AWS IoT SiteWise Edge
Collect, process, and monitor industrial equipment data on-premises
AWS IoT SiteWise Edge software makes it easy to collect, organize, process, and monitor equipment data on-premises. It enables factory operators to get visibility into their equipment data and make decisions that help improve equipment uptime, product quality, and process efficiency. SiteWise Edge is installed on local hardware such as third-party industrial gateways and computers, or on AWS Outposts and AWS Snow Family compute devices. Since SiteWise Edge runs on-premises, local applications that use data from SiteWise Edge will continue to work even during intermittent cloud connectivity.
Unlock industrial data from disparate equipment and sensors
Securely connect to and read data from equipment or local industrial data stores such as historian databases. SiteWise Edge includes built-in data collection capabilities to read multiple time-series data streams from equipment and historian databases using industrial protocols and standards such as OPC-UA, EtherNet/IP, and Modbus TCP.
Build hybrid industrial applications that work seamlessly across edge and cloud
Use the same asset models and service APIs across both edge and cloud environments to organize and process data for your edge and cloud applications. This provides a consistent user experience to your customers while reducing your development costs.
Process, store, and use your data wherever you need it
Process your industrial data locally into metrics that indicate the health and performance of your industrial operations. With SiteWise Edge, you can choose to process and use your equipment data locally to help comply with data residency requirements or for use by local edge applications. You can also selectively send processed or unprocessed equipment data to AWS IoT SiteWise or your industrial data lakes in the cloud for further analysis and longer-term storage.
Monitor processes through local web applications
Create monitoring dashboards without writing any code or SQL queries, and access them locally. With SiteWise Edge, process engineers can visualize and monitor equipment data in real time using SiteWise Monitor applications to support quick decision making on the factory floor—even when temporarily disconnected from the internet.
How It Works
Production and asset optimization
Industrial customers are increasingly looking to data-driven process improvements to increase production output. With AWS IoT SiteWise, you can compute metrics such as Overall Equipment Effectiveness (OEE), Mean Time Between Failures (MTBF), and Mean Time to Resolution (MTTR) from equipment state, quality count, and throughput data collected. These metrics help track the progress of smart manufacturing initiatives and find room for improvements. Now with AWS IoT SiteWise Edge, these metrics can be computed entirely on your on-premises gateway for local dashboards that must continue to operate even if the connection of the factory to the cloud is temporarily interrupted, ensuring that operators are able to identify bottlenecks as soon as they arise. Computed metrics can also be sent to the cloud from all production operations to compare results across multiple sites.
Product quality with real-time analytics
Catching product defects quickly during the manufacturing process can help reduce waste arising from units that must be rejected due to quality issues. To identify defect causing conditions in real-time, local applications can be developed that combine data from equipment, secondary sensors, enterprise resource planning (ERP) systems, and manufacturing execution systems (MES) data sources. These applications can now read equipment and sensor data from AWS IoT SiteWise Edge as it is collected on the gateway, and then further analyzed through machine learning models to identify anomalies that can be used to trigger alerts for staff on the factory floor.
Product and acceptance testing
Often, automotive, electronics, and aerospace products need to be acceptance tested before they are shipped to the customer. For example, a heavy-duty truck engine may be run at full throttle to ensure readiness for the road. Such tests can generate thousands of data points per second from multiple sensors embedded in the product and the testing equipment. While this data needs to be processed in real-time for the test operators, not all of it may need to be stored longer term. For example, it might be sufficient to store a single data point per second for each of the sensors. With AWS IoT SiteWise Edge, you can process data locally for real-time dashboards and just store the results in the cloud to optimize your bandwidth and storage costs.
Coca-Cola İçecek (CCI), one of the key bottlers in the Coca-Cola system, produces, distributes, and sells sparkling and still beverages of The Coca-Cola Company to 10 countries across Turkey, Pakistan, central Asia, and the Middle East, serving more than 400 million consumers. As part of CCI’s digital strategy and vision, the company used Amazon Web Services (AWS) to transform its 26 bottling plants. During the project’s first phase, CCI used AWS Professional Services to build a solution for its clean-in-place (CIP) process, a critical sanitation process in the food and beverage industry that cleans interior surfaces of production lines and equipment without disassembly. CCI needed a way to collect and process enormous amounts of industrial data as well as build digital models of clean-in-place (CIP) assets and processes. To ingest equipment data for processing, CCI used AWS IoT SiteWise, which ingests a large amount of data from CCI plants and enables operators to monitor processes at the edge using Grafana dashboards, an open-source analytics and interactive visualization web application. CCI built the CIP digital solution in 2 months. Within 4 months of deployment, CCI identified over 30 improvement opportunities that resulted in annual savings of 20 percent on electricity and 9 percent on water. Additionally, CCI estimates it will save 34 days of processing time per year using the digital twin solution, which will reduce overhead costs and further increase efficiency.
“We knew this was going to be a comprehensive solution that involved multiple aspects, such as data modeling, processing, and performance,” says Elif Ege, digital twin product manager at CCI. “AWS offered a flexible suite of services and provided the level of support we needed to build a scalable and configurable solution.”
Learn how AWS Partner hardware provides a streamlined industrial data collection process with qualified devices in the AWS Partner Device Catalog. Discover AWS Partner solutions in the AWS IoT Solution Repository to optimize factory output, improve product quality, maximize asset utilization, and identify equipment maintenance issues.
“Atos Smart Factory services help manufacturers of all sizes to exploit digital technologies to be more responsive to change. Our customers are now looking to scale their smart factory initiatives and proof of concepts to drive improved business performance through better asset utilization, increased uptime and real time decision making while reducing operational costs. AWS IoT SiteWise Edge is a key enabler in IIoT-centric use cases as it provides intuitive capabilities for collecting, storing, and organizing industrial data based on asset type and corresponding data models. This accelerates time to market as development effort focuses firmly on building data driven applications to address customer business challenges. Depending on the complexity and the scale of the use case, Atos expects the integration of AWS IoT SiteWise Edge in its smart factory reference architecture to reduce time to value for industrial applications from months to weeks.”
Adil Tahiri, CTO, Atos Manufacturing
"Most industrial customers have heterogeneous environments within their factories which makes it difficult to acquire data for IIoT application, especially on a large scale. By adding a Plug & Play connector to AWS IoT SiteWise, CloudRail already reduced the time to connect a machine to AWS from weeks to just minutes. With AWS IoT SiteWise Edge software, customers can now bring many great features of AWS IoT SiteWise right into their factory and benefit from local dashboards for immediate operator feedback or data pre-processing, even if the internet connection goes down."
Felix Kollmar, CEO of CloudRail
"As a Premium Consulting partner for AWS, Cognizant leverages AWS IoT SiteWise Edge, bringing out-of-the-box connectivity to industrial machines and production systems, as well as facilitating advanced analytics for fault detection and visual inspection at the edge. With AWS IoT SiteWise Edge we can define hierarchy and information models to create KPIs with low-code/no-code implementation and provide seamless integration between the edge and cloud. Cognizant is helping customers develop solutions in a cost-effective manner that adhere to security and compliance requirements leveraging AWS IoT SiteWise’s powerful capabilities, which can be deployed on existing server grade edge hardware."
Anjali Deo, AVP IoT, Cognizant
“We’re excited about the introduction of AWS IoT SiteWise Edge as it extends the power of AWS IoT SiteWise from the cloud to the edge and provides additional options for our customers to configure a solution based on use case needs, regulatory compliance mandates, and latency requirements. It is a logical extension to our portfolio of solutions from cloud into edge which our customers have been requesting.”
Usha Nandigala, Vice President of Business Development, DT4o
“Harnessing data from the production lines can empower enterprises with timely insights to optimize and streamline manufacturing operations. AWS IoT SiteWise Edge unleashes the power of ‘edge decisions’ by empowering teams to focus on quick decision making on the factory floor by simplifying complex data acquisition and processing activities. At LTI, we are excited to be the launch partner of AWS IoT SiteWise Edge and look forward to enabling our clients with our deep expertise and strong partnership with AWS.”
Siddharth Bohra, Chief Business Officer & Head of Cloud Business Unit, LTI
“Many IoT engagements don’t progress because of complications in hardware with multiple different sensor types in use, and the requirement for data loggers and edge compute. Additionally, clients face the prospect of sending millions of meaningless data points to the cloud, and in turn require a BI and data science team to present and interpret the data. Using AWS IoT SiteWise Edge in Storm Reply’s AMP solution removes all of these issues by inferring the data at the edge and presenting that data in real-time to the production line managers and operations team on the factory floor. AWS IoT SiteWise Edge also ensures onsite operations teams can still see this data even in sites with poor connectivity or if the asset being monitored is mobile.”
Matt Mould, Partner, Storm Reply UK
“At Synadia, we suggest gathering information from multiple data sources and taking advantage of machine learning models and visualization platforms to uncover new ways to optimize processes. We use AWS IoT SiteWise Edge for data gathering on-premises and on top of that we put the advanced analytics in place. This enables our customers to solve previously impenetrable problems and reveal issues that customers did not even know about, such as hidden bottlenecks or unprofitable production lines. AWS IoT SiteWise Edge provides us with the necessary toolset for data gathering and analytics sites where factory owners cannot be fully dependent on their internet connection."
Remi van Wijngaarden, Founder, Synadia
"Our customers have hundreds or thousands of machines, but need a solution to turn their abundant IoT data into useful actionable insights. TensorIoT uses AWS IoT SiteWise Edge to improve our SmartInsights advanced IoT analytics product and other solutions by providing local processing and "always-on" capabilities, especially critical to deployments in remote areas with intermittent or limited internet connectivity. Further, AWS IoT SiteWise Edge reduces the complexity of providing high-performance, low-latency dashboards on location. This makes it easier to provide immediate feedback to workers and managers alike about the state of a site's operations. Improving the visibility of industrial processes provides our customers with the critical information required to increase output and optimize resource utilization."
John Traynor, VP of Products, TensorIoT