Sight Machine
Canvas Category Software : Information Technology : Asset Performance Management
Sight Machine is the data platform for manufacturing, unlocking plant data to help manufacturers improve profitability, productivity, and sustainability. Using Sight Machine’s common Data Foundation for operations and analysis, manufacturers can make better, faster decisions for improving production performance. Sight Machine’s streaming platform continuously analyzes all assets, data sources, and processes, from machine to enterprise level.
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Microsoft introduces new adapted AI models for industry
We’re announcing adapted AI models, expanding our industry capabilities and enabling organizations to address their unique needs more accurately and effectively. In collaboration with industry partner experts like Bayer, Cerence, Rockwell Automation, Saifr, Siemens Digital Industries Software, Sight Machine and more, we’re making these fine-tuned models, pre-trained using industry-specific data, available to address customers’ top use cases.
Underpinning these adapted AI models is the Microsoft Cloud, our platform for industry innovation. By integrating the Microsoft Cloud with our industry-specific capabilities and a robust ecosystem of partners, we provide a secure approach to advancing innovation across industries. This collaboration allows us to create extensive scenarios for customers globally, with embedded AI capabilities — from industry data solutions in Microsoft Fabric to AI agents in Microsoft Copilot Studio to AI models in Azure AI Studio — that enable industries to realize their full potential.
LS ELECTRIC uses data to optimize power consumption with Sight Machine and Microsoft Cloud for Manufacturing
LS ELECTRIC, in collaboration with Sight Machine and Microsoft, is revolutionizing manufacturing sustainability and productivity through data optimization. By standardizing unstructured data, LS ELECTRIC gleans detailed insights into energy consumption, leading to a 20% reduction in power use on some manufacturing lines and integrating systems for better decision-making. This partnership drives towards a future of sustainable manufacturing, leveraging Microsoft Cloud for Manufacturing and Microsoft Copilot to drive efficiency and competitive operation.
LS ELECTRIC has already implemented the new solution in one of their factories and plans to roll it out to multiple facilities. The early results have been impressive: streamlined issue resolution, improved resource optimization, and greater agility in implementing and adapting to new inputs. By monitoring energy usage per production line, Dr. Wook-Dong Cho reports, “LS ELECTRIC has reduced power consumption by about 20% to certain manufacturing lines.”
Sight Machine on Microsoft Cloud for Manufacturing Brings Contextualized Manufacturing Data into the Data Estate
Sight Machine Inc., provider of the leading platform for manufacturing data and industrial AI, today introduced a manufacturing data solution for integrating contextualized production data into Microsoft Fabric.
Bringing Sight Machine’s data and its analytics tools, including Factory CoPilot, into Microsoft Fabric enables companies to combine and analyze contextualized manufacturing data with financial, supply chain, ERP and MES data, enabling unprecedented levels of knowledge and enterprise-wide insight.
Sight Machine for Siemens Industrial Edge Brings Manufacturing AI to Factory Automation Systems
Sight Machine Inc. and Siemens AG announced a partnership bringing manufacturing AI to on-premises automation networks.
Bringing Sight Machine’s advanced data models and analytics into on-premises systems opens the opportunity for software-defined automation and closed-loop systems. Sight Machine’s software analyzes the entire history of production runs to determine the best settings for the current conditions. These Dynamic Recipes are available to guide operators to integrate with control systems for automated optimization. Sight Machine is now a certified Industrial Edge Solution Partner of Siemens Digital Industries Factory Automation.
TeamViewer to drive smart factory innovation with strategic investments in manufacturing analytics and IoT
TeamViewer, a leading global provider of remote connectivity and workplace digitalization solutions, today announced strategic investments in two pioneering companies for smart factory solutions: Sight Machine and Cybus. With a total investment of a low double-digit million EUR amount, the company is strengthening its commitment to the digital transformation of industrial working environments and the convergence of Information and Operation Technology (IT & OT).
LS ELECTRIC and Sight Machine Collaborate to Build AI-Based Big Data Analytics Platform for Manufacturing and Energy
LS ELECTRIC announced on September 18 that it has signed an MOU with Sight Machine to build an AI-based intelligent manufacturing and energy big data analysis platform at LS ELECTRIC Cheongju, Chungbuk, Korea. With this MOU, the two companies plan to conduct extensive collaboration in the field of integrated platforms aimed at the ESG market, including verification and analysis of manufacturing-energy big data connectivity using Sight Machine’s Manufacturing Data Platform, prediction of AI-based manufacturing process equipment control values, and construction of big data analysis platforms to help companies achieve smart manufacturing and power efficiency in the production process.
📊 Simplify and Accelerate IoT Data-Driven Innovation
Databricks is thrilled to announce strategic partnerships to deliver specialized expertise and unparalleled value to the industry. These partnerships allow companies to simplify access to complex datasets, generate actionable insights and accelerate the time to value with the Lakehouse platform.
Seeq, a global leader in advanced analytics for the process manufacturing industries, delivers self-service, enterprise SaaS solutions to accelerate critical insights and action from historically unused data. Sight Machine enables real-time data-driven operations for manufacturers to achieve breakthrough performance by continuously improving profitability, productivity, and sustainability. Kobai delivers unparalleled semantic capabilities to unify operational and enterprise data and empowers all users to make better decisions and drive operational excellence. Companies across the Fortune 500 leverage Plotly’s powerful interactive analytics and visualization tools to build and scale production-grade data apps quickly and easily.
Sight Machine Factory CoPilot Democratizes Industrial Data With Generative AI
Sight Machine Inc. today announced the release of Factory CoPilot, democratizing industrial data through the power of generative artificial intelligence. By integrating Sight Machine’s Manufacturing Data Platform with Microsoft Azure OpenAI Service, Factory CoPilot brings unprecedented ease of access to manufacturing problem solving, analysis and reporting.
Using a natural language user interface similar to ChatGPT, Factory CoPilot offers an intuitive, “ask the expert” experience for all manufacturing stakeholders, regardless of data proficiency. In response to a single question, Factory CoPilot can automatically summarize all relevant data and information about production in real-time (e.g., for daily meetings) and generate user-friendly reports, emails, charts and other content (in any language) about the performance of any machine, line or plant across the manufacturing enterprise, based on contextualized data in the Sight Machine platform.
Microsoft Cloud for Manufacturing: Tackling data accessibility in manufacturing alongside partners
I’m very excited about all the updates being shared at Microsoft Inspire 2023, particularly about the announcement of the new AI Cloud Partner Program (MACPP) and the additional offerings and benefits this brings for partners. Under the MACPP, I’m thrilled to announce that we will be including manufacturing partner solutions through new independent software vendor (ISV) designations.
This designation represents our commitment to bringing the best partner solutions to our customers and provides a way for customers to identify proven partner solutions aligned with the Microsoft Cloud and our industry clouds. The designation validates that our partners’ solutions meet the high standards of data accessibility specific to the manufacturing industry.
Sight Machine Blueprint Enables Automated Data Labeling and Comprehensive Analysis of All Manufacturing Data
Sight Machine, creator of the data foundation for manufacturing, today announced that it has released Sight Machine Blueprint, a tool developed in collaboration with NVIDIA and Microsoft that provides manufacturers with high-speed, automated data labeling, mapping data tags to plant assets and the context they need to interpret their plant data. Blueprint makes it possible, for the first time, for manufacturers to analyze all their plant data, leading to improved outcomes in throughput, quality and sustainability.
“Microsoft Azure Machine Learning, combined with Sight Machine and advanced technology from NVIDIA, provides the infrastructure to easily scale GPU-based machine learning pipelines,” said Indranil Sircar, CTO, Manufacturing at Microsoft. “This combination in Sight Machine Blueprint will help eliminate manufacturers’ massive time drain from manually labeling data, and enable them to tap into the full wealth of data at their fingertips for business impact through true analytics-driven decision-making.”
Common Data Models for Manufacturing
- Sight Machine analyzes production by streaming plant floor data from all systems and sources in real time
- Data is streamed into 4 Common Data Models. These models represent automated production in all industries
- Streams continuously generate Data Foundation. Data Foundation is then graphed into representations of machines, lines and plants, which are further visualized and analyzed in KPIs, analytics and AI/ML
- Sight Machine’s architecture is modular, transparent, and configurable at each level. Clients and partners can access and modify: (a) raw data, (b) configuration, and (c) Transformed Data via API and SDK layers
- This presentation reviews Common Data Models and graphing methods, and highlights a few out of hundreds of analytics currently generated through web services. After several introductory slides, it is mostly pictures
- Connectivity and pre-processing, and streaming and transformation are addressed elsewhere
Sight Machine, NVIDIA Collaborate to Turbocharge Manufacturing Data Labeling
The collaboration connects Sight Machine’s manufacturing data foundation with NVIDIA’s AI platform to break through the last bottleneck in the digital transformation of manufacturing – preparing raw factory data for analysis. Sight Machine’s manufacturing intelligence will guide NVIDIA machine learning software running on NVIDIA GPU hardware to process two or more orders of magnitude more data at the start of digital transformation projects.
Accelerating data labeling will enable Sight Machine to quickly onboard large enterprises with massive data lakes. It will automate and accelerate work and lead to even faster time to value. While similar automated data mapping technology is being developed for specific data sources or well documented systems, Sight Machine is the first to use data introspection to automatically map tags to models for a wide variety of plant floor systems.
2021 IW Best Plants Winner: IPG Tremonton Wraps Up a Repeat IW Best Plants Win
“If you wrapped it and just wound it straight, it would look like a record, with peaks and valleys,” says Richardson. So instead, the machines rotate horizontally, like two cans of pop on turntables. Initially, IPG used a gauge that indicated whether the film was too thick or too thin. “That was OK,” says Richardson, “but it didn’t get us the information we needed.”
Working with an outside company, IPG Tremonton upgraded the gauge to one that could quantify the thickness of the cut plastic in real time as the machine operates.
The benefits of the tinkering were twofold. First, the upgrade gave operators the ability to correct deviations on the fly. Second, “we found that we had some variations between a couple of our machines,” Richardson says. Using the new gauge on both machines revealed that one of them was producing film “a few percentage points thicker” than its twin. “We [were] basically giving away free product,” Richardson recalled. The new sensor gave IPG the information it needed to label film more accurately.
Strategic Analytics Help Intertape Polymer Shrink Inefficiencies
For Intertape Polymer Group (IPG), a global manufacturer of packaging and protective solutions for industrial and e-commerce applications, the digital transformation process has always been about embracing technology with a keen eye on extracting the overall business value. As such, IPG is currently at different levels of maturity across the portfolio of digital technology deployments, including additive manufacturing, AR/VR training, IoT-based predictive downtime and robotic process automation.
IPG has taken advantage of the unique data modeling capabilities of the Sight Machine platform, which continuously transforms all data types generated by factory equipment and manufacturing software into a robust data foundation for analyzing and modeling a plant’s machines, production processes and finished products.