Google Cloud Brings End-to-End Visibility to Supply Chains

US Presidential Candidate Ross Perot years ago described a “giant sucking sound” using a typical businessperson’s view of government. Well, I think that a digital picture of today’s supply chains would show a giant clogging mess, like a kitchen garbage disposal gone wrong. Regardless, Google Cloud released this supply chain digital twin to show just such a condition.

We in manufacturing and production need to pay attention to these giant enterprise IT companies. They keep encroaching into our territory. Someday industrial technology will be absorbed into it at the rate we are going.

Google Cloud today announced the launch of Supply Chain Twin, a purpose-built industry solution that lets companies build a digital twin–a virtual representation of their physical supply chain–by orchestrating data from disparate sources to get a more complete view of suppliers, inventories, and other information. In addition, the Supply Chain Pulse modulealso announced today, can be used with Supply Chain Twin to provide real-time dashboards, advanced analytics, alerts on critical issues like potential disruptions, and collaboration in Google Workspace. 

The majority of companies do not have complete visibility of their supply chains, resulting in retail stock outs, aging manufacturing inventory, or weather-related disruptions. In 2020, out-of-stock items alone cost the retail industry an estimated $1.14 trillion. The past year-and-a-half of supply chain disruptions related to COVID-19 has further proven the need for more up-to-date insights into operations, inventory levels, and more.


“Siloed and incomplete data is limiting the visibility companies have into their supply chains.” said Hans Thalbauer, Managing Director, Supply Chain & Logistics Solutions, Google Cloud. “The Supply Chain Twin enables customers to gain deeper insights into their operations, helping them optimize supply chain functions—from sourcing and planning, to distribution and logistics.”  

With Supply Chain Twin, companies can bring together data from multiple sources, all while requiring less partner integration time than traditional API-based integration. Some customers have seen a 95% reduction in analytics processing time, with times for some dropping from 2.5 hours down to eight minutes. Data types supported in Supply Chain Twin include:

  • Enterprise business systems: Better understand operations by integrating information such as locations, products, orders, and inventory from ERPs and other internal systems. 
  • Supplier and partner systems: Gain a more holistic view across businesses by integrating data from suppliers, such as stock and inventory levels, and partners, such as material transportation status. 
  • Public sources: Understand your supply chain in the context of the broader environment by connecting contextual data from public sources, such as weather, risk, or sustainability-related data, including public datasets from Google.

Once customers are up-and-running on Supply Chain Twin, the Supply Chain Pulse module enables further visibility, simulations, and collaboration features:

  • Real-time visibility and advanced analytics: Drill down into key operational metrics with executive performance dashboards that make it easier to view the status of the supply chain. 
  • Alert-driven event management and collaboration across teams: Set mobile alerts that trigger when key metrics reach user-defined thresholds, and build shared workflows that allow users to quickly collaborate in Google Workspace to resolve issues. 
  • AI-driven optimization and simulation: Trigger AI-driven algorithm recommendations to suggest tactical responses to changing events, flag more complex issues to the user, and simulate the impact of hypothetical situations.

“At Renault, we are innovating on how we run efficient supply chains. Improving visibility to inventory levels across our network is a key initiative,” said Jean-François Salles, Supply Chain Global Vice President at Renault Group. “By aggregating inventory data from our suppliers and leveraging Google Cloud’s strength in organizing and orchestrating data, with solutions like the Supply Chain Twin we expect to achieve a holistic view. We aim to work with Google tools to manage both stock, improve forecasting, and eventually optimise our fulfillment.” 

“End-to-end visibility across the entire supply chain is a top priority for supply chain professionals to optimize planning, real-time decision making and monitoring,” said Simon Ellis, Program Vice President at IDC. “Google Cloud’s approach to a digital twin of the supply chain spans internal, external, and partner data networks without complex integrations. This approach can help organizations to better plan, monitor, collaborate and respond at scale.”

Customers are deploying Supply Chain Twin via Google Cloud partners 

Retailers, manufacturers, CPG firms, healthcare networks, and other logistics-heavy companies can deploy Supply Chain Twin by working directly with Google Cloud’s partner ecosystem. For example, system integration partners such as Deloitte, Pluto7, and TCS, can help customers integrate the Supply Chain Twin and relevant datasets into their existing infrastructure. 

In addition, data partners, such as Climate Engine, Craft, and Crux can augment Supply Chain Twin by providing geospatial, sustainability, and risk management data sets for a more complete macroenvironment view. Finally, application partners such as Anaplan, Automation Anywhere, and project44 can provide information from their platforms into Supply Chain Twin to help customers better understand product lifecycles, track shipments across carriers, predict ETAs, and more.

Supply Chain Twin and the Twin Pulse module are today globally available in Preview. For pricing and availability, customers should talk to their Google Cloud sales representative. For more information on Supply Chain Twin, visit here.

Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology – all on the cleanest cloud in the industry. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.

HPE Hastens Transition To Data Management Company

Hewlett Packard Enterprise (HPE) held a Web event Sept. 28 to announce extensions and enhancements to its GreenLake edge-to-cloud platform. One commentator during the “deep dive” sessions opined that HPE is becoming a “data management company.” In other words, it is transitioning from a hardware company to a software and as-a-Service company. And the pace of the change during the past two years is picking up. Quite frankly, I’m surprised at the speed of the changes in the company over that brief period of time.

The announcements in summary: 

  • HPE unveils new cloud services for the HPE GreenLake edge-to-cloud platform
  • The HPE GreenLake platform now has more than 1,200 customers and $5.2 billion in total contract value
  • HPE takes cyberthreats and ransomware head-on with new cloud services to protect customers’ data from edge to cloud
  • HPE pursues big data and analytics software market – forecasted by IDC to reach $110B by 2023– with industry’s first cloud-native unified analytics and data lakehouse cloud services optimized for hybrid environments

Following is information from HPE’s press release. 

HPE GreenLake edge-to-cloud platform combines control and agility so customers can accelerate innovation, deliver compelling experiences, and achieve superior business outcomes

Hewlett Packard Enterprise (NYSE: HPE) today announced a sweeping series of new cloud services for the HPE GreenLake edge-to-cloud platform, providing customers unmatched capabilities to power digital transformation for their applications and data. This represents HPE’s entry into two large, high-growth software markets – unified analytics and data protection. Together, these innovations further accelerate HPE’s transition to a cloud services company and give customers greater choice and freedom for their business and IT strategy, with an open and modern platform that provides a cloud experience everywhere. The new offerings, which add to a growing portfolio of HPE GreenLake cloud services, allow customers to innovate with agility, at lower costs, and include the following:

  • HPE GreenLake for analytics – open and unified analytics cloud services to modernize all data and applications everywhere – on-premises, at the edge, and in the cloud

  • HPE GreenLake for data protection – disaster recovery and backup cloud services to help customers take ransomware head-on and secure data from edge-to-cloud

  • HPE Edge-to-Cloud Adoption Frameworkand automation tools– a comprehensive, proven set of methodologies expertise, and automation tools to accelerate and de-risk the path to a cloud experience everywhere

“The big data and analytics software market, which IDC predicts will reach $110 billion by 2023, is ripe for disruption, as customers seek a hybrid solution for enterprise datasets on-premises and at the edge,” said Antonio Neri, president and CEO, at HPE. “Data is at the heart of every modernization initiative in every industry, and yet organizations have been forced to settle for legacy analytics platforms that lack cloud-native capabilities, or force complex migrations to the public cloud that require customers to adapt new processes and risk vendor lock-in. The new HPE GreenLake cloud services for analytics empower customers to overcome these trade-offs and gives them one platform to unify and modernize data everywhere. Together with the new HPE GreenLake cloud services for data protection, HPE provides customers with an unparalleled platform to protect, secure, and capitalize on the full value of their data, from edge to cloud.” 

HPE continues to accelerate momentum for the HPE GreenLake edge-to-cloud platform. The HPE GreenLake platform now has more than 1,200 customers and $5.2 billion in total contract value. In HPE’s most recent quarter, Q3 2021, HPE announced that the company’s Annualized Revenue Run Rate was up 33 percent year-over-year, and as-a-service orders up 46 percent year-over-year. Most recently, HPE announced HPE GreenLake platform wins with Woolworths Group, Australia and New Zealand’s largest retailer, and the United States National Security Agency.

HPE GreenLake Rolls Out Industry’s First Cloud-Native Unified Analytics and Data Lakehouse Cloud Services Optimized for Hybrid Environments

HPE GreenLake for analytics enable customers to accelerate modernization initiatives, for all data, from edge to cloud. Available on the HPE GreenLake edge-to-cloud platform, the new cloud services are built to be cloud-native and avoid complex data migrations to the public cloud by providing an elastic, unified analytics platform for data and applications on-premises, at the edge and in public clouds. Now analytics and data science teams can leverage the industry’s first cloud-native solution on-premises, scale-up Apache Spark lakehouses, and speed up AI and ML workflows. The new HPE GreenLake cloud services include the following:

  • HPE Ezmeral Unified Analytics: Industry’s first unified, modern analytics and data lakehouse platform optimized for on-premises deployment and spans edge to cloud.

  • HPE Ezmeral Data Fabric Object Store: Industry’s first Kubernetes-native object store optimized for analytics performance, providing access to data sets edge to cloud.

  • Expanding HPE Ezmeral Partner Ecosystem: The HPE Ezmeral Partner Program delivers a rapidly growing set of validated full-stack solutions from ISV partners that enable customers to build their analytics engines. This includes new support from NVIDIA, Pepperdata and Confluent, and open-source projects such as Apache Spark. HPE has added 37 ISV partners to the HPE Ezmeral Partner Program since it was first introduced in March 2021, delivering additional ecosystem stack support of core use cases and workloads for customers, including big data and AI/ML use cases.

HPE Takes Cyberthreats and Ransomware Head-On with New HPE GreenLake Cloud Services to Protect Customers’ Data from Edge to Cloud

HPE today entered the rapidly growing data protection-as-a-service market with HPE GreenLake for data protection, new cloud services designed to modernize data protection from edge to cloud, overcome ransomware attacks, and deliver rapid data recovery.

  • HPE Backup and Recovery Service: Backup as a service offering that provides policy-based orchestration and automation to backup and protect customers’ virtual machines across hybrid cloud, and eliminates the complexities of managing backup hardware, software, and cloud infrastructure.

  • HPE GreenLake for Disaster Recovery: Following the close of the Zerto acquisition, HPE plans to deliver Zerto’s industry-leading disaster recovery as a service through HPE GreenLake, to help customers recover in minutes from ransomware attacks. Zerto provides best-in-class restore times without impacting business operations for all recovery scenarios.

HPE Accelerates Adoption of Cloud-Everywhere Operating Models with Proven Framework and Data-Driven Intelligence and Automations Tools

HPE also today announced a proven set of methodologies and automation tools to enable organizations to take a data-driven approach to achieve the optimal cloud operating model across all environments:

  • The HPE Edge-to-Cloud Adoption Framework leverages HPE’s expertise in delivering solutions on-premises, to meet a broad spectrum of business needs for customers across the globe. HPE has identified several critical areas that enterprises should evaluate and measure to execute an effective cloud operating model. These domains, which include Strategy and Governance, People, Operations, Innovation, Applications, DevOps, Data, and Security, form the core of the HPE Edge-to-Cloud Adoption Framework.

  • The cloud operational experience is enhanced with the industry’s leading AI Ops for infrastructure, HPE InfoSight, that now constantly observes applications and workloads running on the HPE GreenLake edge-to-cloud platform. The new capability, called HPE InfoSight App Insights, detects application anomalies, provides prescriptive recommendations, and keeps the application workloads running disruption free. HPE CloudPhysics delivers data-driven insights for smarter IT decisions across edge-to-cloud, enabling IT to optimize application workload placement, procure right-sized infrastructure services, and lower costs.

HPE GreenLake Announcement Event

Please visit the HPE Discover More Network to watch the HPE GreenLake announcement event, including the keynote from Antonio Neri, HPE president and CEO, live on September 28that 8:00 am PT or anytime on-demand.

Product Availability

HPE GreenLake for analytics and HPE GreenLake for data protection will be available in 1H 2022.

The HPE Edge-to-Cloud Adoption Framework is available now.

HPE provides additional information about HPE product and services availability in the following blogs: 

HPE GreenLake for analytics

HPE GreenLake for data protection

HPE Edge-to-Cloud Adoption Framework

Hewlett Packard Enterprise (NYSE: HPE) is the global edge-to-cloud company that helps organizations accelerate outcomes by unlocking value from all of their data, everywhere. Built on decades of reimagining the future and innovating to advance the way people live and work, HPE delivers unique, open and intelligent technology solutions delivered as a service – spanning Compute, Storage, Software, Intelligent Edge, High Performance Computing and Mission Critical Solutions – with a consistent experience across all clouds and edges, designed to help customers develop new business models, engage in new ways, and increase operational performance. 

Cloud-Capable PLCs Enable More IIoT Applications

When AutomationDirect was PLCDirect and control platforms were developing with much technical development and innovation, I visited the company and its control developer in Knoxville, TN frequently. They were adding Ethernet and IT technologies. Great times. Then that part of the industry matured and AutomationDirect became a master electrical and automation distributor, while still keeping a foot in the automation development door.

This information came to me last week. Given all the interest in automation and sensor and OPC to the cloud, I thought this was interesting. AutomationDirect here discusses the PLC as an integral part of a cloud-based system. Good for them.

PLCs can now be directly integrated with cloud-based computing platforms, empowering end users and OEMs to quickly and easily add IIoT functionality to their systems.

Damon Purvis, PLC Product Manager at AutomationDirect, wrote an article for the August 2021 edition of Machine Design. The article is titled Modern PLCs Simplify Cloud-Based IIoT and it talks about how the newest BRX PLCs can securely connect directly to the leading cloud platforms from AWS, Microsoft, and others.

Industrial automation systems created by end users and OEMs have long had some IIoT data connectivity capabilities—but getting to this data and working with it has often been a chore, prohibitively expensive, or both.

Cloud computing options have eliminated many of these barriers, providing a cost-effective way to deploy and scale up IIoT projects. This is especially the case now that the BRX PLC can connect natively to cloud services, without requiring intermediate layers of processing.

Google Cloud Visual Inspection AI For Manufacturing Quality Control

What these cloud companies are doing with their platforms is becoming amazing. This news is from Google—a little later than first Amazon Web Services and then Microsoft Azure. It is quickly adding some interesting capabilities. Once again, we’re seeing artificial intelligence (AI) built into so many applications that we should cease to have surprise and awe. It’s a tool—and a powerful one if used appropriately. Check out this vision inspection solution.

Google Cloud today launched Visual Inspection AI, a new purpose-built solution to help manufacturers, consumer packaged goods companies, and other businesses worldwide reduce defects and deliver significant operational savings from the manufacturing and inspection process. 

Today, defects in products such as computer chips, cars, machinery, and other products cost manufacturers billions of dollars annually. In fact, quality-related costs can consume 15% to 20% of sales revenue[1]. In addition, high production volumes outpace the ability of humans to manually inspect each part. 

Google Cloud has traditionally supported manufacturing quality control through its general purpose AI product, AutoML. Today, it is taking the next step by offering a purpose-built solution for manufacturers. Using Google Cloud’s leading computer vision technology, Visual Inspection AI automates the quality control process, enabling manufacturers to quickly and accurately detect defects before products are shipped. By identifying defects early in the process, customers can improve production throughput, increase yields, reduce rework, and reduce return and repair costs. Visual Inspection AI operates across a wide range of industries and use cases, potentially saving manufacturers millions of dollars at each facility

Based on pilots run by Google Cloud customers, Visual Inspection AI can build accurate models with up to 300 times fewer human-labelled images than general-purpose ML platforms. This allows the solution to be deployed quickly and easily in any manufacturing setting. In addition, Visual Inspection AI customers improved accuracy in production trials by up to 10X compared with general-purpose ML approaches. And, unlike competing solutions that use simple anomaly detection, Visual Inspection AI’s deep learning allows customers to train models that detect, classify, and precisely locate multiple defect types in a single image. 

“AI has proven to be particularly beneficial in helping to automate the visual quality control process for manufacturers—a particular pain point felt by the industry. We’ve been delighted by the strong interest in Visual Inspection AI, and we look forward to supporting more organizations as they continue to find innovative new ways to deploy AI at scale,” said Dominik Wee, Managing Director Manufacturing and Industrial at Google Cloud. 

“We’ve been listening to the specific needs of the industry and have brought the best of Google AI technologies to help address those needs. The outcome is an AI solution that, built upon years of computer vision expertise, is purpose-built to solve quality control problems for nearly any type of discrete manufacturing process,” said Mandeep Waraich, Head of Product for Industrial AI at Google Cloud.

Building and training machine learning models typically requires deep AI expertise, as well as extensive databases containing thousands of labelled images. Such systems usually run in an on-premise data center or in the cloud, making them difficult to deploy at scale across the factory floor. With Google Cloud Visual Inspection AI:

  • No special expertise is required. Quality, test, and manufacturing engineers can use the solution without any computer vision or AI subject-matter expertise. An intuitive user interface guides employees through all of the necessary steps. 
  • Engineers can get started quickly and build more accurate models. Machine learning models can be trained using as few as 10 labelled images (vs. thousands) and will automatically increase in accuracy over time as they are exposed to more products.
  • Full edge-to-cloud capability: Inspection models can be downloaded to machines on the factory floor and run autonomously at the edge, whether it be for data governance reasons or to improve latency. At the same time, Visual Inspection AI is fully integrated in Google Cloud’s portfolio of analytics and ML/AI solutions. This enables manufacturers to combine insights from Visual Inspection AI with other data sources on the shop floor and beyond, for instance to identify root causes of quality problems or to cross-reference with supplier and customer data.
  • Problems are resolved faster. Not only does the solution flag a defective component, but also Visual Inspection AI can locate and identify the specific defect within each part, which reduces the time spent by engineers to diagnose problems, rework parts, and implement process improvements. 

“Google Cloud’s approach to visual inspection is the roadmap most manufacturing companies are looking for. Manufacturers want flexibility, scale, inherent edge-to-cloud capabilities, access to both real-time and historical data, and ease of use and maintainability”, said Kevin Prouty, Group Vice President at IDC. “Google is one of those companies that has the potential to bring together IT, OT and an ecosystem of partners that manufacturers need to deploy AI on the shop floor at scale.”

Wide Range of Use Cases for Visual Inspection AI

Automotive manufacturers: A typical vehicle factory produces around 300,000 vehicles each year, and up to 10% of them may have parts that underwent rework or replacement during the manufacturing process to address some type of production defect [2]. By automatically identifying defects in paint finish, seat fabrication, body welds, and end-of-line testing of mechanical parts, Visual Inspection AI could save automakers more than $50 million annually per plant. 

“Google Cloud’s strength in machine learning and artificial intelligence is accelerating Renault’s Industry 4.0 transformation. We are adopting innovative computer vision solutions like Visual Inspection AI, AutoML and Vertex AI to implement more accurate quality controls with a significantly reduced time to market at a lower cost. We are working now on deploying these new tools in every Renault factory. Renault is ready for future-oriented manufacturing and welcomes the partnership with Google Cloud,” said Dominique Tachet, Digital Project Leader, Renault.

Electronics manufacturing services (EMS): Of the 15 million circuit boards produced each year in a typical EMS factory, as many as 6% may be reworked or scrapped during the assembly process due to internal or external quality failures, such as soldering errors or missing screws [3]. Reducing rework and material waste can save such a facility nearly $23 million each year. 

“It’s been amazing to work with Google Cloud to bring innovative machine learning and computer vision technologies to our quality processes. Engineers from FIH Mobile, a subsidiary of Foxconn, trust Google Cloud and we are achieving considerable product improvements through our collaboration. We cannot wait to roll out the Visual Inspection AI solution further across our extensive PCB manufacturing operations.” said Sabcat Shih, Senior Associate Manager, FIH Mobile.

Semiconductor production: A chip fabrication plant that produces 600,000 wafers per year could see yield losses of up to 3% from cracks and other defects [4]. Implementing Visual Inspection AI can reduce production delays and scrap, saving up to $56 million per fab.

“With the shortage of AI engineers, Visual Inspection AI is an innovative service that can be used by non-AI engineers. We have found that we are able to create highly accurate models with as few as 10-20 defective images with Visual Inspection AI. We will continue to strengthen our partnership with Google to develop solutions that will lead our customers’ digital transformation projects to success.” said Masaharu Akieda, Division Manager, Digital Solution Division, KYOCERA Communication Systems Co., Ltd.

[1] “Cost of Quality,” American Society for Quality (ASQ).

[2] “Internal documents reveal the grueling way Tesla hit its 5,000 Model 3 target,” Business Insider

[3] “Capturing the value of good quality in medical devices,” McKinsey & Company

[4] “Taking the next leap forward in semiconductor yield improvement,” McKinsey & Company

Additional Resources

  • Visual Inspection AI solution webpage
  • Visual Inspection AI launch blog
  • Visual Inspection AI overview video
  • FIH Mobile case study
  • Keep up with the latest Google Cloud news on our newsroom and blog

Google Cloud accelerates organizations’ ability to digitally transform their business with the best infrastructure, platform, industry solutions and expertise. We deliver enterprise-grade cloud solutions that leverage Google’s cutting-edge technology to help companies operate more efficiently and adapt to changing needs, giving customers a foundation for the future. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to solve their most critical business problems.