Dataset opportunity
Ilmor — 维护日志数据集机会
Ilmor 持有的中等维护日志数据集，可用于预测性维护和异常检测。
Score
73.1
Score (0–100) blends weighted dimensions — dataset rarity, training value, buyer demand, evidence strength and right-to-license. 70+ is deal-ready. See the scored dimensions below for the breakdown.Confidence
49%
Action
收购
The recommended deal structure for this dataset: Acquire (full buyout), License (paid usage rights), Data Sharing Agreement (controlled access, no transfer of ownership), Partnership (co-development) or Annotation Program (labeling). Chosen from data ownership, licensing complexity and accessibility.Market size (indicative estimate)
全球预测性维护市场在 2024 年的价值为 123 亿美元，预计复合年增长率为 29.7%。
Lineage
How this lead was derived
The signal-first chain, end to end: recent external signals → qualified niche → resolved data-holder → site verification → scored opportunity. Every lead is explainable.
Concrete evidence this company actively cares about data — why it's ripe for the deal room.
- 🧑💻Hiring a data role
招聘专注于设计和分析的应届毕业生工程师
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Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
出行
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
受限
Legal
公司所有 — 许可权待澄清
Buyer persona
工业人工智能与维护优化供应商
Ilmor 持有源自其在赛车运动、航空航天和国防领域的高性能发动机项目的广泛时间序列 维护日志。这种独特的工业数据和物联网数据集合为开发和验证预测性维护算法提供了丰富的基础，捕捉了极端条件下的实际运行压力、组件磨损和故障事件。
全球预测性维护市场在 2024 年的价值为 123 亿美元，预计将呈现 29.7% 的复合年增长率。 [7] 虽然访问此数据需要应对共享所有权（与原始设备制造商合作伙伴）和高度敏感的知识产权等复杂性，但其稀有性和特异性使其具有极高的价值。从传统模拟格式中提取数据的挑战被其为在快速增长的市场中创建稳健、高精度预测模型所提供的保真度洞察所抵消。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权可能与原始设备制造商合作伙伴（例如，Chevrolet、Honda）或赛车队共享；与航空航天和国防部门相关的知识产权高度敏感；技术数据可能被隔离在传统模拟格式或物理测试日志中。· 公司：独立。
Scoring
Scored dimensions
Explainable, evidence-based dimensions (0–100). The radar shows the investment axes.
这些证据共同证明 Ilmor 持有源自数十年精密工程的专有、高保真时间序列数据集，用于赛车运动和航空航天领域。这些数据是工业人工智能供应商开发预测性维护模型的关键资产，而预测性维护是全球市场的核心用例，预计该市场将以 29.7% 的复合年增长率增长。该数据集源自高性能动力总成测试和数控制造，为训练算法以预测高风险工业环境中的故障提供了稀有的真相来源，使其具有极高的价值。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，行业出行，3 种特定类型
How sharply the data targets a specific, hard-to-substitute domain or task. Niche, well-defined data scores higher than generic. - Dataset Rarity82
专有领域数据
How scarce and proprietary the data is. Unique domain data scores high; openly available data lowers it. - Dataset Volume52
3 个证据命中
Apparent scale of the data, inferred from the number of evidence hits and any explicit volume mentions. - Dataset Freshness82
实时/流式传输
How current the data stays — real-time/streaming scores highest, periodic dumps lower. - Training Value84
适用于预测性维护
How useful the data is for the target AI use-case — its fit for model training or fine-tuning. - Buyer Demand90
买家需求异常高，这得益于预测性维护市场对专业工业数据集的迫切需求，该市场正以 29.7% 的复合年增长率扩张。[7]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility28
受限/未知
How legally easy the data is to obtain and use — open/API access scores high; PII or regulated data scores low. - Acquisition Feasibility30
中等难度，独立
How realistic it is to actually obtain the data, given access difficulty and the holder's corporate structure. - Evidence Strength62
3 种证据类型，3 次命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License70
所有权=公司所有，许可=权利不明确
Whether the company can legally license the data out — based on ownership and licensing complexity. - Corporate Independence90
独立
Whether the holder can decide alone — an independent company scores higher than a subsidiary of a large group. - Data Orientation39
1 个数据胃口信号（1 种类型）
How actively the company invests in data, measured by its data-appetite signals (hires, products, APIs…). - Dormant Data Surplus92
盈余=高 — 专有数据超出已货币化的部分
Volume and value of proprietary data this company holds BEYOND what it already monetises — the dormant surplus we can unlock. A company can sell some insights AND still sit on a far larger dormant asset. - ICP Audit92
✓ 良好目标 — Ilmor 是一家高性能发动机制造商，服务于赛车运动和船舶领域；它是一个理想的目标，因为它作为其核心工程业务的副产品生成有价值的维护和性能数据，并且似乎不销售这些数据。问题：该公司总部设在英国（ilmor.co.uk）并在美国拥有重要业务（ilmor.com），这可能会使联系和决策复杂化；虽然他们的核心业务是发动机，但他们越来越多地涉足电动推进领域，并拥有专门的“高级项目”小组，该小组可能拥有其 o
- Deep Qualification70
⚠ 需要审查 — Ilmor 是一家高价值工程服务提供商，其工作会产生大量的维护和性能数据。然而，这些数据是为 Chevrolet、Honda 和国防承包商等客户提供服务产生的副产品，导致数据所有权混合且转售权高度受限，这给收购带来了重大障碍。[许可受限]
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
IoT / sensor data
这些证据指向专有的时间序列数据，特别是来自数十年高性能动力总成严格测试的遥测数据，这对于模拟极端应力下的组件故障至关重要。
Industrial data
该数据集包括用于工程模拟的虚拟实验室模型产生的时间序列数据，为验证和优化预测性维护算法提供了关键基线。
Maintenance logs
这表明为航空航天和赛车运动领域服务的现代数控机床产生了持续的维护和运行数据流，这是训练模型以预测高精度制造中故障的丰富来源。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Ilmor Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the mobility domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance Market was valued at $12.3 Billion in 2024, with a projected CAGR of 29.7% (source: Custom Market Insights). Investment score 73.1/100 (confidence 0.49). Recommended action: Acquire.
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