Hi Ronen
I really like your paper. However, I'm wondering how the principle may apply where there can be no assumption of homogeneity? For example, we make items written to a prescription and that conform to specifications detailed in a technical file and are made in line with a procedure/ work instruction. They all have homogeneous characteristics (the same materials are used and the procedure for making them is the same) but they will not conform *exactly* because dimensions will be written to suit the patient's requirements. Any views?
Cheers
James
Hi James,
I'm glad you like the paper.
The concept of Homogeneity in this context comes from the world of SPC, i.e. it relates to serial production. When it comes to individual "unique" products, there is little utility and need for statistical handling. I would say that in your case you should verify only those aspects of the device that are not unique (i.e. are not affected by specific-patient customisation) based on the methodology in my article. All other aspects that require verification should be verified 100%, i.e. checked (again, not necessarily tested) in each and every unique device unit, and documented in it's production record. In the case of custom/customised devices, looking at design verification and production verification (you may call the latter "production release", "QC" etc.) is somewhat redundant, because in a way one "designs" and makes just one unit of that "model".
I admit I wrote the article with serial production in mind, as I hardly deal with custom/customised devices. However, I think that some of the concepts and methods may still be useful for custom/customised devices.
So I would say that "homogeneous" is not found in nature, but a term to be defined. It can mean "conforms to specifications" or "conforms to procedure/work instructions." How much that means the specific items vary from each other, those are the details wherein you find the statistical devil. Your materials are not actually "the same" from device to device, nor is the extent to which they meet specifications. That's what "tolerances" are all about.
Thank you.
I think that in the current context Homogeneity is well-defined (refer to Dr. Wheeler's articles for example). To be precise, my article is mostly concerned with whether the subject samples come from a Homogeneous Process or not, and it also prescribes a method for determining that. I tried to be as unambiguous as I could in doing that, and I estimate that in a large majority of the cases the steps I listed will suffice. However, I acknowledge that in complicated/borderline cases the prescribed instructions will call for more judgement calls and analysis acumen. I tried to point in one possible direction for when that happens, but it's difficult to prescribe precise and detailed instructions to cover all possible anomalies and scenarios. I also think that even just realising that one is in that area is valuable, because it means one is already off the highway, i.e. the process is not as robust as it might/should be and maybe it's time to stop, think, and maybe go a few steps back in the D&D process.
