Microsoft has positioned itself as a premier platform provider for manufacturing applications for a long time. It lists as partners just about every industrial/manufacturing application developer. Recently, AVEVA announced it has reached a new level of competency within the Microsoft ecosystem.
AVEVA has attained a Gold Application Development competency and Silver Cloud Platform, Data Analytics, and Data Center competencies, demonstrating a ‘best-in-class’ ability and commitment to meet Microsoft customers’ evolving needs in today’s mobile-first, cloud-first world and distinguishing itself within a small percentage of the Microsoft partner ecosystem. A portfolio of competencies showcases that AVEVA is committed to focusing on on-demand, business solution areas, along with ensuring it can meet the evolving needs of our mutual customers.
To earn a Microsoft competency, partners must successfully complete exams (resulting in Microsoft Certified Professionals) to prove their level of technology expertise and, for Gold competencies, designate these certified professionals uniquely to one Microsoft competency, ensuring a certain level of staffing capacity. Partners must also submit customer references that demonstrate successful projects and pass technology and/or sales assessments. For gold competencies, partners must also implement a yearly customer satisfaction study and, for many competencies, meet a revenue commitment.
“AVEVA is enabling industrial organizations to embrace innovative digital platforms that will allow them to deploy faster, reduce energy consumption and emissions, and work more collaboratively,” commented Steen Lomholt-Thomsen, Chief Revenue Officer at AVEVA. “These Microsoft competencies not only showcase our technology expertise, but also demonstrate our commitment to supporting customers and embracing innovation. By deploying our solutions, customers can be empowered to deliver better business outcomes, which will in turn help to accelerate their own success.”
“By accomplishing a portfolio of competencies, partners demonstrate true commitment to meeting customer technology needs today and into the future,” said Gavriella Schuster, corporate vice president, Worldwide Partner Group at Microsoft Corp. “These partners’ proficiency and expertise of Microsoft technology is instrumental in helping our mutual customers continue to drive innovative solutions.”
All 17 Microsoft technology competencies differentiate a partner’s specific technology capabilities, helping customers find qualified solution providers with expertise in discrete areas quickly and easily.
Earning the Application Development competency helps partners differentiate themselves as a trusted expert to their customers through development and deployment of commercial or custom applications built using core Microsoft technologies like Windows Server and Windows 8 operating systems, the Windows Azure platform, Microsoft Visual Studio 2012 development system, Microsoft BizTalk Server and emerging cloud-based and web business models. By gaining access to a comprehensive set of benefits through the Application Development competency, partners can acquire new customers and help them be more productive and profitable through deployment of business applications, advanced web portals or rich client user interfaces that run on premises or in the cloud.
The Cloud Platform competency is designed for partners to capitalize on the growing demand for infrastructure and software as a service (SaaS) solutions built on Microsoft Azure. Differentiate your company with the Cloud Platform competency, and you will be eligible for Signature Cloud Support, Azure deployment planning services, Azure sponsored credit, direct partner support, eligibility to deploy certain on-premises, internal use software on Microsoft Azure, and access to the cloud platform roadmap.
The Data Analytics competency recognizes partners who demonstrate expertise in specific aspects of Microsoft BI solutions to deliver, deploy, and support BI projects. Differentiate your company with this competency and receive access to internal use software licenses, technical and presales support, training for your IT professionals, developers, incentives, and marketing through the Partner Marketing Center and Pinpoint. Strengthen relationships with your customers by becoming a provider of SQL Server deployment planning services or SharePoint deployment planning services.
The Datacenter competency recognizes partners who are transforming data centers into more flexible, scalable, and cost-effective solutions. Partners can deepen customer relationships by becoming a provider of Private Cloud, Management, and Virtualization Deployment Planning Services. Differentiate your company with this competency and receive access to internal use software licenses, technical and presales support, training for your IT professionals, incentives, and access to the Microsoft Partner server and cloud site with exclusive content and resources to help you win new deals to deliver projects successfully.
The Microsoft Partner Network helps partners strengthen their capabilities to showcase leadership in the marketplace on the latest technology, to better serve customers and to easily connect with one of the most active, diverse networks in the world.
Sparta’s AI-enabled software as a service (SaaS) quality management software (QMS) offering will combine with Honeywell Forge and Experion Process Knowledge System
Honeywell will leverage Sparta’s technologies to continue to drive global growth and expand into new market segments, including highly regulated verticals, that require advanced process technologies
Sparta’s technologies will accelerate Honeywell’s breakthrough initiative to further penetrate the life sciences market and strengthen Honeywell’s existing portfolio of advanced automation and process control technologies
It’s not only Apple and Google in technology consolidating the market and increasing their private portfolios. The same phenomenon is happening in the industrial space with the latest exhibit being this software acquisition by Honeywell.
Honeywell announced Dec. 22 it has agreed to acquire privately held Sparta Systems for $1.3 billion in an all-cash transaction from New Mountain Capital. Sparta Systems is a leading provider of enterprise quality management software (QMS), including a next-generation SaaS platform, for the life sciences industry.
The acquisition further strengthens Honeywell’s leadership in industrial automation, digital transformation solutions and enterprise performance management software.
Honeywell will leverage its global presence, Honeywell Forge and Sparta’s expertise to introduce new, integrated solutions, including QMS offerings, for life sciences and adjacent industries. Honeywell’s customers will benefit from advanced digital QMS solutions to help them proactively achieve better quality, which results in improved new therapies, faster time to market, better business and patient outcomes, and effective regulatory compliance.
“Sparta’s TrackWise Digital and QualityWise.ai are a welcome addition to Honeywell’s enterprise performance management software, Honeywell Forge, and will further enhance the link between quality and production data for life sciences manufacturers,” said Que Dallara, president and chief executive officer of Honeywell Connected Enterprise. “Our combined offerings will make it easier for customers to gain critical insights from manufacturing and quality data that can improve their manufacturing processes while ensuring product quality, patient safety, and supply chain continuity.”
Honeywell has provided the world’s leading drug manufacturers and biomedical firms with advancements in automation technologies, systems and services for more than 30 years.
Honeywell’s portfolio includes advanced automation and process controls; data capture and recording solutions that simplify and safeguard compliance; and technologies that help maintain auditability, optimize production, and speed time to market while ensuring quality and repeatability. Honeywell’s Fast Track Automation helps life science manufacturers expedite development and production of vital vaccines and medical therapies.
“Sparta Systems is an ideal complement to our life sciences portfolio,” said Rajeev Gautam, president and chief executive officer of Honeywell Performance Materials and Technologies. “While Sparta’s capabilities will initially help us expand our capabilities for our existing breakthrough initiative in life sciences, we plan to leverage Honeywell’s global footprint and expertise to quickly expand Sparta’s capabilities to serve other markets. We have strong conviction in the growth opportunities in the life sciences and pharmaceuticals space and in the synergies between Sparta and Honeywell both for Honeywell Connected Enterprise and Honeywell Forge as well as for Honeywell Process Solutions.”
Sparta Systems is headquartered in Hamilton, N.J., and has approximately 250 employees globally. Sparta serves more than 400 customers, including 42 of the world’s top 50 pharma companies and 33 of the top 50 medical device companies.
“Organizations need a quality management software solution with advanced digital capabilities that effectively automates, optimizes and standardizes quality processes across the board,” said Dana Jones, chief executive officer of Sparta Systems. “When you combine Sparta’s leading QMS platform with Honeywell’s existing process automation and software offerings, you create a highly differentiated, comprehensive solution that allows customers to focus more on the value-add activities that will accelerate their growth.”
Honeywell will continue to enhance TrackWise Digital QMS by adding AI and machine learning capabilities that augment human decision making. Honeywell will also add new IoT-enabled connectivity between quality and operational data to detect manufacturing anomalies and triage quality events in near real time. These continuing innovations will help customers proactively address quality to improve patient safety and effective regulatory compliance.
Pete Masucci, managing director of New Mountain Capital, said, “Since we partnered with Sparta in 2017, the company launched its TrackWise Digital platform – the only AI-enabled QMS solution, expanded its SaaS customer base by two-and-a-half times, and significantly invested in product development and R&D. We are excited to watch Sparta continue to thrive within the Honeywell organization.”
The acquisition is expected to close by the end of the first quarter of 2021 and is subject to certain regulatory approvals and other customary closing conditions. There is no change to Honeywell’s 2020 financial outlook as a result of the acquisition.
Combination of Onshape and Arena to Enable PTC to DeliverComplete CAD + PLM SaaS Solution
PTC Reaffirms Cash Flow Targets for FY’21
PTC announced Dec. 14 that it has signed a definitive agreement to acquire Arena Solutions, Inc. (Arena Solutions) “the industry’s leading software-as-a-service (SaaS) product lifecycle management (PLM) platform provider”.
I am not particularly surprised by this announcement. PTC needed to do something interesting with cash from some past investments. Jim Heppelmann, PTC CEO, clearly stated last year the company’s direction toward becoming a complete SaaS provider. In the IT world, HPE first and then Dell Technologies and Hitachi Vantara later, companies are rapidly moving to pretty much “everything-as-a-service”.
This may not be a market disrupter in itself, but the move definitely applies pressure to other PLM suppliers to change business models. Responses will be telling.
The acquisition will further PTC’s strategy to be the leader in the rapidly growing market for SaaS-based product development software, enabling the company to deliver a complete CAD + PLM SaaS solution. Under the terms of the agreement, PTC will acquire Arena Solutions for $715 million in cash. Subject to customary closing conditions and completion of regulatory review, the acquisition is expected to be completed in PTC’s fiscal Q2 2021.
“A year ago, PTC entered the SaaS world for product development software with our acquisition of Onshape,” said Jim Heppelmann, president and CEO, PTC. “That move reflected our strong conviction that our market is nearing a tipping point in its willingness to adopt SaaS technology, following the trend seen in many other software markets. The effects of COVID-19 have dramatically accelerated this inevitable shift, with PTC customer surveys indicating a 25% increase in readiness for SaaS PLM since the pandemic started. We expect the acquisition of Arena will significantly extend our leadership position as we continue to redefine the future of our industry.”
With headquarters in Foster City, California, Arena Solutions serves more than 1,200 customers across the electronics, high-tech, and medical-device industries, including world-class innovators such as Nutanix, Peloton, Sonos and Square. In addition, Arena will broadly extend PTC’s presence in the attractive mid-market, where SaaS solutions are becoming the standard.
“As the SaaS PLM pioneer, we were first to see that engineers and product developers would benefit from a new paradigm in the way they collaborate and drive product innovation,” said Craig Livingston, Arena Solutions president and CEO. “We were ahead of the market in the early days, but in the past several years we’ve seen an acceleration of market receptivity and demand. This acquisition validates our original vision, and we are pleased to be joining an established leader in CAD and PLM capable of hastening the movement of our market to SaaS.”
The Arena Solutions product realization platform unifies PLM, quality management, and requirements management, allowing every participant throughout the product design and manufacturing process – as well as across an extended supply chain – to work together in a secure, high availability cloud environment.
“This acquisition is the logical next step in PTC’s strategy to be the industrial SaaS leader,” continued Heppelmann. “A big first step was the acquisition of Onshape, the SaaS leader in CAD and collaborative design capabilities. Arena will enable us to round out the solution with full PLM capabilities and deliver the only complete CAD + PLM SaaS solution in the industry.”
Arena Solutions is expected to end calendar year 2020 with approximately $50 million in annualized recurring revenue, reflecting double-digit growth over 2019. The transaction is expected to be neutral to PTC’s FY’21 cash flow from operations target of $365 million and free cash flow target of $340 million (which reflects the deduction of approximately $25 million of capital expenditures from cash flow from operations) and accretive to FY’22 and beyond. The transaction will be funded with cash on-hand and amounts borrowed under PTC’s existing credit facility.
PTC management will provide additional details about the transaction at its Investor Day virtual meeting scheduled for Tuesday, December 15.
Centerview Partners LLC is the exclusive financial advisor to PTC and Morgan, Lewis & Bockius LLP is acting as its legal counsel. Barclays is the exclusive financial advisor to Arena and JMI Equity, and Goodwin Procter is acting as their legal counsel.
I have two Linux Foundation open source releases today. We connected through the EdgeX Foundry IoT platform. Then we discovered we had many common interests. One of the releases touches on a fundamental element of commerce and collaboration—trust. The Linux Foundation is an open source project. Open source is a powerful software development model. But, it takes many dedicated and talented people to accomplish the task. Why do people work on open source? LF conducted a survey to get an idea.
The Janssen Project Takes on World’s Most Demanding Digital Trust Challenges at Linux Foundation
New Janssen Project seeks to build the world’s fastest and most comprehensive cloud native identity and access management software platform
The Linux Foundation announced the Janssen Project, a cloud native identity and access management software platform that prioritizes security and performance for our digital society. Janssen is based on the Gluu Server and benefits from a rich set of signing and encryption functionalities. Engineers from IDEMIA, F5, BioID, Couchbase, and Gluu will make up the Technical Steering Committee.
Online trust is a fundamental challenge to our digital society. The Internet has connected us. But at the same time, it has undermined trust. Digital identity starts with a connection between a person and a digital device. Identity software conveys the integrity of that connection from the user’s device to a complex web of backend services. Solving the challenge of digital identity is foundational to achieving trustworthy online security.
While other identity and access management platforms exist, the Janssen Project seeks to tackle the most challenging security and performance requirements. Based on the latest code that powers the Gluu Server–which has passed more OpenID self-certification tests then any other platform–Janssen starts with a rich set of signing and encryption functionality that can be used for high assurance transactions. Having shown throughput of more than one billion authentications per day, the software can also handle the most demanding requirements for concurrency thanks to Kubernetes auto-scaling and advances in persistence.
“Trust and security are not competitive advantages–no one wins in an insecure society with low trust,” said Mike Schwartz, Chair of the Janssen Project Technical Steering Committee. “In the world of software, nothing builds trust like the open source development methodology. For organizations who cannot outsource trust, the Janssen Project strives to bring transparency, best practices and collective governance to the long term maintenance of this important effort. The Linux Foundation provides the neutral and proven forum for organizations to collaborate on this work.”
The Gluu engineering teams chose the Linux Foundation to host this community because of the Foundation’s priority of transparency in the development process and its formal framework for governance to facilitate collaboration among commercial partners.
New digital identity challenges arise constantly, and new standards are developed to address them. Open source ecosystems are an engine for innovation to filter and adapt to changing requirements. The Janssen Project Technical Steering Committee (“TSC”) will help govern priorities according to the charter. The initial TSC includes:
Michael Schwartz, TSC Chair, CEO Gluu
Rajesh Bavanantham, Domain Architect at F5 Networks/NGiNX
Rod Boothby, Head of Digital Trust at Santander
Will Cayo, Director of Software Engineering at IDEMIA Digital Labs
Ian McCloy, Principal Product Manager at Couchbase
Alexander Werner, Software Engineer at BioID
New Open Source Contributor Report from Linux Foundation and Harvard Identifies Motivations and Opportunities for Improving Software Security
New survey reveals why contributors work on open source projects and how much time they spend on security
The FOSS (Free and Open Source Software) contributor survey and report follow the Census II analysis released earlier this year. This combined pair of works represents important steps towards understanding and addressing structural and security complexities in the modern-day supply chain where open source is pervasive but not always understood. Census II identified the most commonly used free and open source software (FOSS) components in production applications, while the FOSS Contributor Survey and report shares findings directly from nearly 1,200 respondents working on them and other FOSS software.
Key findings from the FOSS Contributor Survey include:
The top three motivations for contributors are non-monetary. While the overwhelming majority of respondents (74.87 percent) are already employed full-time and more than half (51.65 percent) are specifically paid to develop FOSS, motivations to contribute focused on adding a needed feature or fix, enjoyment of learning and fulfilling a need for creative or enjoyable work.
There is a clear need to dedicate more effort to the security of FOSS, but the burden should not fall solely on contributors. Respondents report spending, on average, just 2.27 percent of their total contribution time on security and express little desire to increase that time. The report authors suggest alternative methods to incentivizing security-related efforts.
As more contributors are paid by their employer to contribute, stakeholders need to balance corporate and project interests. The survey revealed that nearly half (48.7 percent) of respondents are paid by their employer to contribute to FOSS, suggesting strong support for the stability and sustainability of open source projects but drawing into question what happens if corporate interest in a project diminishes or ceases.
Companies should continue the positive trend of corporate support for employees’ contribution to FOSS. More than 45.45 percent of respondents stated they are free to contribute to FOSS without asking permission, compared to 35.84 percent ten years ago. However, 17.48 percent of respondents say their companies have unclear policies on whether they can contribute and 5.59 percent were unaware of what policies – if any – their employer had.
The report authors are Frank Nagle, Harvard Business School; David A. Wheeler, the Linux Foundation; Hila Lifshitz-Assaf, New York University; and Haylee Ham and Jennifer L. Hoffman, Laboratory for Innovation Science at Harvard.
As a companion to my Amazon Web Services (AWS) product release post, several company spokespeople have discussed their applications of the new AWS predictive maintenance and quality products.
“Industrial and manufacturing customers are constantly under pressure from their shareholders, customers, governments, and competitors to reduce costs, improve quality, and maintain compliance. These organizations would like to use the cloud and machine learning to help them automate processes and augment human capabilities across their operations, but building these systems can be error prone, complex, time consuming, and expensive,” said Swami Sivasubramanian, Vice President of Amazon Machine Learning for AWS. “We’re excited to bring customers five new machine learning services purpose-built for industrial use that are easy to install, deploy, and get up and running quickly and that connect the cloud to the edge to help deliver the smart factories of the future for our industrial customers.”
Fender Musical Instruments Corporation is an iconic brand and the world’s foremost manufacturer of guitars, basses, amplifiers, and related equipment. “Over the past year we worked with AWS to help develop the critical but sometimes overlooked part of running a successful manufacturing business, knowing your equipment condition. For manufacturers worldwide, maintaining equipment uptime is the only way to remain competitive in a global market. Unplanned downtime is costly both in loss of production and labor due to the fire-fighting nature of breakdowns,” said Bill Holmes, Global Director of Facilities at Fender. “Amazon Monitron can give both large industry manufacturers as well as small ‘mom and pop shops’ the ability to predict equipment failures, giving us the opportunity to preemptively schedule equipment repairs.”
RS Components is a leading player in the industrial components and predictive maintenance space. “We are constantly trying to innovate how we serve the maintenance needs of our customers. With the emergence of IoT, we have seen our customers looking to bring real-time condition monitoring capabilities into the factory environment to reduce reactive maintenance and improve asset reliability,” said Richard Jeffers, Technical Director at RS Components. “We are excited to be working with AWS to bring Amazon Monitron to our customers because it allows them to deploy a cost effective, easy to use, continuously improving condition monitoring solution and enable predictive maintenance across a broader set of equipment in their asset base. Although we stock over 500,000 products from 2,500 different suppliers, this is the first end-to-end wireless vibration and temperature condition monitoring solution in our portfolio. We plan to make Amazon Monitron available to our customers via our e-commerce platform, and leverage it to deliver condition-based monitoring and reliability services through RS Monition, our data led, reliability services business. Working with AWS will enable us to support our customers’ efforts to adopt IoT and machine learning as emerging technologies and accelerate their Industry 4.0 strategies.”
GS EPS is a South Korean Industrial Conglomerate. “We have been generating data across our assets for over a decade now but have only been using physics and rules based methods to gain insights into our data,” said Kang Bum Lee, Executive Vice President of GS EPS. “Amazon Lookout for Equipment is enabling our plant operation teams to build models on our equipment with no ML expertise required. We are leading the transformation of our organization into a data-driven work culture with AWS and Amazon Lookout for Equipment.”
Doosan Infracore is a leading global manufacturer of heavy duty equipment and engines. “Leveraging AI is critical in advancing Doosan’s next generation equipment, so we are working with AWS to develop use cases where automated and scalable machine learning could be leveraged,” said Mr. Jae Yeon Cho, Vice President of Doosan Infracore. “Based on this, we are excited to continue to work with AWS to leverage Amazon Lookout for Equipment in our next generation IoT platform.”
OSIsoft is a manufacturer of application software for real-time data management, called the PI System. “Today, there are more than 2 billion sensor-based data streams inside OSIsoft PI Systems, and thousands of customers relying on the PI System daily to run their operations. These customers are constantly looking for methods to easily serve up insights for improving their competitiveness. OSIsoft products can be integrated with AWS services to help customers unlock additional value from their data. Amazon Lookout for Equipment expands the scope of services and insights available to customers by delivering automated machine learning built specifically for equipment monitoring,” said Michael Graves, Director of Strategic Alliances at OSIsoft.
“Every month, millions of trucks enter Amazon facilities so creating technology that automates trailer loading, unloading, and parking is incredibly important,” said Steve Armato, VP Middle Mile Production Technology at Amazon.com. “Amazon’s Middle Mile Products & Technology (MMPT) has begun using AWS Panorama to recognize license plates on these vehicles and automatically expedite entry and exit for drivers. This enables safe and fast visits to Amazon sites, ensuring faster package delivery for our customers.”
BP is a global energy company, providing customers with fuel for transport, energy for heat and light, lubricants to keep engines moving, and the petrochemicals products used to make everyday items as diverse as paints, clothes, and packaging. The organization has 18,000 service stations and more than 74,000 employees worldwide. “Our engineering teams here at bpx are working very closely with AWS to build an IoT and cloud platform that will enable us to continuously improve the efficiency of our operations,” said Grant Matthews, Chief Technology Officer at BP America. “One of the areas we have explored as part of this effort is the use of computer vision to help us further improve security and worker safety. We want to leverage computer vision to automate the entry and exit of trucks to our facility and verify that they have fulfilled the correct order. Additionally, we see possibilities for computer vision to keep our workers safe in a number of ways, from monitoring social distancing, to setting up dynamic exclusion zones, and detecting oil leaks. AWS Panorama offers an innovative approach to delivering all of these solutions on a single hardware platform with an intuitive user experience. Our teams are excited to work with AWS on this new technology and expect it to help us address many new use cases.”
Siemens Mobility offers intelligent and efficient mobility solutions for urban, interurban, and freight transportation. “Siemens Mobility has been a leader for seamless, sustainable, and secure transport solutions for more than 160 years. The Siemens ITS Digital Lab is the innovation team in charge of bringing the latest digital advances to the traffic industry and uniquely positioned to provide data analytics and AI solutions to public agencies,” said Laura Sanchez, Innovation Manager, Siemens Mobility ITS Digital Lab. “As cities face new challenges, municipalities have turned to us to innovate on their behalf. Cities would like to understand how to effectively manage their assets and improve congestion and direct traffic. We want to use AWS Panorama to bring computer vision to existing security cameras to monitor traffic and intelligently allocate curbside space, help cities optimize parking and traffic, and improve quality of life for their constituents.”
ADLINK Technology offers hardware/software platforms enabling customers to implement edge AI solutions for real-time delivery of actionable data in industrial markets such as manufacturing, transportation, healthcare, energy, and communications. “The integration of AWS Panorama on ADLINK’s industrial vision systems makes for truly plug-and-play computer vision at the edge,” said Elizabeth Campbell, CEO at ADLINK USA. “In 2021, we will be making AWS Panorama-certified ADLINK NEON cameras powered by NVIDIA Jetson AGX Xavier available to customers to drive high-quality computer vision powered outcomes much, much faster. This allows ADLINK to deliver ML digital experiments and time to value for our customers more rapidly across logistics, manufacturing, energy, and utilities use cases.”
INDUS.AI is the world’s most advanced construction intelligence solution that enables real estate investors, owners, developers, and general contractors to have real-time visibility and actionable insights into all activities, productivity, and risks at their construction sites. INDUS.AI seeks to make construction sites and projects safer, more efficient, and completely transparent. “Construction zones are dynamic environments. At any given time you’ve got hundreds of deliveries and subcontractors sharing the site with heavy equipment and it’s changing every day. INDUS.AI is focused on delivering construction intelligence for general contractors,” said Matt Man, CEO of INDUS.AI. “Computer vision is an especially valuable tool for this because of its ability to handle multiple tasks at once. We are looking forward to delivering real-time insights on job-site management and safety in a SaaS-like experience for AWS Panorama customers.”
Dafgards is a household name in Sweden, manufacturing a broad assortment of foods. One of their most successful brands is Billys Pan Pizza, a microwaveable pizza baked and packed at a speed of 2 pizzas per second. “To uphold our brand and deliver the freshest and tastiest customer experience, we want to ensure that all our pizzas are adequately covered in cheese and with the correct toppings. Previously, we installed a machine vision system to detect proper coverage of cheese across a pizza’s surface. While this system served well for our original inspection requirement, it was unable to detect defects on new product types that include multiple toppings,” said Fredrik Dafgård, Head of Operational Excellence and Industrial IoT at Dafgards. “Amazon Lookout for Vision automates and scales inspection of diverse product types such as a cheese pizza with vegetables. We successfully expanded our quality assurance for new product types with minimal impact to operations.”
GE Healthcare is a leading global medical technology and digital solutions innovator that develops, manufactures, and distributes diagnostic imaging agents, radiopharmaceuticals, medical diagnostic equipment, including CT and MRI machines, and intelligent devices supported by its Edison intelligence platform. “Today, we use human inspection to verify the quality of our medical equipment. To uphold our brand and deliver best-in-class products trusted by healthcare professionals, we’re excited about the possibility of using Amazon Lookout for Vision to programmatically improve the speed, consistency, and accuracy of detecting product defects across our factories in Japan and potentially in other plants globally in the near future,” said Kozaburo Fujimoto, Operating Officer, General Manager, Manufacturing Division, Plant Manager at GE Healthcare Japan.
Nukon, a SAGE Group company, is a digital transformation consultancy and delivery company that delivers custom-designed solutions which combine strategy, analysis, and technology to give visibility into key business processes so they can be optimized. “We are excited about how Amazon Lookout for Vision will help us detect product defects in real-time within the manufacturing facility for our sister company, SAGE Automation, in line with their stringent quality control program. We are excited to now apply this technology to other manufacturers and integrate it into their quality systems,” said Rafael Amaral, Chief Technology Officer at Nukon.
As usual, there is more than one conference this week. I have two more to report on. This one is a bit of a surprise. I was providing thoughts about potential disruption of the mainstream automation market from below when I received this news from Amazon Web Services (AWS). This is a lengthy report, because there is a lot of news here. And it’s worth pausing to consider. I worked with another IT company a few years ago about predictive maintenance as a possible market. That company did not see the sales possibilities and bailed.
AWS is not just a remote server farm for cloud services. It has packed tons of tech into the company. Imagine your possibilities using this.
Amazon Monitron provides customers an end-to-end machine monitoring solution comprised of sensors, gateway, and machine learning service to detect abnormal equipment conditions that may require maintenance
Amazon Lookout for Equipmentgives customers with existing equipment sensors the ability to use AWS machine learning models to detect abnormal equipment behavior and enable predictive maintenance
AWS Panorama Appliance enables customers with existing cameras in their industrial facilities with the ability to use computer vision to improve quality control and workplace safety
AWS Panorama Software Development Kit (SDK) allows industrial camera manufacturers to embed computer vision capabilities in new cameras
Amazon Lookout for Visionuses AWS-trained computer vision models onimages and video streams to find anomalies and flaws in products or processes
Axis, ADLINK Technology, BP, Deloitte, Fender, GE Healthcare, and Siemens Mobility among customers and partners using new AWS industrial machine learning services
This week at AWS re:Invent, Amazon Web Services Inc. (AWS), an Amazon.com company, announced Amazon Monitron, Amazon Lookout for Equipment, the AWS Panorama Appliance, the AWS Panorama SDK, and Amazon Lookout for Vision. Together, these five new machine learning services help industrial and manufacturing customers embed intelligence in their production processes in order to improve operational efficiency, quality control, security, and workplace safety.
The services combine sophisticated machine learning, sensor analysis, and computer vision capabilities to address common technical challenges faced by industrial customers. To learn more about AWS’s new industrial machine learning services, visit https://aws.amazon.com/industrial/
Companies are increasingly looking to add machine learning capabilities to industrial environments, such as manufacturing facilities, fulfillment centers, and food processing plants. For these customers, data has become the connective tissue that holds their complex industrial systems together. With these evolving needs and opportunities, industrial companies have asked AWS to help them leverage the cloud, the industrial edge, and machine learning together to get even more value from the vast amounts of data being generated by their equipment.
Amazon Monitron and Amazon Lookout for Equipment enable predictive maintenance powered by machine learning
In order to make predictive maintenance work, companies have historically needed skilled technicians and data scientists to piece together a complex solution from scratch. This included identifying and procuring the right type of sensors for the use case and connecting them together with an IoT gateway. Companies then had to test the monitoring system and transfer the data to on-premises infrastructure or the cloud for processing. Only then could the data scientists on staff build machine learning models to analyze the data for patterns and anomalies or create an alerting system when an outlier was detected.
Some companies have invested heavily in installing sensors across their equipment and the necessary infrastructure for data connectivity, storage, analytics, and alerting. But even these companies typically use rudimentary data analytics and simple modeling approaches that are expensive and often ineffective at detecting abnormal conditions compared to advanced machine learning models. Most companies lack the expertise and staff to build and refine the machine learning models that would enable highly accurate predictive maintenance. As a result, few companies have been able to successfully implement predictive maintenance, and those that have done it are looking for ways to further leverage their investment, while also easing the burden of maintaining their homegrown solutions.
Here’s how the new AWS machine learning services can help:
For customers who do not have an existing sensor network, Amazon Monitron offers an end-to-end machine monitoring system comprised of sensors, a gateway, and a machine learning service to detect anomalies and predict when industrial equipment will require maintenance. Amazon Monitron detects when machines are not operating normally based on abnormal fluctuations in vibration or temperature, and notifies customers when to examine machinery in order to determine if preventative maintenance is needed. The end-to-end system includes IoT sensors to capture vibration and temperature data, a gateway to aggregate and transfer data to AWS, and a machine learning cloud service that can detect abnormal equipment patterns and deliver results in minutes with no machine learning or cloud experience required. Amazon Monitron also includes a mobile app for a customer’s onsite maintenance technicians to monitor equipment behavior in real time https://aws.amazon.com/monitron.
For customers that have existing sensors but don’t want to build machine learning models, Amazon Lookout for Equipment provides a way to send their sensor data to AWS to build models for them and return predictions to detect abnormal equipment behavior. To get started, customers upload their sensor data to Amazon Simple Storage Service (S3) and provide the S3 location to Amazon Lookout for Equipment. Amazon Lookout for Equipment can also pull data from AWS IoT SiteWise, and works seamlessly with other popular machine operations systems like OSIsoft. Amazon Lookout for Equipment analyzes the data, assesses normal or healthy patterns, and then uses the learnings from all of the data on which it is trained to build a model that is customized for the customer’s environment. Amazon Lookout for Equipment can then use the machine learning model to analyze incoming sensor data and identify early warning signs for machine failure. https://aws.amazon.com/lookout-for-equipment.
AWS Panorama uses computer vision to improve industrial operations and workplace safety
Many industrial and manufacturing customers want to be able to use computer vision on live video feeds of their facility and equipment to automate monitoring or visual inspection tasks and to make decisions in real time. However, the typical monitoring methods used today are manual, error prone, and difficult to scale.
Customers could build computer vision models in the cloud to monitor and analyze their live video feeds, but industrial processes typically need to be physically located in remote and isolated places, where connectivity can be slow, expensive, or completely non-existent. This type of video feed could be automatically processed in the cloud using computer vision, but video feeds are high bandwidth and can be slow to upload. Most customers end up running unsophisticated models that can’t be programmed to run custom code that integrates into the industrial machines. Here’s how AWS can now help:
The AWS Panorama Appliance provides a new hardware appliance that allows organizations to add computer vision to existing on-premises cameras that customers may already have deployed. Customers start by connecting the AWS Panorama Appliance to their network, and the device automatically identifies camera streams and starts interacting with the existing industrial cameras. The AWS Panorama Appliance is integrated with AWS machine learning services and IoT services that can be used to build custom machine learning models or ingest video for more refined analysis.
The AWS Panorama Software Development Kit (SDK) enables hardware vendors to build new cameras that can run meaningful computer vision models at the edge. Cameras that are built with the AWS Panorama SDK run computer vision models for use cases like detecting damaged parts on a fast-moving conveyor belt or spotting when machinery is outside of a designated work zone. Customers can train their own models in Amazon SageMaker and deploy them on cameras built with the AWS Panorama SDK with a single click. Customers can also add Lambda functions to cameras built with the AWS Panorama SDK to be alerted to potential issues via text or email. AWS also offers pre-built models for tasks like PPE detection and social distancing and can deploy these models in minutes without doing any machine learning work or special optimizations.
Amazon Lookout for Vision offers automated fast and accurate visual anomaly detection for images and video at a low cost
One use case where AWS customers are excited to deploy computer vision with their cameras is for quality control. Machine learning-powered visual anomaly systems remain out of reach for the vast majority of companies. Here’s how AWS can now help these companies:
Amazon Lookout for Vision offers customers a high accuracy, low-cost anomaly detection solution that uses machine learning to process thousands of images an hour to spot defects and anomalies. Customers send camera images to Amazon Lookout for Vision in batch or in real-time to identify anomalies, such as a crack in a machine part, a dent in a panel, an irregular shape, or an incorrect color on a product. Amazon Lookout for Vision then reports the images that differ from the baseline so that appropriate action can be taken. Amazon Lookout for Vision also runs on Amazon Panorama appliances. Customers can run Amazon Lookout for Vision in AWS starting today, and beginning next year, customers will be able to run Amazon Lookout for Vision on AWS Panorama Appliances and other AWS Panorama devices so customers will be able to use Amazon Lookout for Vision in locations where Internet connectivity is limited or non-existent. https://aws.amazon.com/lookout-for-vision.