Robotics Manufacturer FMEA Analysis
Source, license and coverage
Supplier documentation. These claims are separate from the automated sample score. A listing edit date is not a data freshness date.
- License
- Not documented — confirm reuse terms with the seller
- Source / creator
- Not documented
- Collection method
- Supplier description: 35 FMEA records across 6 robotics companies. 490 field entries covering failure modes, effects, causes, severity/occurrence/detection scores, RPN, recommended actions, and verification methods for major robotics manufacturers: Boston Dynamics, FANUC Robotics, Intuitive Surgical, KUKA Robotics, Unitree Robotics, and iRobot. This is a curated selection and does not include all failure modes for these systems — it represents a sample of documented engineering analysis. Sources include public safety reports, technical documentation, and published engineering analysis of commercial robotics systems. Data compiled from publicly available information in the public domain.
- Coverage start
- Not documented
- Coverage end
- Not documented
- Data last updated
- Not documented
- Update schedule
- Not documented
CSV quoting repaired for F-002 verification_method and S-004 failure_effect; embedded commas and all 35 original records are preserved. This is a formatting repair, not independent verification of the engineering claims. Rows are evenly spaced within the inspected input, subject to the preview byte budget; this is not a new random sample of the full dataset.
Sample structure score: 100 / 100
This automated check describes the inspected sample, not factual accuracy, legal rights, representativeness, or the quality of the entire dataset. It is not a customer rating.
Assessed 10 sample records (JSON) on 2026-10-09. All records in the provided sample were checked.
| Check | Points | Evidence |
|---|---|---|
| Populated cells | 50 / 50 | 140 of 140 top-level cells contain a value. Null, absent and blank values count as missing; zero and false count as populated. |
| Consistent value types | 30 / 30 | 140 of 140 populated cells match their column's most common observed type. Types are inferred, not checked against real-world truth. |
| Consistent record shape | 20 / 20 | 10 of 10 records have the expected fields. CSV/TSV use the header width; JSON uses the union of observed keys. |
Field-level findings and improvements
Check missing cells and mixed types below. Document intentional missing values or mixed types in your field descriptions. Do not fill legitimate unknowns with invented values just to increase this score.
| Field | Missing cells | Most common type | Other populated types |
|---|---|---|---|
| company | 0 / 10 | string | 0 / 10 |
| fmea_id | 0 / 10 | string | 0 / 10 |
| failure_mode | 0 / 10 | string | 0 / 10 |
| failure_effect | 0 / 10 | string | 0 / 10 |
| failure_severity | 0 / 10 | number | 0 / 10 |
| failure_cause | 0 / 10 | string | 0 / 10 |
| failure_occurrence | 0 / 10 | number | 0 / 10 |
| failure_detection | 0 / 10 | string | 0 / 10 |
| recommended_action | 0 / 10 | string | 0 / 10 |
| verification_method | 0 / 10 | string | 0 / 10 |
| rpn_severity | 0 / 10 | number | 0 / 10 |
| rpn_occurrence | 0 / 10 | number | 0 / 10 |
| rpn_detection | 0 / 10 | number | 0 / 10 |
| rpn_total | 0 / 10 | number | 0 / 10 |
About this data
35 failure mode and effects analysis records from 6 robotics manufacturers (Boston Dynamics, FANUC, Intuitive Surgical, KUKA, Unitree, iRobot). Records include failure modes, effects, causes, severity/occurrence/detection scores, risk priority numbers, recommended actions, and verification methods. Sample of documented engineering analysis from public safety reports and technical documentation; does not represent complete failure mode inventories.
Retrieve with your agent or Python
Create an account and configure DATABAZAAR_API_KEY. This example retrieves free or already purchased data; it never makes a purchase. For a multi-file dataset, choose a file index from the manifest.
Download the Python examplepython3 retrieve-dataset.py 330fa30a-a3e0-4b9f-9fa1-c7a540d52fc1 --output dataset.bin
Full supplier documentation
Schema
| Name | Type | Description |
|---|---|---|
| company | string | |
| fmea_id | string | |
| failure_mode | string | |
| failure_effect | string | |
| failure_severity | number | |
| failure_cause | string | |
| failure_occurrence | number | |
| failure_detection | string | |
| recommended_action | string | |
| verification_method | string | |
| rpn_severity | number | |
| rpn_occurrence | number | |
| rpn_detection | number | |
| rpn_total | number |
Sample Data
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For AI Agents
# 1. Add to your agent's MCP config (claude_desktop_config.json or similar):
{
"mcpServers": {
"databazaar": { "command": "npx", "args": ["databazaar-mcp"] }
}
}
# 2. Your agent can then call:
search_datasets({ query: "Robotics Manufacturer FMEA Ana" })
// Found: 330fa30a-a3e0-4b9f-9fa1-c7a540d52fc1
buy_now({ dataset_id: "330fa30a-a3e0-4b9f-9fa1-c7a540d52fc1" }) // uses your saved card# Authenticate with your API key:
curl https://api.databazaar.io/datasets/330fa30a-a3e0-4b9f-9fa1-c7a540d52fc1 \
-H "Authorization: Bearer YOUR_API_KEY"
# Purchase:
curl -X POST https://api.databazaar.io/datasets/330fa30a-a3e0-4b9f-9fa1-c7a540d52fc1/buy \
-H "Authorization: Bearer YOUR_API_KEY" \
-H "Content-Type: application/json" \
-d '{"dataset_id": "330fa30a-a3e0-4b9f-9fa1-c7a540d52fc1"}'