Dataiku > 实例探究 > 利用大型异构数据集来改进制造流程

利用大型异构数据集来改进制造流程

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公司规模
Large Corporate
国家
  • Worldwide
产品
  • Dataiku Data Science Studio (DSS)
技术栈
  • Machine Learning
  • Artificial Intelligence
  • Internet of Things (IoT)
实施规模
  • Enterprise-wide Deployment
影响指标
  • Productivity Improvements
  • Cost Savings
技术
  • 分析与建模 - 机器学习
  • 分析与建模 - 预测分析
适用功能
  • 维护
  • 离散制造
用例
  • 预测性维护
  • 机器状态监测
服务
  • 数据科学服务
关于客户
依视路国际是世界领先的眼科光学公司。该公司设计、制造和销售各种镜片,以改善和保护视力。依视路在全球拥有 67,000 名员工,拥有 34 家工厂、481 个处方实验室和磨边设施,以及全球 4 个研发中心。该公司的核心业务是生产眼科镜片。依视路致力于确保工厂高效、创新并遵守高质量标准,拥有全球工程 (GE) 服务,负责实施和标准化生产流程。
挑战
领先的眼科光学公司 Essilor International 面临着改进表面处理机的流程和性能以大幅提高产量的挑战。镜片制造中的表面处理步骤复杂而精细,因为它赋予镜片光学功能。该公司旨在优化此步骤以符合每个人的个人处方和个人参数。然而,他们正在处理来自表面处理机的大量异构数据集,需要一种可扩展的方式来处理这些数据。该公司已经在使用物联网连接设备等持续监控技术,但他们希望更进一步,采用先进的算法和机器学习,根据实时洞察采取行动。
解决方案
Essilor 选择 Dataiku 数据科学工作室 (DSS) 来帮助他们有效处理来自表面处理机器的大量数据。Dataiku 的设置和实施非常简单,使他们能够快速上手。该工具使他们能够探索、分析和创建预测模型,每个人都可以使用这些模型,从专业专家到机器操作员、数据科学家和 IT。Dataiku 还使他们能够高效、有效地管理来自表面处理机器的数据变化。该团队能够快速测试和迭代用例,以更快地找到解决方案。他们还欣赏使用代码或使用点击式可视化界面的灵活性,无论哪种方式都能让他们更快地工作。
运营影响
  • The GE team at Essilor was able to use Dataiku to execute on a predictive maintenance use case that indicates to operators the right time to change the consumable components so as to optimize their lifespan while also guaranteeing the production quality standards.
  • In addition to using Dataiku to predict the optimal conditions under which they will use the consumables completely, the GE team also leverages Dataiku’s web application feature to provide a visual decision tool to help operators make a consistent choice when they have to change the consumables.
  • The GE team provides value to Essilor as a whole by promoting the use of data to provide insight throughout the rest of the organization - Dataiku is now being used internationally by additional teams.
  • The team also encourages cross-team collaboration, as the use case was a collaborative work between the GE department, factories, and IT teams.
  • The company gained a dedicated resource for data science, which will allow them to continue to make future improvements.
数量效益
  • Optimized lifespan of consumable components, ensuring production quality standards.
  • Promotion of data usage for insights throughout the organization, leading to international use of Dataiku by additional teams.
  • Enhanced cross-team collaboration between the GE department, factories, and IT teams.
  • Acquisition of a dedicated resource for data science for future improvements.

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