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解决方案

IOT 过程质量控制和 IOT 镜头数据顾问

IOT 过程质量控制

采用适当的质量控制系统对于减少实验室内的错误至关重要。 通过确保满足质量标准,可以实现更高的产量。

借助 IOT 过程质量控制,您将能够验证所有生产过程操作是否处于最佳状态、机器是否正常运行以及使用正确的生产材料来确保质量。 此外,它还有助于检测制造过程中的错误,以便您做出适当的决策,从而提高运营效率。

IOT 过程质量控制 | 导师

一对一监控镜头质量

允许您检查镜片的质量以确保它们符合规定的标准,检测生产中的错误并发现需要改进的地方。

可靠且易于使用。 不需要技术知识。

一步一步的过程。 通过自动突出显示超出公差的值来显示测量顺序。

IOT 过程质量控制 | 分析

SPC* 分析工具

提供有关生产过程质量的统计信息。 促进数据驱动的决策制定,以改善生产并预测未来的问题。

小组或报告。 五个统计信息面板,帮助跟踪生产过程。

错误跟踪。 检测生产过程中发生错误的区域并确定纠正该情况的步骤。

IOT 过程质量控制
我们通过提供个性化建议、灵活的软件配置、质量控制和流程改进,帮助您为您的生产实施适当的质量控制系统。

* 统计过程控制。

IOT 过程质量控制 | 分析

通过数据了解和提高实验室整体绩效的分析工具。

信息面板:

1

随时间变化的状态

在与 NO-GO 镜头(不符合既定质量标准的镜头)设定的目标相关的时间序列中显示有关生产数量和质量的信息。

确定目标将帮助您了解与预期目标的偏差。
它允许您:

•   识别生产过程中不同日期或不同时间出现的问题。
•   确定导致问题的原因。
•   了解为提高质量而引入的改进的效果。
•    了解每种镜头的生产性能。
•   收集大量信息以改进整个生产过程。

No alt text available for image

每天/每周每小时生产的镜片数量。
生产的 NO-GO 镜片的百分比。
NO-GO 镜片的材料百分比。
按生产阶段和机器划分的 NO-GO 镜片百分比。
镜头设计类型。

2

NO-GO分析

检测 NO-GO 生产的原因,按镜头/材料类型确定优先级,并确定具体问题。

考虑到大多数错误是由几个因素引起的。 NO-GO 分析检测这些因素,并将分析重点放在每种材料上。 此外,它还可以确定在选择材料时特定机器的 NO-GO 百分比是否增加。

它使用处方过滤器来确定错误是影响高处方镜片还是低处方镜片,定位导致大量 NO-GO 的材料和机器,并检测两个 NO-GO 特征之间是否存在相关性。

例如:它缩小了生产中的主要问题,哪些材料导致了高达 80% 的错误,以及哪台机器对这些错误负责。

No alt text available for image

按材料划分的 NO-GO 镜片数量。
每个阶段和机器的 NO-GO 镜头分布。
每个评估特征中的 NO-GO 百分比。
显示分布变化的视觉交互。

3

改进领域

通过对镜头类型和产生误差的主要原因进行分类,轻松找到需要关注的领先指标。

它在具有最佳性能的镜头之间进行比较。 它分析可能影响其余部分的原因,以确定问题是特定于镜头类型,还是由于一般问题,例如需要维护的机器故障。

No alt text available for image

NO-GO 镜头的数量。
累积 NO-GO。
主要分析轴:材料、机械和 NO-GO 特征。

4

比较工具

比较两组不同镜片的性能,通过隔离机器、生产线、材料或处方来定位错误,并简单地进行所有可能的组合。

一个简单的工具,用于验证获得的结论是否有效。 它应用过滤器来隔离,例如,一组镜头,并证明它是否是导致错误的原因,确定其特性和需要改进的方面。

可以通过一种非常直观的方式查看两组镜片之间的比较,此外,它还可以让您确定哪些设备随着时间的推移具有最佳质量。

No alt text available for image

NO-GO 百分比的每日或每周变化。

5

镜头细节

组装完整的生产信息列表并允许将其导出到电子表格。

它定位特定的客户工作,识别错误(偏差)的大小,获取自定义参数,并导出数据以供任何其他类型的进一步分析。

No alt text available for image

NO-GO 镜头数量
日期 - 材质 - 镜头类型
过程 - 机器 - 状态

IOT 镜头数据顾问

IOT 镜片数据顾问是一个系统,可以为每位佩戴者计算理想的渐进镜片,同时考虑到以前渐进镜片佩戴者的满意度。

借助数据分析和机器学习技术,IOT Lens Data Advisor 最大限度地提高了每次新验配的成功机会,提高了患者的最终满意度。 在眼科行业中,第一次实现了一个可以随着时间的推移学习和发展的客观系统——以佩戴者的反馈为指导——已经实现。

推荐镜头设计的挑战

最好的镜片是满足患者期望并为他们提供最大满意度的镜片。 然而,今天没有全面的模型或临床研究可以提供佩戴者满意度(与他们的个人特征)和镜片满意度之间的明确联系。 推荐设计的决定通常基于从业者自己的经验。 它可以通过诸如以前的错误和成功、患者的反馈或其他指导等因素来推断。

IOT Lens Data Advisor 源于需要为视觉专业人士提供一个系统,该系统能够根据客观数据为每位佩戴者计算最佳镜片。

IOT Lens Data Advisor 是一个原创的专利解决方案。 它是在眼科镜片行业使用机器学习的先驱。

IOT 镜头数据顾问 | 算法

IOT Lens Data Advisor 包括一个决策算法。 一系列指令,代表用于计算理想渐进镜片的解决方案模型,保证高满意度。 该算法考虑了诸如处方、以前使用渐进镜片的经验、生活方式和满意度等方面的因素。

基于机器学习的客观决策

IOT Lens Data Advisor 通过系统地向每位新佩戴者学习而成长和发展。 由于机器学习 (ml) 技术,它从一个静态系统变成了一个活的系统,旨在智能地模拟与患者相关的不确定性。 它考虑他们的满意度,识别对其产生最显着影响的变量以及要推荐的设计。 通过这种方式,我们设法改进了当前的系统,并且佩戴者可以获得更好的镜片设计。

IOT 镜头数据顾问提供什么?

为配镜师提供简单有效的解决方案。
一个复杂的高科技平台,可帮助您将自己定位在最高水平。
一种自动系统,可减少重拍并纠正拒绝。
镜头的最新创新。
建立忠诚度。

患者资料

每个患者在 IOT Lens Data Advisor 平台上都有一个独特的个人资料,具有特定的特征和需求,包括他们的生活方式、以前的镜片经验、期望、处方、建议的镜片数据以及他们的满意度。所有这些匿名数据,经过充分组织和处理,生成一个用于检测模式和行为、预测情况、预测决策和计算理想镜头的数据库,为最终客户提供更好的体验。
根据以前患者的满意度,系统通过搜索与他们自己相似的配置文件来计算佩戴者最喜欢的镜片:相似配置文件。

可以先验地知道哪个镜片对每个佩戴者来说是最好的。由于佩戴者的不断流动和适当的机器学习技术,我们可以制造出最令人满意的镜片。通过分析以前佩戴者的行为并考虑他们的满意度,IOT Lens Data Advisor 为专业人士提供了一个计算正确镜片设计的系统。它还有助于解决那些满意度低或拒绝的案例。 IOT Lens Data Advisor 在提供更好的镜片以提高满意度和改善佩戴者体验方面取得了突破。

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作为原则,我们与您分享我们的知识。 这是改进我们共同开发的产品和技术的最微小细节的唯一方法。 需要时联系我们。 我们都是耳朵。

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We hereby inform you that if you reject the installation of cookies or disable these in your browser settings, certain services may not be available to you and therefore you may not be able to gain access to certain services and/or make full use of this Website http://www.iotlenses.com.

 

 

We last changed this policy on: July 16, 2024