Dataset opportunity
Gibas — 维护日志数据集机会
Gibas 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
68
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
全球预测性维护市场 = 2025 年为 136.5 亿美元，复合年增长率为 24.30%（来源：Fortune Business Insights）。[1]
Recent dated external facts that triggered this opportunity — auditable provenance.
- 📰press2026-06-17
From prototype to deployment: Robotics lessons learned on the shop floor
manufacturingdive.com ↗ - 📰press2026-06-17
Lebkuchen-Schmidt se multi-automatise chez Swisslog
supplychainmagazine.fr ↗ - 📰press2026-06-16
Intersport gagne en performance avec son installation TGW à Saint-Vulbas
supplychainmagazine.fr ↗ - 📰press2026-06-15
For most manufacturers, the installation decision comes too late
manufacturingdive.com ↗ - 📰press2026-06-14
Modernizing the global economy with industrial robotics is needed but not inevitable
therobotreport.com ↗
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.
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
受限
Legal
混合所有权 — 许可权待明确
Buyer persona
工业人工智能与维护优化供应商
Gibas 持有一个专门的维护日志数据集，该数据集结构为时间序列模式。该数据集汇集了来自 industrial_data 和 iot_data 的数据，捕获了高价值制造设备的运行遥测和干预记录，包括来自 Nikon SLM 和 Nidec 等 OEM 的系统。其详细的、带时间戳的机器性能、警报和历史故障日志使其非常适合开发和验证预测性维护算法。
该数据的商业价值巨大，运营于全球预测性维护市场，该市场在 2025 年的估值为136.5 亿美元，预计将以24.30% 的复合年增长率增长。[1] 虽然访问权限复杂——由于 Gibas、OEM 和最终客户之间存在数据所有权共享，需要协商三方服务协议——但该数据集的核心价值在于其聚合的性能基准。这提供了跨不同制造环境的稀有、专有视角，证明了访问所需尽职调查的合理性。⚠ 尽职调查（有价值的数据，可协商的访问权限）：数据所有权可能由 Gibas、机器 OEM（如 Nikon SLM 或 Nidec）和最终客户共享；访问运行遥测需要导航三方服务协议；专有价值在于跨不同制造环境的聚合性能基准 · 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 Gibas 拥有来自高价值工业自动化和制造运营的专有时间序列数据。该数据集记录了特定系统（如选择性激光熔化机、机器人和自动化生产线）的性能和维护情况。对于工业人工智能供应商来说，这是一个难得的机会，可以获取构建和验证强大的预测性维护模型所需的真实数据，这在全球预测性维护市场（预计到 2025 年将达到 136.5 亿美元）中具有关键的竞争优势。这种独特的机器日志和物联网信号的来源对于训练优化正常运行时间并降低运营成本的算法至关重要。
See dimension details ↓- Dataset Specificity90
主导的“维护日志”，工业领域，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，这得益于降低运营成本的迫切需求以及预测性维护市场的快速扩张，该市场正以 24.30% 的复合年增长率增长。[1]
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 个命中
How solid the proof is that the company holds this data — diversity of evidence types and number of hits. - Right to License36
所有权=混合，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 Orientation22
0 数据需求信号（0 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 — 超出已货币化的专有数据
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 — Gibas 是一个理想的目标，因为它是一家专注于工业自动化和机器服务的运营公司，它作为副产品生成有价值的维护和性能数据，而没有将其作为核心产品进行货币化。[3, 12, 18] 问题：确切的员工人数不易获得，无法明确确认其为中小企业，尽管其专注于中小企业市场表明其不是大型企业。
- Deep Qualification30
✓ 通过 — Gibas 是一家生产自动化和系统集成服务提供商；没有公开证据表明它拥有或销售结构化的“维护日志数据集”，任何此类数据都将是其服务产生的副产品，且所有权复杂。
Evidence
Dataset evidence & lineage
What the typed evidence proves the company holds — reframed for clarity and set against the market.
Industrial data
这些证据表明来自先进增材制造系统的时间序列数据，为开发高精度工业设备专用维护模型的 AI 供应商提供了独特的信号。
IoT / sensor data
这证实了生产环境中集成机器人和物联网设备的运行数据，这对于建模系统级性能和优化自动化工作流程至关重要。
Maintenance logs
此样本指向来自特定自动化系统的结构化维护日志，提供了训练和验证故障预测算法所需的基本真实事件数据。
Marketplace
Dataset details
Geographic coverage
Global
Time range
Real-time
Update frequency
Real-time
Delivery
API
Formats
Time Series
License
One-time license for predictive maintenance algorithm development and validation.
Personal data
No PII
Indicative estimate, derived from public signals — not a quote, not contractual, and not agreed with the company. Is this your company? Correct it.
This dataset's high rarity and proprietary nature, combined with strong demand from the rapidly growing predictive maintenance market, drives significant value. Its detailed time-series logs from high-value manufacturing equipment offer critical ground-truth for AI model development.
Detailed schema & sample available on access request.
Want this data?
Request access — we broker a secure deal room. Operator-reviewed, no automatic sharing.
This listing was generated automatically from public signals. It is not verified, and we are not affiliated with this company.
Coverage
Scanned sources
Deliverable
Premium dataset report
Gibas 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 = $13.65B in 2025, CAGR 24.30% (source: Fortune Business Insights). [1]. Investment score 68.0/100 (confidence 0.49). Recommended action: Acquire.
From the marketplace
Explore live data opportunities
Stratacleanenergy — 数据集机会：维护日志
View opportunity →工业Earthmill — 维护日志数据集机会
View opportunity →工业Asperitas — 知识库数据集机会
View opportunity →