Build a Sparkplug B Multi-Zone Thermal Energy Optimizer
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.
What you are building
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.
Process Operations Engineer
Parse Sparkplug B thermal zone telemetry payloads across multiple industrial curing ovens.
Evaluate cumulative instantaneous power against utility peak demand threshold ceilings.
Sequence oven pre-heating and ramp intervals to stagger overlapping peak loads.
Generate a thermal ramp scheduling plan for furnace control operators.
Heatmap timetable illustrating staggered zone power curves against the site demand cap.
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.
Eclipse Sparkplug Uses Sparkplug B complex data types, metric properties, and dataset structures defined in Source 2.
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.
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.
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.
```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 } } ] ```
Read-only planning simulation; does not issue write commands to live furnace controllers. Use mock external writes. Require human review before any real deployment.
Rules
Read-only planning simulation; does not issue write commands to live furnace controllers. Use mock external writes and human review.
How work is evaluated
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.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
Complete workflow
Parse Sparkplug B thermal zone telemetry payloads across multiple industrial curing ovens. Evaluate cumulative instantaneous power against utility peak demand threshold ceilings. Sequence oven pre-heating and ramp intervals to stagger overlapping peak loads. Generate a thermal ramp scheduling plan for furnace control operators.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
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.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Heatmap timetable illustrating staggered zone power curves against the site demand cap.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Read-only planning simulation; does not issue write commands to live furnace controllers.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
Learning goals
Parse Sparkplug B thermal zone telemetry payloads across multiple industrial curing ovens.
Evaluate cumulative instantaneous power against utility peak demand threshold ceilings.
Sequence oven pre-heating and ramp intervals to stagger overlapping peak loads.
Generate a thermal ramp scheduling plan for furnace control operators.
Resources
Generate synthetic JSON payloads following Sparkplug B v3.0 metric schemas for multi-zone industrial ovens. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Challenge input
Input details are not configured.
Ray Serve
Action Space in the agent workflow.
Evaluated output
No output checks are configured.
- Parse Sparkplug B thermal zone telemetry payloads across multiple industrial curing ovens. Evaluate cumulat...
- Guarantees aggregate power remains below simulated 1.2 MW peak demand cap. Ensures all curing recipes achie...
- Heatmap timetable illustrating staggered zone power curves against the site demand cap.
- 2 public reference cases
- 1 configured tool
Shows the first task, up to three tools, and up to three evidence items.
View technical recipe
Configured tools
- Ray Serve · Optional
Evaluation contract
- Complete workflow · Weight 40
- Correctness and evidence · Weight 30
- Review interface · Weight 20
- Safe execution · Weight 10
Reference cases
- 2 public reference cases
Workflow tasks
No workflow tasks are configured.
Recipe freeze marker
No recipe freeze time is recorded.