by Gary Mintchell | Nov 9, 2018 | Automation, Industrial Computers, Internet of Things
Advantech has been appearing on a variety of lists of prominent Internet of Things suppliers. The Taiwanese computer company with a US office in Cincinnati, OH and intellectual leadership, supplies intelligent I/O, a variety of computing devices, and HMI devices.
Several years ago I was privileged to be invited to Suzhou, China to attend Advantech’s user conference. It was an impressive event. This year they called it the “first IoT Co-Creation Summit.”
More than five thousand Advantech clients and partners from around the world attended the summit. Here Advantech introduced its newest IoT platform structure WISE-PaaS 3.0 and 32 IoT solution ready packages (SRPs) co-created with software and industry partners.
The event in itself will aid in the software/hardware integration for various industries, connect and build a complete industrial IoT ecosystem and value chain, and allow Advantech and partners to officially step into the next IoT stage.
Advantech Chairman KC Liu stated that in view of IoT application characteristic’s diversity and fragmented market, Advantech has assisted industries in integrating and connecting existing hardware and software and regards creating a complete industry value chain as its primary task in IoT industry development.
Advantech is introducing new features for its WISE-PaaS 3.0 and sharing a number of IoT solution ready packages (SRPs), based on WISE-PaaS, developed with numerous co-creation partners. The company is also outlining future co-creation strategies and schedules for the upcoming year.
Allan Yang, Chief Technology Officer at Advantech said, “While IoT is currently flourishing and many companies have invested in connectivity and data collection equipment, we are still in the early stages of generating value from IoT data. Since WISE-PaaS launched in 2014, Advantech has continued its integration and improved connectivity with open source communities. Our IoT software modules are developed to create operational cloud platform services oriented around the commercial value generated by data acquisition. Data-driven innovation has thus become the main target for our WISE-PaaS evolution.
WISE-PaaS 3.0 offers four main function modules:
- WISE-PaaS/SaaS Composer: a cloud configuration tool with visible workflow. WISE-PaaS/SaaS Composer supports customized component plotting for simple and intuitive 3D modeling application and interaction. It updates views at millisecond rates and, together with WISE-PaaS/Dashboard, presents critical management data in a visually intuitive display to help extract valuable data and improve operational efficiency.
- WISE-PaaS/AFS (AI Framework Service): an artificial intelligence training model and deployment service framework. The WISE-PaaS/AFS provides a simple drag and drop interface that allows developers to quickly input industrial data. When combined with AI algorithms, the service builds an effective inference engine with automatic deployment to edge computing platforms. AFS offers model accuracy management, model retraining, and automated redeployment. It simultaneously controls multiple AI models in the application field; offering automated model accuracy improvements and life-cycle management services.
- WISE-PaaS/APM (Asset Performance Management): an equipment network connection remote maintenance service framework. WISE-PaaS/APM connects to a wide array of on-site industrial equipment controls and communication protocols. It supports the latest edge computing open standard, EdgeX Foundry, and includes built-in equipment management and workflow integration templates. Jointly with the AFS, APM accelerates Machine to Intelligence (M2I) application development.
- Microservice development framework: WISE-PaaS contains a micro service development framework to help developers rapidly create program design frameworks while reducing development requisites. Micro service functions, such as service finding, load balancing, service administration, and configuration center, all offer built-in flexible support mechanisms.
Advantech recently established a water treatment system, jointly developed with GSD (China) Co., Ltd., and a CNC equipment remote operation service, jointly developed with Yeong Chin Machinery Industries Co. Ltd. Both partnerships demonstrate how industrial digital transformations, led by Advantech and its partners through the co-creation model, offer innovative win-win IoT solutions.
Advantech’s IIoT iAutomation Group has launched a broad selection of rackmount GPU Servers from 1U to 4U. The SKY-6000 GPU server series are powered by Intel Xeon scalable processors and each of these highly scalable GPU-optimized servers support up to five NVIDIA Tesla P4 GPUs. IPMI management functions and smart fan control ensure better temperature control and thermal management environments. Every GPU pair includes one high-speed PCIe slot for highly parallel applications like artificial intelligence (AI), deep learning, self-driving cars, smart city applications, health care, high performance computing, virtual reality, and much more.
AI Deep Learning GPU Solution
With support for up to five pcs of half-length half-height (HHHL) GPU cards or one full-height full-length (FHFL) double deck card, plus one full-height half-length (FHHL) GPU card, the SKY-6100 series are designed for NVidia Tesla P4 HHHL GPU cards, making it the best choice for deep learning applications.
IPMI Server Management
With IPMI 2.0 support, the SKY-6000 series allows users to monitor, manage, and control servers remotely and receive alerts if any sensors detect device or component faults. In addition, event logs record important information about the server which can be controlled remotely using the IPMI KVM.
Smart Fan Control
The optimized thermal design separates the CPU and GPU fan zones, making sure the GPU card is not preheated or thermally affected by any other heat source. Also, with the smart fan control mechanism, fan speeds are controlled based on different CPU and GPU workloads and ambient temperature. This feature lowers the acoustic noise of GPUs that have heavy loading but not CPUs. Advantech’s SKY-6000 server series are available for order now.
by Gary Mintchell | Oct 10, 2018 | Commentary, News
Which companies are leading us into the Fourth Industrial Revolution? The World Economic Forum has completed a study and named nine of the best factories in the world—certainly an audacious task. Dubbed “lighthouses”, they were selected from a survey of over 1,000 manufacturing sites based on a successful track record of implementing technologies of the Fourth Industrial Revolution.
Three of the nine “lighthouse” sites are in China, five are in Europe and one is in the United States.
The aim of this effort is to build a network of “manufacturing lighthouses” to address problems confronting industries in both advanced and emerging economies when it comes to investing in advanced technologies. Earlier work by the Forum identified that over 70% of businesses investing in technologies such as big data analytics, artificial intelligence, or 3D printing do not take the projects beyond pilot phase due to unsuccessful implementation strategies. To aid the learning and adoption of technologies by other companies, all nine lighthouses in the network have agreed to open their doors and share their knowledge with other manufacturing businesses.
“The Fourth Industrial Revolution is expected to deliver productivity gains amounting to more than 3.7 trillion USD. But we are still at the beginning of the journey” said Helena Leurent, Head of the Shaping the Future of Production System Initiative and Member of the Executive Committee at the World Economic Forum. “Our efforts to create a learning platform with the lighthouses as the cornerstone are part of the giant leap needed to capture the benefits for the larger manufacturing ecosystem including multinationals, SMEs, start-ups, government and academia”.
“The Fourth Industrial Revolution is real. Workers and management equally get augmented with technology. These pioneers have created factories that have 20-50% higher performance and create a competitive edge,” said Enno de Boer, Partner and Global Head of Manufacturing at McKinsey & Company, which collaborated with the Forum on the project. “They have agile teams with domain, analytics, IoT and software development expertise that are rapidly innovating on the shop floor. They have deployed a common data/IoT platform and have up to 15 use cases in action. They are thinking “scale”, acting “agile” and resetting the benchmark.”
The nine “lighthouses” have comprehensively deployed a wide range of Fourth Industrial Revolution technologies and use cases at scale while keeping humans at the heart of innovation. One example from each of the sites is highlighted below:
- Bayer Biopharmaceutical (Garbagnate, Italy): ‘Using data as an asset’- While most companies use less than 1% of the data they generate, Bayer’s massive data lake has led to a 25% reduction in maintenance costs and 30-40% gains in operational efficiency
- Bosch Automotive (Wuxi, China): ‘Supporting output increase’ – By using advanced data analytics to deeply understand and eliminate output losses, simulate and optimize process settings, and predict machine interruptions before they occur
- Haier (Qingdao, China): ‘User-centric mass customization model’ – Artificial Intelligence led transformations include an ‘order-to-make’ mass customization platform and a remote AI supported, central intelligent service cloud platform to predict maintenance needs before they happen
- Johnson & Johnson Depuy Synthes (Cork, Ireland): ‘Process-driven digital twinning’ – This factory used the internet of things to make old machines talk to one other, resulting in 10% lower operating costs and a 5% reduction in machine downtime
- Phoenix Contact (Bad Pyrmont and Blomberg, Germany): ‘Customer-driven digital twinning’ – By creating digital copies of each customer’s specifications, production time for repairs or replacements has been cut by 30% Procter & Gamble (Rakona, Czech Republic): ‘Production agility’ – A click of a button is all it takes production lines in this factory to instantly change the product being manufactured, which has reduced costs by 20% and increased output by 160%
- Schneider Electric (Vaudreuil, France): ‘Factory integration’ – Sharing knowledge and best practices across sites has helped this company make sure all its factory sites enjoy the highest energy and operational efficiencies, reducing energy costs by 10% and maintenance costs by 30%
- Siemens Industrial Automation Products (Chengdu, China): ‘3D simulated production line optimization’ – Using 3D simulation, augmented reality and other techniques to perfect the design and operations of its factory, employees helped increase output by 300% and reduced cycle time
- UPS Fast Radius (Chicago, USA): ‘Balancing capacity with customer demand’ – Meeting increasing consumer demand for fast-turnaround customized products has been made possible through a combination of globally distributed 3D printing centres with real-time manufacturing analytics
The World Economic Forum, committed to improving the state of the world, is the International Organization for Public-Private Cooperation. The Forum engages the foremost political, business and other leaders of society to shape global, regional and industry agendas.
by Gary Mintchell | Jul 30, 2018 | Commentary, Technology
Everybody has a list of transformative technologies. A news release from an advisory firm, ABI Research, came my way a few weeks ago. Its analysts came together and compiled a list of eight technologies they feel will be transformative in manufacturing and then they fit them with Smart Manufacturing. That latter phrase is one of the descriptors for the new wave of manufacturing strategy and technology.
We will have difficulty contesting the list. Most of these are, indeed, already well along the adoption path. I find it interesting that they refer to IIoT platforms, but they don’t view those as transforming technologies but rather as a sort of sandbox for the technologies to play in.
[This is a Gary aside—when an analyst firm makes a list of suppliers, I’d advise not considering it to be comprehensive. Rather the list is usually comprised of companies that the firm’s analysts get to sit down with and receive in-depth briefings.]
The ABI report identifies eight transformative technologies:
1 Additive manufacturing
2 Artificial intelligence (AI) and machine learning (ML)
3 Augmented reality (AR)
4 Blockchain
5 Digital twins
6 Edge intelligence
7 Industrial Internet of Things (IIoT) platforms
8 Robotics
From the ABI news release, “The manufacturing sector has already seen increased adoption of IIoT platforms and edge intelligence. Over the next ten years, manufacturers will start to piece together the other new technologies that will eventually lead to more dynamic factories less dependent on fixed assembly lines and immobile assets. Each step in this transformation will make plants and their workers more productive.”
“Manufacturers want technologies they can implement now without disrupting their operations,” says Pierce Owen, Principal Analyst at ABI Research. “They will change the way their employees perform jobs with technology if it will make them more productive, but they have no desire to rip out their entire infrastructure to try something new. This means technologies that can leverage existing equipment and infrastructure, such as edge intelligence, have the most immediate opportunity.”
ABI summary of its research
The transition towards a lights-out factory has started, but such a major disruption will require an overhaul of workforces, IT architecture, physical facilities and equipment and full integration of dozens of new technologies including connectivity, additive manufacturing, drones, mobile collaborative robotics, IIoT platforms and AI.
IIoT platforms must support many of these other technologies to better integrate them with the enterprise and each other. Those that can connect and support equipment from multiple manufacturers, such as PTC Thingworx and Telit deviceWISE, will last.
After decades of producing little more than prototypes, the AM winter has ended and new growth has sprung up. GE placed significant bets on AM by acquiring Arcam and Concept laser in 2016, and Siemens announced an AM platform in April 2018. Other leading AM specialists include EOS, Stratasys, HP and 3D Systems.
ML capabilities and simulation software have made digital twins extremely useful for product development, production planning, product-aaS, asset monitoring and performance optimization. Companies with assets that they cannot easily inspect regularly will significantly benefit from exact, 3D digital twins, and companies that manufacture high-value assets should offer digital twin monitoring as-a-service for new revenue streams. Innovative vendors in digital twins and simulation software include PTC, SAP, Siemens, and ANSYS.
The above technologies have already started to converge, and robotics provide a physical representation of this convergence. Robotics use AI and computer vision and connect to IIoT platforms where they have digital twins. This connectivity and AI will increase in importance as more cobots join the assembly line and work alongside humans. The robotics vendors that can integrate the most deeply with other transformative technologies have the biggest opportunity. Such vendors include the likes of ABB, KUKA, FANUC, Universal Robots, Rethink Robotics and Yaskawa.
“The vendors that open up their technologies and integrate with both existing equipment and infrastructure and other new transformative technologies will carve out a share of this growing opportunity. Implementation will go step-by-step over multiple decades, but ultimately, how we produce goods will change drastically from what we see today,” concludes Owen.
by Gary Mintchell | Jul 24, 2018 | Internet of Things, Operations Management
Successful digitalization requires data. Data, in turn, originates often from sensors. The Industrial Internet of Things runs on this data providing a valuable use case of tying a manufacturing enterprise together from supply chain through customer experience.
Mahesh Veerina, CEO of Cloudleaf, walked me through an application based on his company’s technology that indeed ties a supply chain in the pharma industry together. Start with sensors on approximately 5,000 pallets. Each meshes via sub-MHz unlicensed radios through 30 intelligent gateways reporting 16 million data points. Cloudleaf’s SaaS software gathers the data, performs the analytics, then feeds custom dashboards for different roles at the customer’s company. Oh, and continuous learning through Artificial Intelligence (AI) creates a virtuous cycle that constantly improves the system.
The return on investment (ROI)? Estimated at between $70 million and $100 million.
Cloudleaf has announced the next generation of its patented Sensor Fabric, the IoT-at-scale solution that optimizes management of distributed assets throughout any enterprise value chain.
Cloudleaf’s next-generation Sensor Fabric maintains an intelligent grid at the edge for global commerce, making digitization a reality for enterprise customers and value chain partners. Its easy-to-deploy intelligent sensors, gateways and cloud technologies minimize costs and maximize quality, efficiency and reporting standards. At the same time, Cloudleaf’s patented solution generates a continuous stream of increasingly predictive data that enables an enterprise to monitor, measure and manage distributed assets –– on the ground and on the fly. Key enhancements include:
• Comparative multi-location movement history maximizes yield and improves asset utilization.
• Lifecycle tracking optimizes business processes, managing dwell times, cycle times, asset condition changes and other variables.
• Value Loss analytics measure inefficiencies in asset handling, storage and usage.
• Path Modeling provides compliance tracking, monitoring and reporting.
• Next-gen control center enables on-the-fly deployment, calibration, and management of Sensor Fabric, with easy to use web and mobile dashboards.
Unlike products that occasionally add new features and functionalities, Sensor Fabric essentially upgrades itself. Tens-of-millions-per-day messaging sparks multiplier machine learning. The result is agile and actionable insights in virtually any industrial process. The longer Sensor Fabric is deployed, the smarter the industrial process is.
“We are extremely gratified by the extraordinary market acceptance that Cloudleaf is achieving,” said Veerina. “More and more extended enterprises in a wide range of industries are asking Cloudleaf to help them achieve the kinds of efficiencies and ROI that our current customers are gaining. In the very near future, we expect to begin announcing the addition of a number of industry leaders –– including internationally known household names – to our rapidly growing customer base.”
by Gary Mintchell | Jun 21, 2018 | Internet of Things, Manufacturing IT
Antonio Neri, CEO and President of Hewlett Packard Enterprise (HPE), used the phrase “Data is the new currency, memory the new gold” in his keynote to the company’s annual US customer conference Discover in Las Vegas in June. Just one of the many places I’ve been lately.
If you haven’t planned for data in your machine and process control designs, you had best begin.The race for improved operations performance is on now.
We talk often of “edge” in the world of Internet of Things or Industrial Internet of Things. The edge has many definitions, but it can be defined as any place outside a data center. PLCs, for example, not only perform logic control, but they also aggregate data from perhaps thousands of sensors. SCADA devices and industrial computers also collect and channel data from a few to many sensors and data sources.
Business operations managers are hungry for this data to feed their information systems that in turn fuel their business decisions. Data in context is information. Information correctly presented to decision makers leads to better, faster decisions—and a competitive edge.
This search for competitive edge has moved me from an emphasis on control and automation (something we still need to do well) to Industrial Internet of Things. The IIot is taken by many as a similar strategy to Industrie 4.0 or Smart Manufacturing or whatever different countries call their strategies. This means I’m looking at a new generation of edge computing, enhance networking standards, human-centered design for mobile visualization of data, and even Augmented Reality (AR) and Artificial Intelligence (AI). These are not far-out technologies any longer. They are here and applications are growing.
Neri talked about the future as edge-centric, cloud-enabled, data-driven. He said the edge is where the action is, where the data is created. HPE is going to invest $4 billion in the intelligent edge over the next 4 years.
The company announced a new edge computing device with enterprise grade computing power (far beyond a PC) plus up to 48TB (yes that’s Tera not Giga) of memory. Oh, and it also comes in an environmentally hardened package. The CTO of Murphy Oil talked of using these on off-shore oil rigs.
Texmark Chemicals is a Houston, Texas based petrochemical refiner. I had several opportunities to talk with them about their IoT projects. They orchestrated an ecosystem of 12 suppliers initially to instrument critical pumps in their process in order to achieve predictive maintenance. This potentially saves the company millions of dollars by avoiding catastrophic failure. (Note: I previously wrote about the Texmark use case here–and expect more to come.)
Back to the announcement from HPE about the new edge product—a family of edge-to-cloud solutions enabled by HPE Edgeline Converged Edge Systems to help organizations simplify their hybrid IT environment. By running the same enterprise applications at the edge, in data centers and in the cloud, the solutions allow organizations to more efficiently capitalize on the vast amounts of data created in remote and distributed locations like factories, oil rigs or energy grids.
(Dr. Tom Bradicich wrote a blog post you can find here.)
HPE’s new edge-to-cloud solutions operate unmodified enterprise software from partners Citrix, GE Digital, Microsoft, PTC, SAP and SparkCognition, both on HPE Edgeline Converged Edge Systems – rugged, compact systems delivering immediate insight from data at the edge – and on data center and cloud platforms. This capability enables customers to harness the value of the data generated at the edge to increase operational efficiency, create new customer experiences and introduce new revenue streams. At the same time, edge-to-cloud solutions enabled by HPE Edgeline simplify the management of the hybrid IT environment, as the same application and management software can be used from edge to cloud.
“The edge is increasingly becoming a centerpiece of the digital enterprise where things and people generate and act on massive amounts of data,” said Dr. Tom Bradicich, Vice President and General Manager, IoT and Converged Edge Systems, HPE. “Our edge-to-cloud solutions help bring enterprise-class IT capabilities from the data center to the edge. This reduces software and IT administration costs, while accelerating insight and control across the organization and supply chain.”
HPE also announced the HPE Edgeline Extended Storage Adapter option kit, adding up to 48 terabytes of software-defined storage to HPE Edgeline Converged Edge Systems. This enhancement enables storage-intensive use cases like artificial intelligence (AI), video analytics or databases at the edge, while leveraging industry-standard storage management tools such as Microsoft Storage Spaces, HPE StoreVirtual VSA, and VMware vSAN.
