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Performing a Part Compliance Query#

A Part Compliance Query determines whether one or more parts are compliant with the specified indicators. This is done by first finding all substances directly or indirectly associated with that part, determining compliance for those substances, and then rolling up the results to the material.

Connecting to Granta MI#

Import the Connection class and create the connection. See the Getting Started example for more details.

from ansys.grantami.bomanalytics import Connection

server_url = "http://my_grantami_server/mi_servicelayer"
cxn = Connection(server_url).with_credentials("user_name", "password").connect()

Defining an Indicator#

A Compliance query determines compliance against ‘Indicators’, as opposed to an Impacted Substances query which determines compliance directly against legislations.

There are two types of Indicator object (WatchListIndicator and RohsIndicator), and the syntax presented below applies to both. The differences in the internal implementation of the two objects are described in the API documentation.

Generally speaking, if a substance is impacted by a legislation associated with an indicator, and in a quantity above a specified threshold, the substance is non-compliant with that indicator. This non-compliance applies to any other items in the BoM hierarchy that directly or indirectly include that substance.

First, create two WatchListIndicator objects.

from ansys.grantami.bomanalytics import indicators

svhc = indicators.WatchListIndicator(
sin = indicators.WatchListIndicator(

Building and Running the Query#

Next define the query itself. Parts can be referenced by Granta MI record reference or Part Number. The table containing the Part records is not required, since this is enforced by the Restricted Substances database schema.

from ansys.grantami.bomanalytics import queries

part_query = (
    .with_part_numbers(["asm_flap_mating", "DRILL"])

Finally, run the query. Passing a PartComplianceQuery object to the method returns a PartComplianceQueryResult object.

part_result =
<PartComplianceQueryResult: 2 PartWithCompliance results>

The result object contains two properties, compliance_by_part_and_indicator and compliance_by_indicator.

Results Grouped by Part#

compliance_by_part_and_indicator contains a list of PartWithComplianceResult objects with the reference to the part record and the compliance status for each indicator.

In Granta MI, Parts can link to the following record types:

  • Parts

  • Specifications (which can link to Specifications, Materials, Substances, and Coatings)

  • Materials (which can link to Substances)

  • Substances

Because compliance of a part is determined based on the compliance of the items that the record is linked to, the corresponding ResultWithCompliance objects are included in the parent PartWithComplianceResult, each with their own compliance status.

Since we specified two part records, we have received two result objects back. In this example, we will only look in more detail at results for the wing flap assembly.

wing = part_result.compliance_by_part_and_indicator[0]
print(f"Wing compliance status: {wing.indicators['SVHC']}")
Wing compliance status: WatchListHasSubstanceAboveThreshold

This tells us that the wing flap assembly contains an SVHC above the 0.1% threshold.

We can print the parts below this part that also contain an SVHC above the threshold. The parts referenced by the wing part are available in the parts property.

above_threshold_flag = svhc.available_flags.WatchListAboveThreshold
parts_contain_svhcs = [part for part in
                       if part.indicators["SVHC"] >= above_threshold_flag]
print(f"{len(parts_contain_svhcs)} parts that contain SVHCs")
for part in parts_contain_svhcs:
    print(f"Part: {part.record_history_identity}")
1 parts that contain SVHCs
Part: 564821

This process can be performed recursively to show a structure of each part that contains SVHCs either directly or indirectly. The cells below implement the code above in a function that can be called recursively, and then call it on the wing flap assembly.

def recursively_print_parts_with_svhcs(parts, depth=0):
    parts_contain_svhcs = [part for part in parts
                           if part.indicators["SVHC"] >= above_threshold_flag]
    for part in parts_contain_svhcs:
        print(f"{'  '*depth}- Part: {part.record_history_identity}")
        recursively_print_parts_with_svhcs(, depth + 1)
- Part: 564821
  - Part: 564794
  - Part: 564907
  - Part: 565076
  - Part: 565088

This can be extended further to include all possible BoM components in the recursive iteration, including specifications, coatings, and substances.

def recursively_print_parts_with_svhcs(parts, depth=0):
    parts_contain_svhcs = [part for part in parts
                           if part.indicators["SVHC"] >= above_threshold_flag]
    for part in parts_contain_svhcs:
        print(f"{'  '*depth}- Part: {part.record_history_identity}")
        recursively_print_parts_with_svhcs(, depth + 1)
        print_materials_with_svhcs(part.materials, depth + 1)
        print_specifications_with_svhcs(part.specifications, depth + 1)
        print_substances_with_svhcs(part.substances, depth + 1)
def print_materials_with_svhcs(materials, depth=0):
    mats_contain_svhcs = [m for m in materials
                          if m.indicators["SVHC"] >= above_threshold_flag]
    for mat in mats_contain_svhcs:
        print(f"{'  '*depth}- Material: {mat.record_history_identity}")
        print_substances_with_svhcs(mat.substances, depth + 1)
def print_specifications_with_svhcs(specifications, depth=0):
    specs_contain_svhcs = [s for s in specifications
                           if s.indicators["SVHC"] >= above_threshold_flag]
    for spec in specs_contain_svhcs:
        print(f"{'  '*depth}- Specification: {spec.record_history_identity}")
        print_coatings_with_svhcs(spec.coatings, depth + 1)
        print_substances_with_svhcs(spec.substances, depth + 1)
def print_coatings_with_svhcs(coatings, depth=0):
    coatings_contain_svhcs = [c for c in coatings
                             if c.indicators["SVHC"] >= above_threshold_flag]
    for coating in coatings_contain_svhcs:
        print(f"{'  '*depth}- Coating: {coating.record_history_identity}")
        print_substances_with_svhcs(coating.substances, depth + 1)
def print_substances_with_svhcs(substances, depth=0):
    subs_contain_svhcs = [sub for sub in substances
                          if sub.indicators["SVHC"] >= above_threshold_flag]
    for sub in subs_contain_svhcs:
        print(f"{'  '*depth}- Substance: {sub.record_history_identity}")
- Part: 564821
  - Part: 564794
    - Specification: 164846
      - Coating: 83146
        - Substance: 75023
  - Part: 564907
    - Specification: 164846
      - Coating: 83146
        - Substance: 75023
  - Part: 565076
    - Specification: 164846
      - Coating: 83146
        - Substance: 75023
  - Part: 565088
    - Specification: 164846
      - Coating: 83146
        - Substance: 75023

We have now identified a coating that is causing non-compliance. There is a single coating in the assembly that is non-compliant, but it appears in 4 non-compliant sub-components. The coating also only contains one non-compliant substance.

Results Grouped by Indicator#

Alternatively, using the compliance_by_indicator property will give us a single indicator result that rolls up the results across all parts in the query. This would be useful in a situation where we have a ‘concept’ assembly stored outside of Granta MI, and we want to determine its compliance. We know it contains the subassemblies specified in the query above, and so using compliance_by_indicator will tell us if that concept assembly is compliant based on the worst result of the individual subassemblies.

if part_result.compliance_by_indicator["SVHC"] >= above_threshold_flag:
    print("One or more subassemblies contains an SVHC in a quantity > 0.1%")
    print("No SVHCs, or SVHCs are present in a quantity < 0.1%")
One or more subassemblies contains an SVHC in a quantity > 0.1%