Build the application

## Build
Process Sparkplug B thermal oven metric updates and electric utility peak hours. Plan dynamic zone ramp-up sequences to minimize compound electrical peak demand charges.

## User
Process Operations Engineer

## Workflow
1. Parse Sparkplug B thermal zone telemetry payloads across multiple industrial curing ovens.
2. Evaluate cumulative instantaneous power against utility peak demand threshold ceilings.
3. Sequence oven pre-heating and ramp intervals to stagger overlapping peak loads.
4. Generate a thermal ramp scheduling plan for furnace control operators.

## Interface
Heatmap timetable illustrating staggered zone power curves against the site demand cap.

## Data
Generate synthetic JSON payloads following Sparkplug B v3.0 metric schemas for multi-zone industrial ovens.
Starter examples below are synthetic. They are not downloaded records.

## Source
[Eclipse Sparkplug](https://raw.githubusercontent.com/eclipse-sparkplug/sparkplug/master/README.md)
Uses Sparkplug B complex data types, metric properties, and dataset structures defined in Source 2.

## Tools
ray-serve, numpy.
Ray Serve enables scalable parallel evaluation of multi-zone thermal scheduling constraints across multiple production cells.
Local model for rule-checking or hosted API for thermal ramp plan explanation.

## Deliverables
Submit runnable source, pinned dependencies, setup commands, a working interface, example outputs, and a recorded end-to-end demo. Include tests and an action log.

## Acceptance
- Guarantees aggregate power remains below simulated 1.2 MW peak demand cap.
- Ensures all curing recipes achieve target soaking temperatures within required batch windows.
- Produces valid Sparkplug B compatible schedule proposal documents.

## Starter Examples
```json
[
  {
    "input": {
      "ovens": [
        {
          "id": "OVEN-1",
          "ramp_power_kw": 400,
          "soak_power_kw": 120,
          "ramp_min": 30,
          "soak_min": 60
        },
        {
          "id": "OVEN-2",
          "ramp_power_kw": 500,
          "soak_power_kw": 150,
          "ramp_min": 40,
          "soak_min": 45
        }
      ],
      "max_simultaneous_kw": 700
    },
    "expected_output": {
      "oven_1_start_minute": 0,
      "oven_2_start_minute": 30,
      "peak_aggregate_kw": 620,
      "demand_cap_breached": false
    }
  },
  {
    "input": {
      "ovens": [
        {
          "id": "OVEN-3",
          "ramp_power_kw": 600,
          "soak_power_kw": 200,
          "ramp_min": 45,
          "soak_min": 90
        },
        {
          "id": "OVEN-4",
          "ramp_power_kw": 650,
          "soak_power_kw": 250,
          "ramp_min": 45,
          "soak_min": 90
        }
      ],
      "max_simultaneous_kw": 800
    },
    "expected_output": {
      "oven_3_start_minute": 0,
      "oven_4_start_minute": 45,
      "peak_aggregate_kw": 850,
      "demand_cap_breached": true
    }
  }
]
```

## Safety
Read-only planning simulation; does not issue write commands to live furnace controllers.
Use mock external writes. Require human review before any real deployment.