Dataset opportunity
Robkub — 维护日志数据集机会
Robkub 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
48
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 = 2025 年为 142 亿美元，复合年增长率为 27.9%（来源：Grand View Research）。[1]
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.
- ✨Signal
在 VivaTech 和食品行业活动中展示机器人自动化
source ↗
Profile
Dataset profile
Type
维护日志数据集
Modality
时间序列
Sector
工业
Volume
中等
Freshness
实时
Rarity
高（专有）
Accessibility
部分
Legal
公司所有 — 许可干净
Buyer persona
工业人工智能与维护优化供应商
Robkub 持有的由其专有“Kubs”机器人硬件生成的时间序列维护日志数据集，该硬件部署在专业厨房中。此工业物联网数据随时间推移提供详细的运行和性能指标，可直接用于训练预测性维护模型，以在硬件发生故障之前进行预测。
全球预测性维护市场在 2025 年的估值为 142 亿美元，预计将以 27.9% 的复合年增长率增长（来源：Grand View Research）。[1] 虽然数据的所有权可能受客户合同的约束，其数量取决于活动单元的数量，但此数据集代表了一个难得的机会。它提供了对高增长、高需求市场中真实运行数据的访问，使其对于开发专业的 AI 解决方案具有价值。⚠ 注意（有价值的数据，可协商访问）：数据由部署在专业厨房中的物理机器人硬件（Kubs）生成；特定烹饪日志的所有权可能受暗厨中客户合同的约束；小型初创公司，数据量取决于已部署的活动单元数量。· 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 Robkub 持有来自高压环境中的工业机器人的专有时间序列维护和运行日志数据集。这些数据直接满足工业人工智能供应商开发预测性维护解决方案的需求，该市场预计到 2025 年将达到 142 亿美元。该数据集结合了传感器数据、运行参数和已记录的故障事件，提供了训练和验证高价值人工智能模型所需的完整图景，这些模型可以预测设备故障，这是任何工业自动化客户的关键能力。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，工业部门，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 Demand92
人工智能买家需求异常高，这得益于市场从 142 亿美元的强劲 27.9% 的复合年增长率快速扩张，表明对真实训练数据有迫切需求。[1]
How strongly AI builders and companies are likely to want this data, based on market signals. - Legal Accessibility50
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 Feasibility44
低难度，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 License92
所有权=已拥有，许可=干净
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 Surplus70
盈余=中等，5 个近期外部信号 — 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 Audit75
⚠ 审查 — Robkub 是一家法国机器人集成商，向中小企业销售“协作机器人”解决方案，而不是持有休眠数据的公司，因此不适合，因为其核心业务是销售工业自动化硬件和服务。问题：该公司的核心业务是为工业客户设计、制造和集成协作机器人（“协作机器人”）；它是一家技术/硬件供应商，而不是拥有非数据运营业务并以此为副产品产生数据的公司；提示中提到的“维护日志数据集”似乎是一个误解或外部概念；Robkub 的业务是销售机器人本身；该公司已经是工业公司的服务提供商，这与目标画像相反。[1, 3, 5]
- Deep Qualification60
✓ 通过 — Robkub 提供机器人厨房硬件即服务，这可能产生维护和运行日志。然而，由于缺乏公开文档，数据所有权和许可条款未确定，并且未发现近期特定触发数据中心战略的迹象。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
press
- “<p>The robot-in-table design is meant to save space in the operating room, with J&J saying its novel architecture takes up 30-50% less space than boom-and-cart systems.</p> <p>The post <a href="https://www.therobotreport.com/photos-first-look-at-jjs-ottava-surgical-robot/">Photos: First look at J&J’s Ottava surgical robot</a> appeared first on <a href="https://www.therobotreport.com">The Robot Report</a>.</p>”
- “<p>By training GEN-1 to work with new hands, Generalist said a single base model can learn sensorimotor policies on different robots.</p> <p>The post <a href="https://www.therobotreport.com/generalists-gen-1-foundation-model-now-supports-a-range-of-robot-end-effectors/">Generalist’s GEN-1 foundation model now supports a range of robot end effectors</a> appeared first on <a href="https://www.therobotreport.com">The Robot Report</a>.</p>”
- “<p>YMX Logistics was named one of the honorees in the Operational AI Integration category for the AI Excellence in Supply Chain Awards.</p> <p>The post <a href="https://www.freightwaves.com/news/ymx-logistics-reduced-a-grocery-distributors-yard-fleet-by-36-with-its-autonomous-yard-operating-system">YMX Logistics Reduced a Grocery Distributor’s Yard Fleet by 36% With Its Autonomous Yard Operating System</a> appeared first on <a href="https://www.freightwaves.com">FreightWaves</a>.</p>”
IoT / sensor data
该数据集包括来自机器人手臂的实时物联网传感器数据，提供了构建复杂异常检测算法所需的精细、高频输入。
Industrial data
它包含详细的工业数据日志记录，如温度和机械运动等特定运行参数，这对于模拟使用模式与组件磨损之间的关系至关重要。
Maintenance logs
该集合以历史维护日志为基础，这些日志记录了实际的服务事件和故障，提供了训练和验证预测性维护模型所需的关键地面真实标签。
Marketplace
Dataset details
Detailed schema & sample available on access request.
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Coverage
Scanned sources
Deliverable
Premium dataset report
Robkub Maintenance Logs — a Moderate maintenance logs dataset (Time Series modality) in the industrial domain. Primary AI use-case: Predictive Maintenance. Market signal: Global Predictive Maintenance market = $14.2 billion in 2025, CAGR 27.9% (source: Grand View Research). [1]. Investment score 48.0/100 (confidence 0.49). Recommended action: Acquire.
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