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Hi,

In Apparel/Garments/Textile industries, it is a common practice to have different types of defects like Major, Minor and Critical. And for all these types of defects users use different AQL values(normally for major and minor different AQL values are used and for Critical it’s always Acceptance No=0 and Rejection No=1 is used in most of the cases) due to which Acceptance and Rejection No changes, though the sample size remains the same as in AQL chart sample size is based on the lot size and acceptance and rejection no is based on AQL value.

In IFS Apps-10, we can assign only one AQL value for one control plan of an Inventory Part/Inventory Part and Supplier Combination. And we cannot have multiple control plans Active for each of the items. So, how can we handle this without customization/modification, can anyone suggest?

>I need this both for Manufacturing & Purchase items]

 

Regards-

Nahin

Hi,

Yes you are correct that in current versions of IFS Cloud you define the Acceptance Sampling parameters, including AQL, on the control plan header level only. 

Being able to define AQL (and Inspection Level) on the control plan line level is on the IFS R&D road map for future development in the Quality Management area.


Thanks @Peter Lundgren . If that is the case, I have to go for customization, but for that I need to get the AQL table that is available in the background. Any idea how can i reach that table, so that in the customization i can use that and the minimize the scope of the customization?

Regards-

Nahin


I think the table you want to use for the customization is named qman_as_aql


Thanks @Peter Lundgren .


And if you want to customize the Sample Size, Ac and Re values for a specific Code Letter and AQL combination, then have a look at the qman_as_attr_single_normalqman_as_attr_single_reduce and qman_as_attr_single_tight tables.


Ahh..great help @Peter Lundgren. Thanks.


Great news, in IFS Cloud 23R1 it is possible to control AQL and Inspection Level on the control plan line level. Both for Attribute and Variable acceptance sampling.

 


@Peter Lundgren , thats a real great news!!

Regards-

Nahin


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