Siemens Generative AI and Predictive Maintenance

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.

HighByte Releases Industrial DataOps Solution with Native Connectivity to the Snowflake Data Cloud

A couple of IT companies introduced DataOps to me about ten years ago. I thought this looked like a ripe opportunity for the industrial market. Shortly thereafter I ran into a group of former Kepware people who had formed just such a company—HighByte. I then had an opportunity to talk with the Snowflake people at the Ignition Customer Community meeting last September. This Data Cloud company has some interesting technology. This news relates to a relationship and interoperability service.

If you have not explored the utility of DataOps, check out HighByte and also Snowflake.

HighByte announced in February 2024 the release of HighByte Intelligence Hub version 3.3 that offers new and improved interoperability with industry-leading cloud services, including the Snowflake Data Cloud and AWS IoT SiteWise. The latest release introduces two new native connectors for Snowflake supporting a broad set of use cases for industrial enterprises. 

The first new connector, Snowflake Streaming, utilizes the Snowflake Snowpipe Streaming API. This interface enables direct publishing to Snowflake tables without the need for staging files or third-party applications. This significantly reduces the compute, latency, and cost of frequently moving telemetry events into Snowflake. The second new connector, Snowflake SQL, enables HighByte Intelligence Hub users to directly query Snowflake tables. Rather than merely publishing to Snowflake, the Intelligence Hub can operationalize insights and context derived through the Snowflake Manufacturing Data Cloud by making this data available for industrial devices and applications. 

HighByte Intelligence Hub is an Industrial DataOps solution that contextualizes and standardizes raw industrial data at the edge, delivering usable information to cloud service partners. Receiving consistent, usable industrial data accelerates adoption and scale of these cloud services, helping industrial companies orchestrate digital transformation projects across their enterprise. The Intelligence Hub gives operational technology (OT) domain experts a no-code application to curate and contextualize industrial data according to standard data models.

Intelligence Hub version 3.3 also introduces tighter integration with AWS IoT SiteWise. The Intelligence Hub’s modeling engine and the IoT SiteWise connector have been refined and enhanced for working with hierarchical asset structures. These improvements simplify the user experience, reduce effort, and provide a single, no-code approach for composing and delivering asset-model hierarchies to IoT SiteWise as well as hydrating them with industrial data. 

HPE to acquire Juniper Networks to accelerate AI-driven innovation

Hewlett Packard Enterprise (HPE) influencer group first contacted me in the mid-2010s through the Aruba networking group. I was the independent industrial IoT writer at the time. The scope broadened for a time, then they closed the influencer group a couple of years ago. But I’ve maintained a bit of a connection to HPE networking, as well as its software and high-end hardware groups.

I’m not an analyst of this part of the market, but I’d have to say this is not a surprising acquisition. HPE has been pretty aggressive under CEO Antonio Neri. They usually do pretty well at integrating acquisitions. This acquisition of Juniper Networks should be a boost.

From the news release in brief:

  • Highly complementary combination enhances secure, unified, cloud and AI-native networking to drive innovation from edge to cloud to exascale
  • Accelerates long-term revenue growth and expands gross and operating margin; Expected to be accretive to non-GAAP EPS and free cash flow in year 1, post close
  • Advances HPE’s portfolio mix shift toward higher-growth solutions and strengthens high-margin networking business 

Hewlett Packard Enterprise and Juniper Networks, a leader in AI-native networks, announced January 9 that the companies have entered a definitive agreement under which HPE will acquire Juniper in an all-cash transaction for $40.00 per share, representing an equity value of approximately $14 billion.

The combination of HPE and Juniper advances HPE’s portfolio mix shift toward higher-growth solutions and strengthens its high-margin networking business, accelerating HPE’s sustainable profitable growth strategy. The transaction is expected to be accretive to non-GAAP EPS and free cash flow in the first year post close.

The acquisition is expected to double HPE’s networking business, creating a new networking leader with a comprehensive portfolio that presents customers and partners with a compelling new choice to drive business value.

Combining HPE and Juniper’s complementary portfolios supercharges HPE’s edge-to-cloud strategy with an ability to lead in an AI-native environment based on a foundational cloud-native architecture. 

Upon completion of the transaction, Juniper CEO Rami Rahim will lead the combined HPE networking business, reporting to HPE President and CEO Antonio Neri.

Industry IoT Consortium and Digital Twin Consortium Merge

Two major sources of technology buzz from around 2015 to 2020 or so found homes in industry consortia within The Object Management Group. I talked often with people from the IIC, aka Industry IoT Consortium, and with the Digital Twin Consortium. These were most likely too much overhead for the supporting suppliers and industry. They have merged under The Object Management Group.

  • Object Management Group Announces Integration of Industry IoT Consortium with Digital Twin Consortium
  • Alignment to increase collaboration for a more holistic view across industries and technologies

Object Management Group (OMG) announced the integration of two of its consortia: the Industry IoT Consortium (IIC) and the Digital Twin Consortium (DTC). This integration will further expand OMG’s collaboration with industry, academia, and government, leading to increased adoption of digital twins and digital transformation.

“During the past several years, we have seen opportunities for increased collaboration and alignment between the IIC and DTC,” said Bill Hoffman, CEO and Chairman of OMG. “Integrating IIC within DTC ensures we have the best minds from both, working together to solve increasingly complex problems and providing a more holistic view across industries and technologies.”

OMG will retain IIC’s essential contributions to IoT and digital transformation on the IIC website. Combined IIC/DTC thought leadership will reside on the DTC website.

IIoT Systems Implementation up Year over Year, Set to Reach 75% Deployment Rate in 2023

All God’s children are doing surveys. They want to know what you think. This report, “Building Industrial IoT Systems in 2024,” presents data from a survey by HiveMQ, an MQTT solution provider, and my friends at IIoT World. 

IIoT no longer generates the buzz it did in the mid-10s of the century. Regardless, the use cases still abound for the technology.

350 professionals were surveyed across Automotive Manufacturing, Power and Utilities, Renewable Energy, Transportation and Logistics, Smart Cities, and more to share feedback on building IIoT systems. The results demonstrate that industries are embracing IIoT technologies and moving towards full implementation and deployment of IIoT solutions. Implementations are up from 67% in 2022 to 75% in 2023.

Getting funding is a never-ending problem for engineers seeking new projects.

With 6 out of ten executives saying it is difficult to quantify investment in technology, more and more professionals are stuck in proof-of-concept purgatory. Industrial automation is no different — over a third of survey respondents said a key challenge for implementing IIoT systems is a lack of budget and uncertain ROI.

Additional insights from the survey include:

  • Increased productivity (29%) and improved Overall Equipment Effectiveness (OEE) (23%) are the top benefits companies expect to gain from implementing IIoT systems.
  • Leadership support (38%) and cybersecurity (35%) are the key challenges companies cite in implementing a new IIoT system.
  • A quarter of survey respondents believed that executive leadership (25%) should own the project while nearly a quarter of respondents (23%) believe that a project team combining both OT and IT expertise should spearhead the IIoT strategy.
  • MQTT (57%) and HTTP (58%) are considered to be essential data movement tools for fulfilling IIoT strategies.
  • Sparkplug is still in its infancy but 25% of companies say they have deployed or are looking at using Sparkplug, while 35% say they need to learn more about it.
  • Microsoft Azure (18%) is the leading cloud provider for IIoT systems, followed by Amazon Web Services (17%), and multi-cloud (14%).

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