re:Invent 2020 – Manufacturing and Industrial Recap

AWS re:Invent 2020, the biggest cloud computing event of the year, kicked off its second wave of free virtual content and announcements on January 12th-14th, 2021. The manufacturing and industrial team brought industry leaders together to discuss how they leverage cloud technology to digitally transform their business with the help of AWS.

In this post, we’ll cover highlights of the show as well as the important announcements for industrial, and especially, manufacturing customers.

In the first week of re:Invent, early December, we featured two recorded sessions with industry leaders General Electric and Georgia Pacific:

• AWS on Air 2020: Industry Live Manufacturing – AWS on Air host Nick Walsh talks with Naren Gopalkrishna, Principal Product Manager, Manufacturing at GE Digital in the AWS Industry Live GE Digital session.
• AWS on Air 2020: Voice of the Customer – Georgia Pacific – Aileen Gemma Smith, Head of Developer Advocacy, Americas and Online talks with Roshan Shah, VP Digital Transformation, Georgia Pacific discusses how Georgia Pacific uses a large number of AWS services to create data lakes, and optimize operations

In early January 2021 we kicked off wave two of re:Invent with six breakout sessions for the industrial and manufacturing audience:

• MFG201: Terex improves quality and optimizes production with AWS: Hear from VP of IT – Aerial Work Platforms, Scott McNeal from Genie (a Terex Brand) how Genie is digitizing their production and products to drive operational efficiency and new customer offerings.
• MFG202: Simulating city-scale transport behavior with AWS: Learn how Arup’s City Modeling capability is helping plan for the future using open agent based model (ABM) approaches to simulate individuals’ activity and travel behavior in cities and countries. See how AWS allows simultaneous simulations running in parallel to explore the hyperparameter space and run at the scale required.
• MFG301: 3M optimizes global materials tracing with AWS: See how American multinational conglomerate corporation 3M users quickly build secure, self-service reporting for questions on raw materials and finished goods, plus how they glean valuable insights from this data, and how they use it to optimize operations.
• MFG302: Hyundai builds smart services and solutions for its connected machinery: Hear from Hyundai Construction Equipment about its experience building Hyundai Connect, the smart service for heavy equipment machines that makes their customers’ equipment and job site operations more efficient, economic, and convenient.
• MFG303: Rivian pushes the pace of automotive innovation with AWS: Learn how Rivian reshaped its simulation and modeling R&D operations with AWS to decrease time to market using open source frameworks, the near limitless scale of AWS compute, and other next-generation AWS technologies to speed engineer and analyst innovations.
• MFG304: Semiconductor design on AWS with guest speaker Qualcomm: Hear Qualcomm discuss running workflows on AWS, and we’ll also outline how AWS is working across the entire semiconductor industry to enable innovation and scale workflows.

New industrial services announced

In the early weeks of re:Invent, we announced numerous purpose-built AI and ML services created to make it easier for manufacturers to use data to improve industrial operations with speed and accuracy, and to address industrial use cases that require near real-time decision making.

These services were born out of the complex automation and factory operations of Amazon, and designed to enable customers to use machine data to predict when equipment will require maintenance, and to use computer vision (such as images from existing camera feeds) to improve processes, identify bottle necks, and detect anomalies, in real-time – with no machine learning expertise required.

Using machine data to predict when equipment will require maintenance:

Amazon Lookout for Equipment: AWS Lookout for Equipment is an anomaly detection service for industrial machinery. It uses data from equipment tags and sensors, and historical maintenance events to detect abnormal equipment behavior.

Amazon Monitron: Amazon Monitron is an end-to-end system that detects abnormal behavior in industrial machinery, such as motors, gearboxes, fans, and pumps, to enable customers to implement predictive maintenance and reduce unplanned downtime. It includes sensors to measure vibration and temperature, a gateway device, and a mobile app to set up devices and track and review potential issues with equipment.

Using computer vision to improve processes, identify bottle necks and detect anomalies:

Amazon Lookout for Vision: Amazon Lookout for Vision enables customers to spot industrial product defects and anomalies using computer vision, accurately and at scale. Customers can automate real-time visual inspection for processes like quality control and defect assessment by analyzing images from cameras that monitor the process line. Amazon Lookout for Vision identifies missing components, damage to products, irregularities in production lines, and even minuscule defects in silicon wafers such as a missing capacitor on a printed circuit board.

AWS Panorama: AWS Panorama is a machine learning appliance and SDK, which enables customers to add computer vision (CV) to existing on-premises cameras or to new Panorama enabled cameras. It gives customers the ability to make real-time decisions to improve operations, automate monitoring of visual inspection tasks, find bottlenecks in industrial processes, and assess worker safety within facilities.

• The AWS Panorama Appliance turns existing onsite cameras into powerful edge devices with the processing power to analyze video feeds from multiple cameras in parallel, and generate highly accurate predictions within milliseconds. With a dust resistant and waterproof appliance, customers can install devices in different environments without compromising functionality.
• The AWS Panorama SDK enables hardware partners to build new AWS Panorama-enabled devices that run more meaningful CV models at the edge, and offer a selection of edge devices to satisfy different use cases. New Panorama-enabled devices are coming soon from partners including ADLINK Technology, Axis Communications, Basler AG, Lenovo, STANLEY Security, and Vivotek.

Using AWS to securely collect, integrate, organize, and store massive industrial data sets even with limited connectivity:

Industrial companies today have more operational data than ever before; however, securely accessing, collecting, and organizing massive industrial data sets is difficult, and often requires new tools to improve systems and processes in industrial low-latency environments. Customers use AWS compute, storage, and database services to build their single source of data truth, and use AWS IoT services to securely collect, organize, and monitor industrial data at scale.

AWS IoT SiteWise: AWS IoT SiteWise is a managed service that makes it easy to collect, store, organize, and monitor data from industrial equipment at scale to help customers make better, data-driven decisions in optimizing their operations.

AWS Snowcone: AWS Snowcone is the smallest member of the AWS Snow Family of edge computing, edge storage, and data transfer devices. It is ruggedized, secure, and purpose-built for use outside of a traditional data center, and its small form factor makes it a perfect fit for tight spaces or where portability is a necessity. Customers can execute compute applications at the edge, and can ship the device with data to AWS for offline data transfer, or can transfer data online with AWS DataSync from edge locations.

AWS Snowball Edge: AWS Snowball Edge, a part of the AWS Snow Family, is an edge computing, data migration, and edge storage device that customers use for data collection, machine learning and processing, and storage in environments with intermittent connectivity or in extremely remote locations before shipping them back to AWS.

AWS Outposts: AWS Outposts is a fully managed service that offers the same AWS infrastructure, AWS services, APIs, and tools to virtually any datacenter, co-location space, or on-premises facility for a truly consistent hybrid experience. AWS Outposts is ideal for workloads that require low latency access to on-premises systems, local data processing, data residency, and migration of applications with local system interdependencies.

Amazon Lake Formation: Setting up and managing data lakes involves manual and time-consuming tasks such as loading, transforming, securing, and auditing access to data. AWS Lake Formation automates many of those manual steps and reduces the time required to build a successful data lake using Amazon S3, from months to days.

Using AWS for cloud management, and optimizing engineering workloads for improved price performance:

Reduce friction when integrating with a hybrid cloud environment with Amazon EKS, ECS Anywhere, and AWS Lambda container image support.

Amazon EKS and Amazon ECS Anywhere bring a consistent AWS management experience to customers’ data centers. Amazon EKS and Amazon ECS Anywhere save you the complexity of buying or building your own management tooling to create clusters, configure the operating environment, update software, and handle backup and recovery. These services also enable automated cluster management and reduced support costs, and eliminates the redundant effort of using multiple open source or third party tools for operating Kubernetes clusters.

Additionally, AWS Lambda now supports packaging and deploying functions as container images, so you can easily build Lambda-based applications by using familiar container image tooling, workflows, and dependencies.

Optimize costs by upgrading to the latest instance and storage types:

The new general purpose (M6g), general purpose burstable (T4g), compute optimized (C6g), and memory optimized (R6g) Amazon EC2 instances deliver up to 40% improved price performance over comparable x86-based instances for a broad spectrum of workloads. The new storage-focused D3 and D3en instances offer 100% higher disk throughput, 7x more storage capacity (up to 336 TB), and 80% lower cost per-TB of storage compared to D2 instances.

Lastly, gp3, the next-generation general purpose SSD volumes for Amazon Elastic Block Store (Amazon EBS) lets you provision performance independent of storage capacity, and offers up to a 20% lower price-point per GB than existing gp2 volumes. With gp3 volumes, you can scale IOPS (input/output operations per second) and throughput without needing to provision additional block storage capacity, and pay only for the resources needed.

In closing, AWS continues to show leadership in the industrial space with new purpose-built industrial services, new solutions, and an expanding set of partner solutions. Industrial customers have one place they can go to for their industrial edge and cloud needs, whether it’s to start building their own custom industrial applications using purpose-built AWS services, or to jump-start their time to value with AWS solutions and partner solutions.

To learn more or get started, explore the AWS Industrial and Manufacturing pages.