by Gary Mintchell | Mar 25, 2024 | Software, Technology
Kevin Rose interviews Chris Dixon recently. Dixon provides a good overview of the current status of blockchain. I really haven’t heard much about that technology for years. A speaker at a Siemens event maybe five years ago extolled the future of pharmaceutical supply chain data through blockchain. That may have been the last I heard. Check out the podcast for an update.
Meanwhile, according to research from Global Data, “The blockchain industry, although volatile and nascent, has made significant progress in a short span of time, driven by remarkable innovation. Global blockchain platform and services revenue is set to grow from $12 billion in 2023 to $291 billion in 2030. This growth trajectory reflects a more delineated and specialized expenditure pattern, with specific areas such as asset tokenization, blockchain development, and infrastructure services serving as primary drivers of market expansion.”
GlobalData’s latest report, “Thematic Research: Blockchain,” reveals a pivotal shift from the technology’s broad, indiscriminate application to more focused, strategic uses. The industry is witnessing a quiet but steady increase in blockchain adoption, concentrating on its practical benefits. This trend is supported by a growing understanding that blockchain’s applicability is not universal and that a robust digital infrastructure is crucial for its successful deployment.
by Gary Mintchell | Mar 12, 2024 | Automation, Data Management, Software, Technology
- Sees Boundless Automation as Industry Inflection Point to Address Data Barriers & Modernize Operations
- Advanced software-defined automation architecture to integrate intelligent field, edge and cloud, unlocking a new era of productivity
- Global automation leaders convene to learn about Boundless Automation at Emerson Exchange in Düsseldorf
I seem have become sort of persona non grata by the new marketing regime at Emerson Automation group. However, I picked up this news from it’s meeting last month in Düsseldorf, Germany. I found this statement by automation President and CEO Lal Karsanbhai interesting. It reflects the underlying philosophy I wanted to address when Dave and Jane and I started Automation World back in 2003. The world requires suppliers to go beyond proprietary control and leverage all the data for higher level decision making.
“After decades of implementing evolving automation strategies, manufacturers recognize the need to extract greater value from data that is locked in a rigid and now outdated automation architecture,” said Emerson President and CEO Lal Karsanbhai. “The proliferation of data and the development of advanced software are moving us to an era of unprecedented productivity. Rich data and advanced software are converging to form the next major inflection point in the industry.”
Acknowledging the foundational problems we’ve identified for years, Emerson says it is “poised to transform industrial manufacturing with the next-generation automation architecture designed to break down data silos, liberate data and unleash the power of software with Boundless Automation.”
I applaud Emerson’s strategy, although I do wish it had been done along with the standards efforts of OPAF. But only a couple of competitors seem to be serious about that one. Further, I continue to find companies in my research still trying to break down the silos. I thought we had accomplished that 10 years ago. I guess not. We still have complex networks of Microsoft Excel spreadsheets and every department for itself on data definition and retention.
To address this challenge and help customers achieve their operational improvements, Emerson is introducing a vision and actionable strategy to push more computing power closest to where it’s needed and establish the blueprint for a modern industrial computing environment. This environment includes flexibility to deploy software across the intelligent field; a modern, software-defined edge; and the cloud. All three domains will be connected through a unifying data fabric, helping to maintain data context, improve its usability and increase security.
Emerson’s modern, software-defined automation architecture will break down hierarchical networks, securely democratizing and contextualizing data for both people and the artificial intelligence (AI) engines that depend on a continuous flow of information.
Here are the components within Boundless Automation:
- Intelligent Field: An intelligent field will simplify access to more data from more sources and a greater diversity of applications. With smarter devices and new connection technologies like 5G and APL, customers can streamline both connectivity from anywhere in the world, and integration across the new architecture
- Edge: The new OT edge creates a modern, secure, low-latency computing environment, putting new software tools and actionable data closest to its user. This enhanced edge environment establishes a platform for IT and OT colleagues to innovate and collaborate more than ever before.
- Cloud: The cloud will power complex operations and engineering capabilities on-premise and across the enterprise by providing infinite analytical computing power, enterprise collaboration, attractive lifecycle costs and on-demand support and service.
by Gary Mintchell | Feb 28, 2024 | Generative AI, Software
It had to happen sooner or later—GenerativeAI Large Language Model (LLM) for human-machine interface applications. Funny that nowhere in the press release do they mention HMI while using more awkward workaround phrasing. Maybe that is a Finish translation?
- Generative AI Large Language Model (LLM) technology for operational environments, bridging knowledge and language barriers between industrial workers and OT systems
- On-premise edge based MX Workmate solution enables connected workers to get contextually relevant real-time information and query OT-systems in a secure and reliable way using natural language
- OT-compliant MX Workmate automated IT/OT knowledge retrieval, eases interaction between workers and systems to drive efficiency, productivity and worker safety
MX Workmate leverages Generative AI (GenAI) and large language module (LLM) technologies to generate contextual, human-like language content based on real-time OT data, enabling workers to understand complex machines, get real time status information and industries to achieve greater flexibility, productivity, sustainability, as well as improve worker safety.
by Gary Mintchell | Feb 20, 2024 | Asset Performance Management, Generative AI, News, Operations Management, Software
Generative artificial intelligence (AI) popularized by ChatGPT is this year’s big buzz in industrial technology. Predictive maintenance seems to be one logical place where finding more powerful computation can be supportive.
Siemens has worked with Microsoft closely for decades. It has also recently acquired Senseye. Here is news about using GenerativeAI for enhancing a predictive maintenance solution.
In short:
- Enhancing proven machine learning capabilities with generative AI creates a robust, comprehensive predictive maintenance solution that leverages the strengths of both.
- Using a conversational user interface, manufacturers can take proactive actions easily, saving both time and resources.
- New generative AI functionality in Senseye Predictive Maintenance makes predictive maintenance conversational.
Siemens is releasing a new generative artificial intelligence (AI) functionality into its predictive maintenance solution – Senseye Predictive Maintenance. This advance makes predictive maintenance more conversational and intuitive. Through this new release of Senseye Predictive Maintenance with generative AI functionality, Siemens will make human-machine interactions and predictive maintenance faster and more efficient by enhancing proven machine learning capabilities with generative AI.
Senseye Predictive Maintenance uses artificial intelligence and machine learning to automatically generate machine and maintenance worker behavior models to direct users’ attention and expertise to where it’s needed most. Building on this proven foundation, now a generative AI functionality is being introduced that will help customers bring existing knowledge from all of their machines and systems out and select the right course of action to help boost efficiency of maintenance workers.
Currently, machine and maintenance data are analyzed by machine learning algorithms, and the platform presents notifications to users within static, self-contained cases. With little configuration, the conversational user interface (UI) in Senseye Predictive Maintenance will bring a new level of flexibility and collaboration to the table. It facilitates a conversation between the user, AI, and maintenance experts: This interactive dialogue streamlines the decision-making process, making it more efficient and effective.
In the app, generative AI can scan and group cases, even in multiple languages, and seek similar past cases and their solutions to provide context for current issues. It’s also capable of processing data from different maintenance software. For added security, all information is processed within a private cloud environment, safeguarded against external access. Additionally, this data will not be used to train any external generative AI. Data doesn’t need to be high-quality for the generative AI to turn it into actionable insights: With little to configure, it also factors in concise maintenance protocols and notes on previous cases to help increase internal customer knowledge. By better contextualizing information at hand, the app is able to derive a prescriptive maintenance strategy.
The new generative AI functionality in the Software-as-a-Service (SaaS) solution Senseye Predictive Maintenance will be available starting this spring for all Senseye users. The combination of generative AI and machine learning creates a robust, comprehensive predictive maintenance solution that leverages the strengths of both.
by Gary Mintchell | Feb 12, 2024 | Generative AI, Software, Technology
Quantum Computing has been making some headlines and the tech world is fluttering about AI. Dario Gil, SVP of Research at IBM provides a cogent explanation of these technologies. Perhaps the best I’ve heard. It’s on Guy Kawasaki’s podcast. Well worth a listen.
by Gary Mintchell | Feb 9, 2024 | Automation, Robots, Software
Robotic systems provide as much news as AI and cybersecurity over the past year. This news regards funding. I don’t follow the whole VC arena closely, but having been in entrepreneurial start-up mode a few times in my life, I know well the value of the life blood of money.
Naturally, this news combines AI and robotic software solutions. Might as well hit two trends at once. Xaba, a Toronto based developer of AI-powered cognitive software to automate programming and deployment of robotics and CNC machines, has announced it has raised US$2 million in a seed extension round of funding to bring to market AI-driven fabrication processes and intelligent autonomous machines.
It says the funding will enable it to democratize robotic automation and drive sustainable manufacturing.
The funding round was led by BDC Capital’s Deep Tech Venture Fund with participation from Hitachi Ventures and existing investor Hazelview Ventures. The investment will be used to establish and staff a new robotics lab and accelerate the delivery of two Xaba manufacturing platforms.
Xaba is augmenting industrial robots and cobots with xCognition, an artificial intelligence (AI)-powered software solution. xCognition leverages innovative proprietary machine learning algorithms to model the elasto-mechanical-dynamic behavior of industrial robotics and cobots, as well as workpiece variances. This includes variances in location and shape, using proprietary rule-based language models to eliminate coding of robotics programs. xCognition solves the challenges of deploying industrial robots by completely automating how they are programmed and adopted. This solution not only increases accuracy, consistency, and throughput, but also significantly reduces the time and costs of robotics deployments.
Xaba has two manufacturing platforms – xCognition and xTrude – which use proprietary, state-of-the-art industrial artificial intelligence (AI) to provide AI-powered cognitive industrial automation, consistency, robustness and high execution quality. Its platforms eliminate the need for constant human supervision, reprogramming, and waste – factors that significantly impact the return on investment of any major manufacturing or construction process.
xCognition is Xaba’s AI-powered software solution. This industrial robotics digital twin captures and models the true physics of any industrial robotics system (elastic, dynamic, mechanical, tooling). This includes workpiece variances both in location and shape, leveraging rules-based language models and multi-modal datasets that capture legacy data and best practices to enable any robotics system to execute tasks such as drilling, welding (MIG, TIG & Laser), assembling, riveting, laser, data acquisition, and more with maximum accuracy, repeatability, and minimum human supervision.
