diff --git a/SAS/TMSS/backend/test/t_adapter.py b/SAS/TMSS/backend/test/t_adapter.py
index ecfcbfa3dcd955abadab8aecd76edb0da69ce083..9d97e0f31b0f65ee8b271699f98f1c49874b4934 100755
--- a/SAS/TMSS/backend/test/t_adapter.py
+++ b/SAS/TMSS/backend/test/t_adapter.py
@@ -64,7 +64,7 @@ from lofar.sas.tmss.tmss.workflowapp.models.schedulingunitflow import Scheduling
 from lofar.sas.tmss.tmss.exceptions import SubtaskInvalidStateException
 from lofar.sas.tmss.tmss.tmssapp.adapters.parset import convert_to_parset, convert_to_parset_dict
 from lofar.common.json_utils import get_default_json_object_for_schema, add_defaults_to_json_object_for_schema
-from lofar.sas.tmss.tmss.tmssapp.adapters.sip import generate_sip_for_dataproduct
+from lofar.sas.tmss.tmss.tmssapp.adapters.sip import generate_sip_for_dataproduct, create_sip_representation_for_dataproduct
 from lofar.lta.sip import constants
 from lofar.sas.tmss.test.test_utils import set_subtask_state_following_allowed_transitions
 
@@ -331,6 +331,8 @@ class SIPadapterTest(unittest.TestCase):
         dataproduct.sap = sap
         dataproduct.save()
 
+        # wipe cache and regenerate
+        create_sip_representation_for_dataproduct.cache_clear()
         sip = generate_sip_for_dataproduct(dataproduct)
 
         # double-check that SIP contains values from feedback and specifications docs
@@ -352,6 +354,9 @@ class SIPadapterTest(unittest.TestCase):
         # alter dataproduct, recreate sip
         dataproduct.specifications_doc['coherent'] = False
         dataproduct.save()
+
+        # wipe cache and regenerate
+        create_sip_representation_for_dataproduct.cache_clear()
         sip = generate_sip_for_dataproduct(dataproduct)
 
         # assert we get an incoherent stokes beam
@@ -360,6 +365,9 @@ class SIPadapterTest(unittest.TestCase):
         # alter dataproduct, recreate sip
         dataproduct.feedback_doc['antennas']['fields'] = [{'type': 'HBA', 'field': 'HBA0', 'station': 'CS001'}]
         dataproduct.save()
+
+        # wipe cache and regenerate
+        create_sip_representation_for_dataproduct.cache_clear()
         sip = generate_sip_for_dataproduct(dataproduct)
 
         # assert we get a flyseye beam if we have a single antenna field
@@ -401,6 +409,8 @@ class SIPadapterTest(unittest.TestCase):
 
         # PULP ANALYSIS
 
+        # wipe cache and regenerate
+        create_sip_representation_for_dataproduct.cache_clear()
         sip = generate_sip_for_dataproduct(dataproduct)
 
         # double-check that SIP contains values from feedback and specifications docs
@@ -428,6 +438,9 @@ class SIPadapterTest(unittest.TestCase):
         # alter dataproduct, recreate sip
         dataproduct.feedback_doc['target']['coherent'] = False
         dataproduct.save()
+
+        # wipe cache and regenerate
+        create_sip_representation_for_dataproduct.cache_clear()
         sip = generate_sip_for_dataproduct(dataproduct)
 
         # assert datatype reflects change of coherent flag
@@ -439,6 +452,9 @@ class SIPadapterTest(unittest.TestCase):
         dataproduct.dataformat = models.Dataformat.objects.get(value="pulp summary")
         dataproduct.feedback_doc['$schema'] = 'http://127.0.0.1:8001/api/schemas/dataproductfeedbacktemplate/pulp summary/1#'
         dataproduct.save()
+
+        # wipe cache and regenerate
+        create_sip_representation_for_dataproduct.cache_clear()
         sip = generate_sip_for_dataproduct(dataproduct)
 
         # assert datatype reflects change of dataformat
@@ -514,6 +530,9 @@ class SIPadapterTest(unittest.TestCase):
             dataproduct.save()
             main_dataproducts.append(dataproduct)
 
+        # wipe cache and regenerate
+        create_sip_representation_for_dataproduct.cache_clear()
+
         # create their SIPs (separate loop since dataproduct.save() will invalidate cache):
         for i in range(10):
             dataproduct = main_dataproducts[i]