Catching up on some older news items from earlier this month. This news from Yokogawa shows how process automation companies have had to expand their offerings and problem sets to solve in this era of process automation and control market maturity. This new product is said to deliver holistic lifecycle management and operational excellence.
Yokogawa Electric Corporation announced the launch of OpreX Plant Stewardship, the most comprehensive lifecycle service program in the company’s OpreX Sustainable Maintenance family, to support customers in achieving and sustaining operational excellence.
OpreX Plant Stewardship offers a tailored, performance-based approach that strategically addresses the ever-evolving challenges faced by customers, enabling them to mitigate risks, effectively manage operational challenges, and achieve key performance indicators across all levels of their organization. OpreX Plant Stewardship is available in all regions outside of Japan.
With the acceleration of plant complexity, IT/OT integration, cybersecurity threats, and a shortage of skilled resources, traditional product-centric maintenance methods are no longer sufficient. In response to these issues, Yokogawa has expanded its lifecycle services portfolio with a program that ensures service performance across systems, field instruments, analyzers, software, and applications.
Main Features
1. A customer-centric lifecycle approach
OpreX Plant Stewardship is a service program designed through a strategic framework to drive long-term operational excellence. By proactively and systematically addressing risks and challenges, organizations can align their operational strategies with business objectives. Through this approach, Yokogawa works closely with various stakeholders across different levels of the customer’s organization, helping customers navigate complex demands and ultimately find the economic optimum that balances performance, cost, and sustainability.
2. Comprehensive coverage of five dimensions
Leveraging decades of domain expertise, Yokogawa’s service approach is built to provide coverage on five essential dimensions that drive a well-operated, efficient, and resilient business throughout the plant lifecycle:
Safety & security: Ensuring robust operational safety and cybersecurity measures are in place
Reliability & availability: Eliminating plant disruptions and improving equipment reliability
Regulatory compliance: Ensuring compliance with evolving industry regulations while supporting relevant Sustainable Development Goals
Operational efficiency: Enhancing process efficiency and reducing waste
Investment efficiency: Optimizing asset investments to maximize long-term value
3. Four-step process for continuous engagement
The four-step engagement model ensures effective collaboration with customers:
Identify: Understanding customer challenges, priorities, and operational risks through an assessment model
Assess: Evaluating which services and solutions are best tailored to address customer pain points and achieve their operational goals, and crafting a tailor-fitted, long-term collaboration proposal
Control: Ensuring seamless and effective global delivery of the services and commitment to high-quality output
Review: Continuously supporting customers through long-term engagement and improvements, utilizing a structured feedback loop to ensure ongoing performance alignment and adaptation to evolving operational needs
Major Target Markets
Oil and gas, petrochemicals, chemicals, renewable energy, power, pulp and paper, pharmaceuticals, food, mining, iron and steel, water distribution, and wastewater treatment.
A highlight of any trip to a trade fair in Germany was always the Festo stand. They turn engineers loose to build some incredible motion displays. This year at Hannover they constructed an “Incredible Machine.”
The Festo Story
It all began 100 years ago in a workshop in Esslingen am Neckar. Festo founder Gottlieb Stoll asked himself how technology could make work easier. From the initial production of machines for woodworking, the company developed into the production of pneumatic and electrical automation technology for mechanical engineering in a wide range of industries. Today, Festo is one of the world’s leading automation specialists.
To mark the company’s 100th anniversary, Festo has designed an extraordinary application, the Incredible Machine. It is not a specific product, but works on the principle of a Rube Goldberg machine, in which one movement triggers the next. The Incredible Machine demonstrates the history of automation technology from the past to the present and reflects our wide range of competencies and our comprehensive expertise.
The Incredible Machine shows the fascination for motion technologies, be it pneumatic, electric, digital or a combination of these, it presents the most important industries in which Festo operates, it inspires enthusiasm for technology and it provides an outlook on what the future of automation could look like – because inventiveness and a pioneering spirit have been part of our DNA from the very beginning.
Just as a butterfly can trigger a chain of movements by fluttering its wings, sometimes a tiny impulse can bring about significant changes. That is why our eMotionButterfly sets the machine in motion. During this journey, we look back at our history, but above all we are looking forward to the future. A motion impulse runs in 12 modules over a total length of 46 feet, triggering a chain reaction of different motion functions in the machine. More than 1000 Festo products and more than 1.12 miles of tubes and cables are installed in the machine.
Whether pushing, turning, lifting, positioning or relocating workpieces, materials and products during their production process, whether dosing, filling, throttling or pumping liquids and bulk materials in the process industry: motion is involved everywhere in industrial manufacturing processes. As a specialist in automation, Festo has made motion its core business.
The machine is not a purchasable product, but rather an innovation carrier that demonstrates the range of technical solutions in automation technology. Festo also wants to show how important freedom for creativity and inventiveness are to maintain a leading position in global competition. Festo wants to be the best partner for its customers, always at the highest technological level and as a holistic provider of electrical, pneumatic and digital solutions and – as a special USP – the matching training courses from Festo Didactic.
Innovations can solve specific problems and have the potential to change entire sectors and create new industries. The driving forces behind these innovations are the ecosystems of customers and partners who are looking for solutions to their challenges. The journey in the machine leads through specific industries, such as battery production for electric cars, laboratory automation in the life sciences, intralogistics and the semiconductor industry. It delves into the company’s history and ends with insights into the actuator technology of the future. But the momentum continues.
Motion is changing our world and will continue to do so in the future. How this change will unfold over the next 100 years remains to be seen. But one thing is certain: it will be characterized by motion and bold ideas. Through small impulses that can trigger chain reactions and ultimately lead to something big.
While I am on a standards reporting kick, this news reflects the growing collaboration among formerly competitive standards development organizations. I wrote recently about how OPAF is actively taking an end user view into standards collaboration and rationalization. Working together usually brings benefits to users.
From the statement of purpose: Accurate energy consumption data is essential for companies aiming to achieve climate-neutral production. To support this goal, a consortium of organizations has recently published a groundbreaking specification for interoperable and efficient energy management in industrial and process automation.
\A key goal of the mechanical and plant engineering industry is to achieve climate-neutral production in the future. This effort is supported by the European Union’s European Green Deal, which aims to make Europe climate-neutral by 2050. In order to achieve this goal and implement many other use cases, accurate data on energy consumption in production is crucial. The consortium, consisting of the organizations ODVA, OPC Foundation, PI and VDMA, has now jointly published version 1.0.0 of their groundbreaking specification for interoperable and efficient energy management in industrial automation and process automation. This group is chaired by the VDMA.
Dietmar Bohn, Managing Director of PNO, explains: “The measurement and analysis of energy consumption in machines and systems is an extremely important topic for the future. We are pleased to make an active contribution to this important initiative to optimize energy consumption and thereby reduce the harmful effects on the environment caused by waste and surplus.”
This specification defines a standardized information model based on OPC UA that enables comprehensive energy management in industrial automation. “This Power Consumption Management collaboration ensures that end users have a highly standardized and interoperable means of achieving their environmental, social and governance (ESG) goals,” explains Dr. Al Beydoun, President and CEO of ODVA.
The introduction of this standard will make energy management in industry considerably easier: companies can now record, analyze and use precise and consistent energy data even more efficiently in order to further increase their energy efficiency. This not only helps to reduce operating costs, but also to reduce the ecological footprint. Standardization makes it possible to implement innovative technologies and best practices faster and more effectively, which contributes to more sustainable and environmentally friendly production in the long term.
The specification essentially comprises two main content fields: Firstly, monitoring, i.e. the display of all types of energy consumption, including electrical energy as well as energy from air, water or coal. Secondly, standby management, which is understood to mean the control and display of various energy-saving modes on machines and components. It is based on the results of the research project “Development of energy management interfaces for IoT technologies (IoTEnRG)”. “The aim of the IoTEnRG research project was to make the results available to industry. We were able to contribute our results directly to the Joint Working Group and thus significantly accelerate the development of the OPC UA Companion Specification,” says Prof. Dr. Niemann from the Institute for Sensor Technology and Automation at the University of Applied Sciences and Arts in Hannover.
“For digitalization, we need an agreement on a common understanding and description of data, including in the energy sector. OPC UA provides exactly that. I am proud that with this joint group, we can also contribute to the energy transition and thus promote optimized energy savings through standardized and efficient monitoring,” says Stefan Hoppe, President of the OPC Foundation.
The VDMA has defined a fundamental standard for the entire mechanical and plant engineering industry, known as “OPC UA for Machinery”. Various functional building blocks are specified in this standard. A new building block for energy management is being developed based on the publication. “The four organizations have been working hard to harmonize and standardize information on energy consumption in manufacturing. This is an excellent first step towards defining an upcoming OPC UA Building Block for mechanical engineering that will bring the machine and plant manufacturing industry a big step closer to the goal of climate-neutral production,” says Andreas Faath, director of the VDMA Machine Information Interoperability department.
I have mixed feelings toward standards organizations and consortia. Some engineers use their work to build systems. I’m never sure what the final benefit is. Some have built technology in everyday use—OPC, ODVA, FieldComm (HART, FDT), Profinet. Some publish papers that I have hear practical outcomes emanating from.
Yet, I still report on some of these. You never know how some engineers may benefit from the work while building their systems.
This news (I’m catching up on news that came my way while traveling and thinking about what I learned there) comes from The Digital Twin Consortium (DTC), a unit of the Object Management Group. My last two trips and several subsequent interviews and press events all worked in the term Digital Twin somewhere in the discussion. So, it’s relevant.
The Digital Twin Consortium (DTC) published a whitepaper titled Spatially Intelligent Digital Twin Capabilities and Characteristics to help business executives, enterprise, business, and solution architects, system designers, and developers understand the base concept of spatial information relative to the capabilities and characteristics used to describe locational intelligence in the context of digital twin capabilities. The concepts described in the whitepaper apply to a broad spectrum of digital twin use cases, industries, and disciplines.
The whitepaper provides organizations guidance to:
Document the capabilities and resulting value streams provided through the ability to visualize, understand, and analyze the geospatial locational characteristics of real-world entities and conditions.
Understand the distinction between different forms of locational representations, including geometric (3D models), spatial, and geospatial models.
Document the key characteristics of locational representations in a digital twin so organizations can consistently capture locational attributes, enabling digital twin system-to-system integration.
Capture the Spatially Intelligent Digital Twin’s locational characteristics in the context of capabilities using the DTC’s Capabilities Periodic Table (CPT).
By completing the steps outlined in the white paper, organizations can define locational capabilities and data requirements for their digital twins. They can design, develop, and operate digital twins that meet organizational needs and provide business value.
The Digital Twin Consortium Architecture, Engineering, Construction, and Operations (AECO) Working Group prepared the whitepaper. Download the DTC website’s Spatially Intelligent Digital Twin Capabilities and Characteristics whitepaper. Become a DTC member and join the global leaders in driving digital twin evolution and enabling technology.DTC is a program of Object Management Group.
People used to (actually, still do) respond to my answer about what I cover as automation, “Oh, robots.” And I’d say, “Yes, that, too.” The robot market was pretty stagnant for quite a time until the cobot flurry from Denmark. Then, quiet again for the most part. Something interesting does come my way at times. The current topic seems to be expansion of software control to make robotics easier to use and with expanded repertoire.
Flexxbotics announced the latest release of FlexxCORE, the patent-pending technology at the center of the Flexxbotics solution. The new release delivers more powerful capabilities for advanced robotic machine tending, robotic quality control, and robotic production lines by enabling robots—both industrial and collaborative—to run multiple machines with multiple operations for multiple part SKUs. These new FlexxCORE capabilities equip manufacturers to scale robotic production across the smart factory in a standardized way for greater plant capacity, quality, and EBITDA margins.
FlexxCORE now includes enhanced robot awareness, parallelized data pipelines, and greater data granularity which further extends the interoperable communication and coordination between robots, factory machines, inspection equipment, and other plant machinery.
Enhanced Robot Awareness – Empowers robots in advanced tending scenarios to interpret each machines’ jobs, processing routines, operational status, and more
Parallelized Data Pipelines – Leverages asynchronous, parallel pipelines for hyperperformant real time robot+multi-machine orchestration
Greater Data Granularity – Expanded data model and event data capture for robotic operational context, pattern recognition, and machine learning
FlexxCORE is a low-code environment for composing and running Transformers – powerful translation driver connectors – which includes a secure, high performance run-time framework with data pipelines, protocols, class structures, method sets, and data models for development. Transformers enable bi-directional read/write between robots and all types of factory equipment for many-to-many interoperability.
FlexxCORE delivers compatibility with over 1000 different makes and models of robots, machines, other factory machinery and inspection equipment options, and enables 22x faster connector creation than conventional automation integration methods.
Now, global companies can roll out production robotics across the smart factory in a standardized way for advanced robotic machine tending to enable:
Robot+Multi-Machine Orchestration—Robots control multiple machines simultaneously to achieve longer unattended robotic production for “lights out” manufacturing.
Robotic Processing of Multiple Parts—Coordinated robotic production of numerous different part types or SKUs within a part family while managing multi-step processes.
Robot Multi-Job Work Order Staging—Work order changeovers detect order completion – including FDA regulated Line Clear – and update part properties for the next order in-feed.
Autonomous Process Control—Offset parameters adjusted in real time directly in the machine controller’s G-code for process control autonomy, improving quality and digital thread traceability.
Future-Ready Agility—Enables the flexible adoption of new breakthroughs – such as AI-driven processes – to quickly adapt to new market realities and rapidly changing conditions.
Keeping track of the many changes within the cybersecurity solution ecosystem takes more time than I can devote. I’m glad my old colleague Greg Hale made that his focus. Rubrik first came to my attention just a couple of months ago. They did get a mention in a post several years ago as an executive invested in a company that never crossed my path again.
Rubrik’s unique proposition is resiliency. In this news, the company announced capabilities related to users of Google Cloud.
In its ongoing commitment to deliver comprehensive cyber resiliency, Rubrik announced April 9 upcoming capabilities designed to help ensure Google Cloud customers can quickly recover their business from a cyberattack or operational disruption.
“As organizations increasingly shift their business-critical data to the cloud, they’re confronted with new challenges in protecting sensitive information against rapidly evolving cyber threats—challenges their traditional security technologies simply can’t address,” explained Anneka Gupta, Chief Product Officer at Rubrik. “We aim to empower Google Cloud customers to address these challenges with confidence, enabling them to strengthen their cyber resilience, streamline data protection, optimize backup and recovery processes, and ensure business continuity in the face of any cyber incident.”
“For organizations navigating today’s complex cyber threat landscape, comprehensive cyber resiliency is non-negotiable,” said Stephen Orban, Vice President of Migrations, ISVs, & Marketplace at Google Cloud. “Our collaboration with Rubrik provides customers with the tools and technologies to establish isolated recovery environments on Google Cloud, fortified by the proactive security insights and expertise of Mandiant.”
Precisely designed for Google Cloud, this collaboration delivers:
Cloud-Based Isolated Recovery Environment in Google Cloud – Rubrik, in collaboration with Mandiant, is developing a cloud-based isolated recovery solution on Google Cloud. This solution is designed to enhance organizational cyber resilience by ensuring business-critical data backups are secure from cyber threats and efficiently, safely replicated to Google Cloud via Rubrik’s Secure Vault after an incident. By leveraging Rubrik’s Data Threat Analytics and Orchestrated Application Recovery Playbooks, combined with Mandiant’s periodic security assessments and Incident Response services, it aims to establish a secure recovery environment on Google Cloud, to enable swift core application restoration and business continuity.
Strengthened protection of Google Cloud Engine and Google Cloud SQL – New threat-analytics capabilities are planned for Anomaly Detection, Data Discovery and Classification, Turbo Threat Hunting, and Threat Monitoring. These capabilities are designed to work together to proactively detect cyber threats, accelerate incident response and recovery, and ensure sensitive data remains protected and compliant.
Enterprise-grade protection for Google Workspace – Rubrik’s solution is designed for Google Workspace customers, to help them protect their mission-critical SaaS data from cyber threats, insider risks, and accidental deletion, through newly-offered immutable backups, automated anomaly detection, and rapid, granular recovery.
Rubrik’s strengthened protection of Google Cloud Engine is available now. New threat analytics capabilities, expanded protection of Google Cloud SQL, expanded protection of Google Workspace, and Cloud-Based Isolated Recovery Environment are planned to be generally available at a later date.
The media relations person found me somehow tempting with this teaser:
Converting natural language into code – Transform vague or unstructured instructions into precise, actionable code through AI-driven natural language processing.
Enhancing automation, accuracy, and efficiency – Minimize manual input and errors, optimizing every stage of the design-to-production lifecycle with intelligent automation.
Seamlessly integrating with existing tools – Leverage AI to integrate effortlessly with existing design and manufacturing software, ensuring full compatibility with established engineering tech stacks.
OK, this is general, full of the latest buzz words. Reading between the lines of this and her emails, I thought I detected the seeds of an answer to problems I had working in engineering data management in the late 70s. So, I consented to an interview (I do few of these anymore) with Foundation EGI co-founder Wojciech Matusik, Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory at MIT.
This decision was one of my best lately. Matusik laid out a coherent, logical, precise definition of what this company (that launched last week) defines as the problem and the solution it intends.
These are my words—I see what they are doing as the crucial step between PLM and MES. That’s a bit to crude, but bear with me.
Early in my career, the VP of Product Development for a manufacturing company picked me for the role of data manager. From the foundation of managing the bills of materials and specifications generated by product design communicating with other departments such as manufacturing operations, cost accounting, and purchasing. These placed me at the center of cost control and reduction efforts (Hello, Elon, I could have helped you do a better job!).
Matusik began with the premise that engineering is programming, that is, it generates a set of rules in a domain-specific language. Look at assembly, for example, it is a small set of operations from a small domain. From this, one could construct a domain-specific program for any set of tasks. (I call this workflow—something I’ve seen MES developers trying to perfect for more than a decade.)
A coding assistant would be a great help developing these task programs. AI helps today’s software engineering become more efficient. Why not use the same tools for this problem? Enter Foundation EGI. Natural language programming of these “rules” for building from the engineering design data.
Construct domain
Program compilers
Data Sets
Then use LLMs and so forth
They are building a platform. Engineering change notices built-in. Focus on the most boring of engineer’s work, leave to the engineer the most creative. They hate the add-on administrative work. They integrate with a variety of CAD files and works either with PLM or not. Also fits well with robotics with automated coding assistant.
Like I have told a few founders whom I’ve interviewed, I am enthusiastic about the potential of your platform—I’m interested in seeing how the technology actually works out.
On Thursday, April 17, Foundation EGI launched, announcing the availability of the first domain-specific, agentic AI platform — engineering general intelligence (EGI) — designed to supercharge automation, accuracy, and efficiency for every stage of product lifecycle management. With EGI, design and manufacturing engineers will be able to build better products faster, driving healthier revenues for the world’s leading industrial brands. To sign up to be part of the beta, interested customers can sign up here.
Foundation EGI was co-founded by MIT academics Mok Oh, Ph.D, Professor Wojciech Matusik, and Michael Foshey, and has assembled a seasoned team with deep engineering, industrial, startup and AI experience. Backed by an over-subscribed $7.6M seed round from early investors including E14 Fund, Union Lab Ventures, Stata Venture Partners, Samsung Next, GRIDS Capital, and Henry Ford III, Foundation’s EGI platform is already in testing at leading Fortune 500 industrial brands, which are witnessing its transformative and revenue-driving potential.
Unlike other digitally-transformed industries, manufacturing and engineering processes and instructions remain manual and disorganized, causing inefficiencies, production delays and stagnant revenues — to the tune of $8T in economic waste. Using Foundation EGI’s purpose-built large language model (LLM) and EGI agentic AI platform, engineers can now transform natural language inputs, including vague and messy instructions, into codified programming that is accurate and structured, optimizing automation, accuracy and efficiency at every stage of the design to production lifecycle. Foundation EGI’s web-based technology platform seamlessly integrates with the major design and manufacturing software applications and tech stacks already used by engineering teams.
“Engineering is primed for an AI revolution, but generic LLMs won’t cut it: they lack vital domain-specificity and are prone to inaccuracies,” said Foundation EGI co-founder and CEO, Mok Oh. “Our first-of-its-kind technology is purpose-built for engineering and will supercharge every stage of product lifecycle management — starting with documentation. EGI transforms what is traditionally error-prone, manual and inconsistent into structured, sustained and accurate information and processes, so that engineering teams can not only achieve significant cost-savings but also be more nimble, productive and creative.”
Dennis Hodges, CIO at Inteva Products, a global automotive supplier of engineered components and systems, commented: “We have high expectations from Foundation’s EGI platform. It’s clear it will help us eliminate unnecessary costs and automate disorganized processes, bringing observability, auditability, transparency and business continuity to our engineering operations.”
Said Habib Haddad, founding Managing Partner of the E14 Fund, the MIT Media Lab affiliated venture fund: “The timing and market conditions are perfect for a company like Foundation EGI to solve what has long been a large and expensive challenge for America’s industrial manufacturing leaders. The combination of Foundation EGI’s vision, its world-class team, the widespread industry appetite for enterprise AI solutions, plus the uptick in manufacturing demand makes this a rich opportunity.”
Co-founder Wojciech Matusik, Professor of Electrical Engineering and Computer Science at the Computer Science and Artificial Intelligence Laboratory elaborated on EGI’s potential, “Engineering general intelligence transforms natural language prompts into engineering-specific language using real-world atoms, spatial awareness and physics. It will unleash the creative might of a new generation of engineers. Expect leaps and bounds in agility, innovation and problem-solving.”
Foundation EGI’s mission was inspired by research conducted by Professor Matusik, Michael Foshey, and others at MIT and other academic institutions, published in a March 2024 paper titled “Large Language Models for Design and Manufacturing.”
The Open Group Open Process Automation Forum (OPAF) provides annual updates at a forum in Orlando in February. I missed that meeting, however recently receiving an update from Aneil Ali, The Open Group OPAF Director.
OPAF members have worked diligently for years developing a standard of standards in order to break the proprietary grip of specific process automation suppliers—hence the word “Open” in the name. Owner/operators facing needed technology upgrades balked at the price of rip-and-replace automation.
I have seen these efforts a few times in the past. The results have provided benefits, but usually far from the vision of the founders.
This organization continues to move forward. They have released version 2.1 of the standard, launched a product certification program, and have witnessed some products making it through the system.
The headline news is ExxonMobil’s Lighthouse project. They have operationalized the OPAF system at a resin finishing plant in Baton Rouge at tail end of 2024. Engineers beat deadlines for startup. They have published some good lessons learned from the project. It’s the first deployment of a commercial OPAF system making money for the owner/operator.
One complaint levied over the years concerned the proliferation of standards, many of which are not interoperable. OPAF has addressed standards harmonization hosting for the fourth year standards harmonizing meetings in Eastern Hemisphere. Recently one was in Germany with FieldComm, OPC UA, Namur, OPAF, PI. They typically meet for three days looking for where there is a risk for divergence and potential problems for endusers.
Ali noted the OPAF have started a regular cadence of user meetings as an effort to get them together to air wishes/desires. These thoughts can be distilled to assignments for working groups.
Ali concluded, “The Forum always open to receiving guidance and feedback from end users not in the ecosystem—we’re not a closed club.”
The Aras ACE2025 Community Event in Boston closed two weeks ago. It has taken me that long to wrap my head around everything I learned. Normally there are many really important-sounding words that sound so enlightening at the time, yet when I sit to write I find no substance. In this case, there was so much substance that I have trouble filtering to the most important themes.
Let’s say that not only were the expected buzz words in evidence but the underlying concepts were demonstrably in use. Aras is a PLM (product lifecycle management) developer. They are solving problems that I had in the late 70s while working at a manufacturer. Mainly, how to make usable sense from all the engineering data.
The principle phrase of the week was digital thread. They are all about the digital thread. Companies were also using Large Language Model (LLM) technology trained on their own data. Agentic AI rears its head and will become even more important with use. (See my interview with John Harrington of HighByte for more on Agentic AI.)
Customer presentations that showcase actual use cases provide reality to the theory.
I sat in a presentation by the sensor manufacturer Sick. They have applied AI to unstructured data turning them into useful structured data. Using Aras PLM, they have realized better speed to market finding product data via natural language query. They have instances of development times cut from 3 years to 6 months.
Another customer presentation came from Denso. Engineers find the digital thread from PLM as a tool for collaboration. The connected flow of data ensures continuity from design to manufacturing to operations. Inconsistent data hurts the business. PLM is the heart of their digital strategy with the BOM as centerpiece. Once again an example of someone actually using GenerativeAI trained on their data to fill in gaps.
The highlight of customer applications came from my half-hour discussion with Tetsuya Kato, Manager of the Technical Management Group from SkyDrive in Japan—the Flying Car company. OK, it’s not the Toyota in your driveway suddenly flying to the store. But it’s close. Check out the goodies on their website.
He was hired to bring order to the product information system. In other words, to develop a better Manufacturing Bill of Materials (MBOM). They were using Team Center PLM with a system brought in by a consulting engineering firm. The system had many problems, was taking too long to implement, and forced SkyDrive to change its systems to fit the software.
Kato brought in Aras Connector to bring engineering data from Team Center to the Aras PLM platform. He started the project in September, showed results in two months, and moved all the data in eight months. The Aras solution had all the features necessary for their manufacturing data with the additional benefit of flexibility to allow them to make the system work for them instead of the other way around.
Chief Technology Officer Rob McAveney asks “What if…”
McAveney noted Aras has 25 years of asking what if…
2001 What if PLM could be flexible, webnative platform?
2005 What if PLM applications were built to work together? Integrated data now called digital thread.
2011 what if impact analysis were an interactive experience? Wizard style digital thread.
2014 what if visual collaboration was available to everyone?
2021 What if a SaaS delivery model came without compromise?
2025 What if we could extend reach of the digital thread? Take advantage of Aras Effect, open, reachability; Aras Portals, apps product data platform, composable PLM apps, low code environment?
The digital thread + AI = Connected Intelligence:
The three areas of Connected Intelligence include:
Discover—conversation about data
Enrich—connect more data and people business
Amplify—maximize impact
Pursuing all three together
Discover—natural language search, content synthesis, machine learning, text to SQL (natural language prompt to query; what if guided tour how to set effectivity conditions to sync multiple changes (context aware help), then phase in changes with confidence, eliminate rework and supply chain, what if assess global supply of a sourced component before submitting a change request, avoid wasting time on changes; what if you could ask AI assistant to ID common factors while root cause analysis, persistent quality issues become a thing of the past.
Enrich—entity recognition, contextual reasoning, topic modeling, deep learning, what if missing of inconsistent links in digital thread could be easily identified and corrected, patterns, downstream analytics, stop wasting effort on redoing work, what if requirements could be automatically identified and ingested from reliable external data sources, then see next level requirements traceability with dynamic requirements, what if factory floor data could be linked to quality planning parameters, planning for feedback loop.
Amplify—agentic AI, surrogate modeling, generative engineering, reinforcement learning, what if engineer-to-order business could be transformed by leveraging all your past engineering work to create a common variability model, engineer shift for individual customer projects to improving full product line.
Many years ago in a galaxy far away, I actually sold an MRO software solution to one of my clients. Fortunately, I left that position to become a senior editor at Control Engineering magazine never learning how it all worked out.
This news concerns a partnership between an MRO software supplier and a services provider said to deliver “technology technology-drive solutions.”
Companies leverage expertise in MRO Supply Chain optimization technology to drive a more efficient, data-driven future
Partnership empowers tire & rubber company to achieve significant MRO inventory optimization across its North American Plants
Verusen, the industry leader driving AI MRO (maintenance, repair, and operations) supply chain and inventory optimization, announced it has expanded its strategic partnership with Advanced Technology Services, Inc. (ATS), a leading industrial maintenance, technology and parts services provider. The collaboration integrates Verusen’s AI platform with ATS’s deep industrial maintenance and reliability expertise to deliver technology-driven solutions for manufacturers. Today’s news builds on the recent announcement that ATS is now a strategic partner of Verusen’s AI-driven platform in North America. The partnership expands the companies’ reach and ability to assist manufacturers in optimizing demand forecasting and inventory management across their MRO supply chains.
The collaboration’s success is exemplified by its impact on a joint tire and rubber customer, which has realized $10M+ cost reductions through MRO inventory optimization across its North American Plants. This achievement underscores the practical value and significant opportunity the Verusen and ATS offering provides.
The Verusen and ATS Partnership Addresses Key Elements of MRO to drive cost savings and inventory optimization through the following:
Supplier Tail-spend Management: Negotiating favorable pricing and lead times with reliable strategic suppliers.
Network Inventory Visibility: Using more robust, AI-driven inventory tracking to monitor real-time stock levels.
Predictive Maintenance: Using data analytics to predict potential equipment failures and proactively order spare parts.
Verusen’s platform is designed to optimize Maintenance, Repair, and Operations (MRO) inventory management using artificial intelligence, helping businesses streamline their supply chain by providing insights and recommendations based on their MRO data across different systems, ultimately ensuring the right materials are available when needed to minimize downtime and operational disruptions.
