Not every supplier of thermoplastic materials - such as Nylon -  test their final product before bagging it up and sending it of to the plastic processor. And even those that do  test  their  product  before  shipping  it  can  make mistakes.   

The Confirmation mode of the identiPol QA2 system can be  used  to  confirm  that  a  fresh  batch  or  delivery  of material  from  your  supplier  can  be  processed  without issue.  This article  sets out  how the Confirmation mode may  be  used  for  the  rapid  assessment  of  Nylon  (PA) material in a quality assurance procedure. 

First the system “learns” the properties of good material - in this case PA - by measuring 10 to 20 batches of good material  that  have  previously  been  processed  without problems.  These  measurements  are  used  to  build  a reference  set  against  which  future  batches  can  be compared against.  

The  identiPol  system  uses  the  QIS  as  a  measure  of similarity between in-coming material and the reference set. A QIS of 10 would indicate that the samples are totally identical and a value of 0 would mean they are completely different.  In  practice,  values  between  7  and  10    are perfectly acceptable in order to have confidence that the material  may  be  put  onto  the  producon  line  with confidence.    The  simplicity  of  using  the  QIS  value  as  a measure of PASS (7 or over) or FAIL (less than 7) cannot be over emphasised as it enables new, inexperienced or non- technical staff to quickly make a judgement prior to putting material into the manufacturing process.

Test samples are prepared by moulding a couple of plasc granules  within  the  idenPol  QA2  to  give  a  consistent material  for  measurement.  This  is  then  followed  by  a second heating regime to measure the properties of the new batch of material.  

A  sample  score  between  4  and  below  7,  would  usually indicate it is very similar, but a key property (e.g. a lower softening temperature) is different. Contamination is one reason  why  a  QIS  value  could  drop  below  7.  If  there  is contamination in sufficient quanty to affect the QIS, then it will almost certainly affect either processing or product properties.   

In the example above the QIS value is shown for various batches of Nylon (Z12, Y22 & X43). The green band at the top of the graph is the “Pass Region” and results falling in this zone are acceptable and the material can be processed.

Clearly batches Z12 and X43 are acceptable as all of the results fall within the “Pass Region” and so this material may  be  passed  onto  the  production  line  without problems.  

Any  results  falling  in  the  white  area  below  the  green band fall in the “Fail Region” and this material should be rejected and not used in production. Batch Y22 is in this region and has a QIS value significantly below 7. So, this material  would  be  unsuitable  to  pass  onto  the production line and the quality of the material should be questioned  with  the  supplier.  If  this  material  were processed  it  would  produce  an  item  with  significantly different mechanical properties and be rejected by the final customer.  

The  Batch  Summary  Report  below,  details  the  key properties for each batch. Aside from the Pass / Fail QIS value, the report also includes results for Amorphicity, Melting  point,  End  point  and  Glass  transition temperature.  This table can be used as evidence with the supplier to challenge the specifications of Batch Y22 which has a lower glass transition temperature and no measureable melting point.  

So, by using the identiPol QA2, within 10-15 minutes of a new  delivery,  an  operator  can  easily  make  a  decision about  the  suitability  of  accepting  and  using  the  fresh material on the production line.  

For most purposes, the simple PASS / FAIL approach of the Confirmation Mode of operating the identiPol QA2 is sufficient  to justify the adoption of the system within the  manufacturing  environment.  However,  detailed reporting, statistical analysis and visualisation of the raw data are possible if further evaluation is required.