Sight Machine
概述
总部
美国
|
成立年份
2012
|
公司类型
私营公司
|
收入
< $10m
|
员工人数
51 - 200
|
网站
|
推特句柄
|
公司介绍
Sight Machine 专注于制造分析,并被全球 500 强公司用于对其运营做出更好、更快的决策。 Sight Machine 的分析平台专为离散和流程制造而构建,使用人工智能、机器学习和高级分析来帮助解决整个企业在质量和生产力方面的关键挑战。该平台由业界唯一的 Plant Digital Twin 提供支持,可为整个企业的每台机器、生产线和工厂提供实时可见性和可操作的洞察力。 Sight Machine 于 2011 年在密歇根州成立,并于 2012 年扩展到湾区,将硅谷技术创新的精神与坚如磐石的底特律制造相融合。我们的团队包括 Slashdot 的创始人以及早期雅虎、Palantir、特斯拉、思科、IBM、麦肯锡和苹果的领导层。
物联网解决方案
Sight Machine 平台Sight Machine 使公司能够获得整个制造企业中每个零件、机器、生产线和工厂的实时可见性和可操作的见解。我们的分析平台使制造商能够使用他们的所有数据——无论它是在何处或以何种格式创建的。我们通过自动化和系统化的数据获取流程来实现这一点,该流程获取、提炼和关联数据,为每个部分和流程创建一个数字双胞胎。制造分析应用程序通过提供高级分析来提高生产力、质量和供应链优化,从而解锁下一个数字制造水平。制造可视性应用程序在智能、安全和可扩展的平台上提供整个公司的工厂和机器性能的实时可视性。 FactoryTX Edge 和 FactoryTX Cloud FactoryTX Edge 和 FactoryTX Cloud 可帮助制造商在其整个企业中快速部署和扩展数字制造能力。
物联网应用简介
技术栈
Sight Machine的技术栈描绘了Sight Machine在平台即服务 (paas), 应用基础设施与中间件, 和 分析与建模等物联网技术方面的实践。
-
设备层
-
边缘层
-
云层
-
应用层
-
配套技术
技术能力:
无
弱
中等
强
Supplier missing?
Start adding your own!
Register with your work email and create a new supplier profile for your business.
实例探究.
Case Study
Digital Twin in Dairy Production
Manufacturers must cultivate the cheese like artisans but do so in enormous batches—thus the need for production know-how. Mass producing cheese requires machinery and elaborate processing plants that are difficult to manage. To better understand their operations, dairy companies are increasingly turning to data analytics.Chemists and engineers at the dairy plant were running into bottlenecks, especially in terms of:-The blend of protein and fat in the raw materials-The temperature of the batches coming out of the upstream cookers-The pH of output from the upstream fermentation process
Case Study
Digital Transformation of Essex Furukawa with Sight Machine
Essex Furukawa, the world’s largest manufacturer of magnet wire/winding wire, faced a significant increase in demand due to the rapid shift of global automakers towards electric power. The company needed to maintain its market leadership by increasing throughput and uptime while delivering high-quality products. The challenge was to meet the growing demands without compromising the quality of their products. The magnet wire they produce for electric vehicle motors must meet exacting standards to withstand years of severe stress, including high heat, high electrical current, and fast switching frequencies. Essex Furukawa leadership recognized the need for a digital transformation of their manufacturing plants to collect and analyze production data for predictive maintenance and continuous operational optimization.
同类供应商.
Supplier
Senseye
Senseye is the leading cloud-based software for Predictive Maintenance. It helps manufacturers avoid downtime and save money by automatically forecasting machine failure without the need for expert manual analysis. Its intelligent machine-learning algorithms allow it to be used on any machine from any manufacturer, taking information from existing Industrial IoT sensors and platforms to automatically diagnose failures and provide the remaining useful life of machinery.
Supplier
Seebo
Seebo is an Industry 4.0 SaaS platform with laser-focused business solutions that ‘move the needle’ for manufacturers in 3-months or less.Founded in 2012, the company has raised over $22M from Viola Ventures, TPY Capital, Pritzker Group, and other investors. Seebo was named a Gartner Cool Vendor in the Internet of Things for 2017.You can learn more by visiting our website: seebo.com or introduce Seebo to others with the following link: seebo.com/introducing-seebo.
Supplier
LLamasoft
Over 750 of the world‘s most innovative companies rely on LLamasoft to answer their toughest supply chain questions. Powered by the comprehensive set of supply chain analytics, LLamasoft technology helps business leaders design the supply chain they need to achieve their profitability, service, and growth goals. Breaking down the limitations of traditional planning and operational systems, LLamasoft creates a true end-to-end view of the global supply chain to reveal the optimal design, assess trade-offs and enable decision making across strategic, tactical and operational time horizons. LLamasoft customers have already identified how they can recapture over $13B in savings and the same technology is being used to solve some of the most complex supply delivery problems in developing nations. Partnering with humanitarian organizations, government entities and as part of the World Economic Forum, LLamasoft plans to positively impact 100 million lives by 2022.
Supplier
INOSIM
Inosim's vision is to empower decision-making in the processing industries with innovative simulation tools and tailored services to contribute to a sustainable future worth living in. They believe that simulation offers unparalleled levels of insight into complex processes and their prospective behavior. Leveraging this potential means making more confident decisions in process development and plant operations.