Build a Workstation Bottleneck Triage and Buffer Rebalancing Planner
Evaluate multi-stage cycle time variances from simulated Sparkplug B device streams. Generate dynamic pallet buffer rebalancing proposals to alleviate manufacturing bottlenecks.
What you are building
The core problem, expected build, and operating context for this challenge.
Evaluate multi-stage cycle time variances from simulated Sparkplug B device streams. Generate dynamic pallet buffer rebalancing proposals to alleviate manufacturing bottlenecks.
Industrial Operations Planning Lead
Consume simulated Sparkplug B DDATA metric updates capturing station execution durations.
Compute moving average cycle times to detect process drift and buffer accumulation.
Synthesize buffer rebalancing proposals to divert in-progress pallets to auxiliary cells.
Generate a supervisor sign-off sheet with projected throughput recovery metrics.
Line balance histogram with drag-and-drop buffer allocation overrides and sign-off panel.
Create normalized synthetic JSON files of Sparkplug B DDATA payloads representing multi-station takt times. Store in local sandbox directory. Starter examples below are synthetic. They are not downloaded records.
Eclipse Sparkplug Sparkplug B DDATA metric records and property metadata for process duration tracking described in Source 2.
ollama, pydantic, fastapi. Ollama runs efficient local models on edge plant hardware without sending operational data to cloud infrastructure. Local quantized open model (e.g. 8B parameter class) capable of tabular numerical comparison.
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.
Detects stations operating at greater than 120% of target takt time.
Proposes valid pallet buffer diversions without overfilling target auxiliary buffers.
Calculates expected hourly production recovery under proposed dispatch routes.
```json [ { "input": { "line_takt_sec": 60, "stations": [ { "station_id": "ST_PRESS", "current_cycle_sec": 85, "buffer_count": 8, "buffer_max": 10 }, { "station_id": "ST_PRESS_AUX", "current_cycle_sec": 55, "buffer_count": 2, "buffer_max": 10 } ], "inbound_pallets": [ "P_101", "P_102", "P_103" ] }, "expected_output": { "bottleneck_identified": "ST_PRESS", "cycle_overrun_pct": 41.7, "diversion_proposals": [ { "pallet_id": "P_101", "divert_to": "ST_PRESS_AUX" }, { "pallet_id": "P_102", "divert_to": "ST_PRESS_AUX" } ], "projected_takt_recovery_sec": 62 } }, { "input": { "line_takt_sec": 60, "stations": [ { "station_id": "ST_PRESS", "current_cycle_sec": 58, "buffer_count": 3, "buffer_max": 10 } ], "inbound_pallets": [ "P_104" ] }, "expected_output": { "bottleneck_identified": "NONE", "cycle_overrun_pct": 0, "diversion_proposals": [], "projected_takt_recovery_sec": 58 } } ] ```
Read-only queue analysis. Output plans require industrial engineer approval before floor execution. Use mock external writes. Require human review before any real deployment.
Participation guide
Read-only queue analysis. Output plans require industrial engineer approval before floor execution. Use mock external writes and human review.
How work is evaluated
Detects stations operating at greater than 120% of target takt time. Proposes valid pallet buffer diversions without overfilling target auxiliary buffers. Calculates expected hourly production recovery under proposed dispatch routes.
Runnable source, pinned dependencies, setup commands, working interface, example outputs, recorded demo, tests, and action logs.
Challenge datasets
Public datasets, plus the private datasets you have access to.
How submissions are scored
These dimensions define what the evaluator checks and which criteria separate a passable run from a strong one.
Complete workflow
Consume simulated Sparkplug B DDATA metric updates capturing station execution durations. Compute moving average cycle times to detect process drift and buffer accumulation. Synthesize buffer rebalancing proposals to divert in-progress pallets to auxiliary cells. Generate a supervisor sign-off sheet with projected throughput recovery metrics.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Correctness and evidence
Detects stations operating at greater than 120% of target takt time. Proposes valid pallet buffer diversions without overfilling target auxiliary buffers. Calculates expected hourly production recovery under proposed dispatch routes.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Review interface
Line balance histogram with drag-and-drop buffer allocation overrides and sign-off panel.
Missing or incorrect.
Partly complete, with documented gaps.
Complete, with reproducible evidence.
Safe execution
Read-only queue analysis. Output plans require industrial engineer approval before floor execution.
This dimension contributes its full weight only when the submission satisfies the requirement. Partial credit is not awarded.
What you should walk away with
Consume simulated Sparkplug B DDATA metric updates capturing station execution durations.
Compute moving average cycle times to detect process drift and buffer accumulation.
Synthesize buffer rebalancing proposals to divert in-progress pallets to auxiliary cells.
Generate a supervisor sign-off sheet with projected throughput recovery metrics.
Reference links and supporting material
Create normalized synthetic JSON files of Sparkplug B DDATA payloads representing multi-station takt times. Store in local sandbox directory. Supplied starter examples are synthetic, not source extracts.
Challenge setup
Configuration summary for this challenge.
Challenge input
Input details are not configured.
Ollama
Local LLM runtime for offline inference.
Evaluated output
No output checks are configured.
- Consume simulated Sparkplug B DDATA metric updates capturing station execution durations. Compute moving av...
- Detects stations operating at greater than 120% of target takt time. Proposes valid pallet buffer diversion...
- Line balance histogram with drag-and-drop buffer allocation overrides and sign-off panel.
- 2 public reference cases
- 1 configured tool
Summary shows the first task, up to three tools, and up to three evidence items. Open the technical recipe to view all configured items.
View technical recipe
Configured tools
- Ollama · 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.