capability.
Then you are ready to begin determining the bis and linearity of the new gage. Use the manufacturer's recomendations if possible to determine the gage response.
Without knowing what the new gage method is and what exactly it is measuring, it is difficult at best to provide a more complete answer. For example, is the CMM using touch, laser, or vision probes? What measurements are being taken and what is the acceptance criteria? What material(s) is/are being measured? What are the environmental conditions/controls? All these and more will feed into the final answer of what is allowable for the task at hand.
Hope this helps define things a bit.
Hershal
Metrology Forum moderator (sorry about plugging the Met Forum, Forrest)
firebrew 9/27/2002
Notwithstanding the excellent reply that Forest Breyfogle provided, I may offer a couple other thoughts.
Be careful that you aren't making this more complicated than it needs to be. A fully nested design is very simple and may serve your needs.
Secondly, I might suggest an excellent text by Don Wheeler and Lyday called "Evaluating The Measurement Process" for some easy to understand principles. It is in Paperback, very reasonably priced, and deals very nicely with the concept of Measurement Systems vs. Per-Cent of Tolerance type criteria.
Happy testing and learning.
John Bruman
QA Manager
forrestbreyfogle 9/26/2002
Question: I am qualifying a new gage method and comparing to the current method as well as CMM. We consider CMM to be "truth" so one analysis I am running is the gage linearity/bias. I am using the gage tolerance for the variation. Do you have a recommendation for the how much gage bias which accounts for the overall process variation is acceptable? Minitab gives you a %. I am getting anywhere from less than 1 to 15%.
Response: Relative to how you worded the issue I don't believe that there is a "right" percentage number for all situations. We need to remember also that the % calculated in the analysis is for the sample and is only an estimate of the true value.
You made a comment that one of the purposes of the work was to determine if the new gage method had less bias than the previous gage method. For this issue, we could word this as a hypothesis statement, where the null hypothesis is the bias for both gages is equal. We could conduct this experiment as a pair-wise comparison experiment. Also for the purpose of the analysis we want to record how the measurement of a part (at a certain position) differs from the CMM measurement of the part.
From this data we could also test the null hypothesis that the bias of the new gage is zero, in addition to getting a confidence interval for the amount of this bias. I think that this way of looking at the bias could be more meaningful than a percentage number.
Hope this helps.
Best Regards,
Forrest Breyfogle
512-996-8288
forrest@smartersolutions.com
www.smartersolutions.com