feat(fusion_iot): add setpoint/optimum + deviation to sensor schema

Sensors previously only tracked alarm thresholds (alert_min/alert_max).
Missing the third piece of standard process control: the SETPOINT —
what the heater/chiller controls toward and what dashboards compare
against. Without it an operator can't tell whether 89°C is "on target"
or "barely still in spec".

Schema changes:

**fusion.plating.bath.parameter** (shop-wide default)
- New `target_value` field — the default setpoint for this parameter
  across the shop (e.g. 87°C for ENP bath). Parallel to existing
  target_min / target_max.

**fp.tank.sensor** (per-sensor override)
- New `target_value_override` — per-sensor override, zero = inherit
  from parameter. Matches the existing override pattern for alert
  thresholds so users can fine-tune per-tank without touching the
  shop-wide spec.
- New `effective_target` / `effective_target_unit` computed — resolves
  override → parameter default, converts to company-preferred unit.
- New `_get_setpoint()` helper for internal use.

**fp.tank.reading**
- New `deviation_from_target` — signed Δ from the sensor's effective
  setpoint, in the company's preferred unit. Positive = above, negative
  = below, zero if no setpoint defined.
- New `deviation_band` (selection: on/near/far/out/none) — coarse band
  for fast visual scanning. `on` = within ±1° of target, `near` = ±3°,
  `far` = beyond, `out` = actually out of the alarm band.

**Views**
- Sensor form: split the alerting panel into two groups — "Target
  (setpoint)" on the left, "Alarm band" on the right. Makes the
  distinction between "where we want to be" and "where we'd panic"
  visually obvious.
- Reading list: new Δ + band columns, with decoration classes
  (success/info/warning/danger) so the list reads at a glance.
- Tank form Sensors tab: inline setpoint + unit column.

Seeded: parameter "Bath Temperature (Hot Process)" now carries
target_value=87°C as a realistic ENP shop default. Sensors inherit
unless they set their own override.

Design decisions kept simple:
- Did NOT add a warning band (warn_min/warn_max). Two-tier model
  (setpoint + alarm band) is enough for the pilot. Can add soft
  warnings later as a separate commit if ops wants them.
- Did NOT auto-control heaters. Setpoint is stored as metadata only;
  actual heater actuation via IoT is a future phase C project.

Verified: setpoint 87°C stored → displays 188.60°F on the live pilot
sensor (company pref = F). Each incoming reading correctly computes
signed deviation; bands colour the reading list appropriately.

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

fusion_plating/fusion_plating/__manifest__.py

@@ -5,7 +5,7 @@
 
 {
     'name': 'Fusion Plating',
-    'version': '19.0.5.4.0',
+    'version': '19.0.5.5.0',
     'category': 'Manufacturing/Plating',
     'summary': 'Core plating / metal finishing ERP: facilities, processes, tanks, baths, jobs, operators.',
     'description': """

fusion_plating/fusion_plating/models/fp_bath_parameter.py

@@ -61,6 +61,13 @@ class FpBathParameter(models.Model):
         string='Default Target Max',
         help='Default target maximum. Per-bath overrides are allowed.',
     )
+    target_value = fields.Float(
+        string='Default Setpoint / Optimum',
+        help='The IDEAL operating value — what the heater/chiller controls '
+             'toward, what dashboards compare against. Sits between '
+             'target_min and target_max. Per-sensor override via '
+             'fp.tank.sensor.target_value_override.',
+    )
     warning_tolerance = fields.Float(
         string='Warning Tolerance %',
         default=10.0,