feat(fusion_plating): fp.work.centre bottleneck_score + avg_wait_minutes (P4.1)

Computes for the Manager At-Risk heatmap (Phase 4 tablet redesign).
Non-stored — recomputed on /fp/manager/at_risk read; that endpoint
caches its full payload for 60s so the cost is bounded.

  bottleneck_score = active_step_count * avg_wait_minutes
  avg_wait_minutes = rolling-7-day avg of (date_started - create_date)

Work centres with high score show red in the heatmap — combination
of queue length AND average wait time.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>

fusion_plating/fusion_plating/models/fp_work_centre.py

@@ -65,6 +65,51 @@ class FpWorkCentre(models.Model):
     # field via _inherit if/when the bake-oven coupling is needed.
     active = fields.Boolean(default=True)
 
+    # Phase 4 tablet redesign — Manager At-Risk heatmap inputs.
+    # Non-stored (recomputed on every read by /fp/manager/at_risk; the
+    # endpoint caches the payload for 60s anyway so the cost is bounded).
+    bottleneck_score = fields.Float(
+        compute='_compute_bottleneck',
+        string='Bottleneck Score',
+        help='active_step_count * avg_wait_minutes (rolling 7-day). '
+             'Drives the Manager At-Risk heatmap — work centres with '
+             'high score have queue + wait pressure.',
+    )
+    avg_wait_minutes = fields.Float(
+        compute='_compute_bottleneck',
+        string='Avg Wait (min)',
+        help='Average minutes that steps at this work centre waited in '
+             'ready state before starting, over the last 7 days.',
+    )
+
+    def _compute_bottleneck(self):
+        from datetime import timedelta
+        Step = self.env['fp.job.step']
+        now = fields.Datetime.now()
+        seven_days_ago = now - timedelta(days=7)
+        for wc in self:
+            active_n = Step.search_count([
+                ('work_centre_id', '=', wc.id),
+                ('state', 'in', ('ready', 'in_progress')),
+            ])
+            # Avg wait: recent steps where date_started is set; approximate
+            # "ready since" as create_date when no explicit ready timestamp
+            # is recorded. Bounded set (last 7 days) keeps the search cheap.
+            recent = Step.search([
+                ('work_centre_id', '=', wc.id),
+                ('date_started', '>=', seven_days_ago),
+                ('date_started', '!=', False),
+            ])
+            waits = []
+            for s in recent:
+                if s.create_date and s.date_started:
+                    waits.append(
+                        (s.date_started - s.create_date).total_seconds() / 60.0
+                    )
+            avg = (sum(waits) / len(waits)) if waits else 0.0
+            wc.avg_wait_minutes = avg
+            wc.bottleneck_score = active_n * avg
+
     _sql_constraints = [
         ('unique_code', 'UNIQUE(code)', 'Work centre code must be unique.'),
     ]