Stay Sharp in Digital Engineering

Razorleaf Corp.

Welcome to 'Stay Sharp in Digital Engineering,' the ultimate podcast for all things digital in the manufacturing industry by Razorleaf. Join us as we take a deep dive into the multifaceted world of digital transformation, exploring topics such as the digital thread, digital twins, IDEs, model-based strategies and delving into the frontiers of cutting-edge technologies like PLM, MES, Integration, and more. Our expert hosts, Jonathan Scott, Jen Ferello, Juliann Grant, and Eric Doubell, will be your guides, providing valuable insights, captivating interviews, and the latest industry updates to ensure you remain at the forefront of the ever-evolving digital landscape. Whether you're a technology enthusiast, a business leader, or simply curious about the digital realm in manufacturing, this podcast is your essential resource for staying sharp and well-informed.

  1. 6d ago ·  Video

    #155: The Future Platform for Hardware Engineering: The Report Explained

    Is PLM dying, or has the engineering world simply outgrown it? Juliann Grant and Jonathan Scott welcome back industry veteran Doug Macdonald for round two to unpack his report, The Future of Product Lifecycle Management: After Forty Years, Where Are We and What's Next? Doug makes the case for FPHE (Future Platform of Hardware Engineering), a new category designed to replace legacy PLM systems that no longer fit the complex, multi-disciplinary nature of modern hardware development. Key Takeaways The Complexity Gap: Products have evolved from purely mechanical parts to complex systems with electronics, wireless tech, and embedded software, but legacy PLM hasn't kept pace.Beyond MCAD: FPHE platforms are independent of mechanical CAD and focus on connecting data across the whole product life cycle—from system requirements to field service.The Reality on the Ground: Many engineering organizations rely on broken integrations, spreadsheets, and manual communications because traditional systems fail to manage cross-discipline workflows.An Emerging Market: Early FPHE pioneers like Cognyx, Daluss, EXP Software, Flow Engineering, Intercax, Makersite, SPREAD AI, and Violet Labs are tackling these modern challenges, though broad adoption faces hurdles against established vendors.Guest Info Doug Macdonald: Lifelong innovation enthusiast, former developer, consultant, and marketer across companies like PTC, SAP, Sherpa, and Aras. Resources Mentioned Report: The Future of Product Lifecycle Management: After Forty Years, Where Are We and What's Next? by Doug MacdonaldEmail the show: podcast@razorleaf.comEnjoying the show? Subscribe on Apple Podcasts or Spotify, leave us a review, and share this episode with an engineer or digital strategist who needs to hear it! Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

  2. Sep 22 ·  Video

    #154: Operational Digital Twins: Closing the Speed Gap

    In this episode of Stay Sharp in Digital Engineering, hosts Juliann Grant and Jonathan Scott are joined by Prithvi Singh Chauhan, Machine Learning Engineer at Geminus AI. They explore the practical application of AI and machine learning to operational digital twins across oil and gas, manufacturing, and energy systems. The discussion covers why traditional physics models fall short in real-time operations and how combining physics-native engineering with fast machine learning solves speed, staleness, and domain silos. Key Takeaways Traditional physics-based digital twins are built for design and back-office engineering, making them accurate but often too slow, stale, and siloed for live operations.Scientific AI embeds fundamental laws of physics directly into machine learning models, providing millisecond-level predictions while staying reliable under unseen operating conditions.Multimodal AI enables systems to process varied data sources together, including sensor time series, lab reports, simulator outputs, and engineering drawings.Self-calibrating digital twins reduce manual recalibration cycles from months to real time, preventing operational drift and enabling better decision-making.The frontier of operational digital twins includes multi-system connected models, self-maintaining architectures, probabilistic risk outputs, pre-trained foundation physics models, and LLMs acting as conversational interfaces to orchestrate physics engines.Key Terminology: Scientific AI: Machine learning models with built-in physics equations (conservation of mass, energy, equations of state) rather than pure data inference.Multimodal AI: Absorbing disparate formats, frequencies, and data streams across complex engineering workflows.World Models: Pure observational learning versus physics-grounded models in live industrial environments.The AI-Enabled Digital Twin Stack: A layered breakdown covering the physics layer, data abstraction layer, physics-native models, continuous calibration, and decision optimization.The Future of Industrial AI: Connecting multi-unit constraints, models that self-detect drift, foundation models for physics, and using LLMs as orchestration interfaces.Guest Info Prithvi Singh Chauhan is a Machine Learning Engineer at Geminus AI, where he builds physics-native AI systems combining machine learning, high-fidelity simulation, and optimization for large-scale energy systems. His work spans assets across North America, Guyana, the Middle East, India, Malaysia, and Australia. He holds an M.Eng. in Petroleum Engineering from Texas A&M University and a B.Tech. from IIT (ISM) Dhanbad. Named SPE's 2026 Young Engineer of the Year and an inventor on four US patent applications, Prithvi has co-authored around 17 peer-reviewed papers and serves as Program Chair for SPE's Data Science and Engineering Analytics technical section. If you enjoyed this episode, please subscribe, rate, and leave a review on Spotify, Apple Podcasts, or wherever you listen to podcasts. Share this episode with colleagues and friends working in digital engineering, energy, and industrial operations! Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

  3. Sep 15 ·  Video

    #153: Zero Downtime, No Disruptions: Honeywell's MES Upgrade Story

    Halfway through a live database migration, Honeywell’s team lost their server connection. With no way to tell whether the scripts were running or failing, all they could do was wait. In this episode of Stay Sharp with Razorleaf, hosts Juliann Grant and Jonathan Scott sit down with Ryan Sims (Senior IT Engineer at Honeywell) and Brian Neff (MES Technical Team Lead at Razorleaf) to discuss how Honeywell Aerospace successfully upgraded its Solumina MES with zero shop floor disruptions. Key takeaways from the episode: The Drivers Behind Upgrading: How addressing deferred maintenance prevents today's stable systems from becoming tomorrow's technical debt.Parallel Infrastructure Strategy: Standing up new Kubernetes application clusters in advance while leaving active production running for a seamless cutover.The Power Outage Test: How a sudden network connection drop during database migration proved the value of an immediate, executable rollback plan.Testing Beyond Release Notes: Why unit, integration, and user acceptance testing (UAT) must focus on end-to-end business processes, database triggers, and hidden code dependencies.Post-Go-Live Risk Mitigation: Preserving a legacy QA environment post-launch as an insurance policy to isolate new bugs versus pre-existing system issues.Main Episode Points Why Modernize MES Infrastructure? Honeywell originally implemented Solumina to replace two legacy, high-tech-debt MES solutions. To keep Solumina from becoming tech debt itself, Honeywell needed to move off aging Red Hat 7 operating systems to Red Hat 8, transition to version i110.2, and simplify its underlying landscape by dropping MongoDB dependencies.  Architecting a Zero-Disruption Strategy To protect shop floor productivity, the team provisioned new application servers for the new Kubernetes cluster well before launch day. By maintaining existing ActiveMQ and Apache reverse proxy servers, they eliminated the need for IP or DNS changes across plant users and key integrations like SAP and Teamcenter. Cutting over—or rolling back—was as fast as switching a URL rewrite rule and restarting Apache.  Managing Unexpected Hurdles During the migration weekend, a power outage in a neighboring building disrupted the database connection. Because SQL logs filled up during the blind run, the team relied on a pre-planned full database backup to restore and re-run upgrade scripts without delaying operations. Later, when a minor SAP bill of materials (BOM) integration issue arose during post-launch smoke testing, the technical team authored a pre-processing fix within hours. Best Practices for Enterprise System Upgrades Leverage Non-Production Environments: Work through dev, test, and sandbox stages to refine custom IT security scripts before touching production.Set Go/No-Go Checkpoints: Establish strict time thresholds for rollback decisions using real-world data timing tests.Keep Old Environments Alive Temporarily: Maintain the previous version in a non-production QA state to verify whether post-launch issues are new or legacy.Audit Scheduled Tasks: Ensure legacy background tasks and cron jobs are disabled so old system nodes do not auto-start after server reboots.Guest Information Ryan Sims - Senior IT Engineer at Honeywell in Muncie, Indiana. Ryan supports the Solumina environment for Honeywell Aerospace in Clearwater, Florida, having managed seven non-production and production instances.Brian Neff - MES Technical Team Lead at Razorleaf. Brian brings over 20 years of experience across software development, database architecture, and Agile technical leadership.Resources Mentioned ●      Razorleaf Corporation ●      iBase-t Solumina MES Enjoyed the episode? Subscribe to Stay Sharp with Razorleaf on Apple Podcasts, Spotify, or your favorite podcast app.  Share this episode with fellow engineering and manufacturing IT leaders!  Have a question or topic suggestion? Email us directly at podcast@razorleaf.com. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

  4. Sep 8 ·  Video

    #152: OpenBOM's New AI Agents Solving the Problems Everyone Ignores

    Digital engineering is moving fast, but the fundamental challenge remains: how do you get your mechanical, electrical, and procurement data to "talk" to each other? In this episode, we dive deep into the "Product Memory Flywheel" with Oleg Shilovitsky, co-founder and CEO of OpenBOM. We explore how OpenBOM is using AI agents to solve the industry's most persistent, "boring" problems—like CAD file management and Bill of Materials (BOM) errors—and why fixing these unglamorous issues is the key to true digital transformation. Key Takeaways ●  The Product Memory Flywheel: Learn about the concept of a data context layer that collects information from disparate systems (PLM, ERP, CAD) and activities. It creates a structured foundation for AI to reason across your entire product development lifecycle. ●  Solving "Boring" Problems: Oleg argues that real innovation doesn't always come from flashy tech, but from solving the painful, mundane tasks engineers hate. We discuss how prioritizing these pain points creates the most immediate value. ●  Agentic Workflows: CAD File Agent: A new, chat-based interface that handles file management, versioning, and syncing, shielding engineers from the complexities of traditional PDM systems.BOM Review Agent: A tool that utilizes "Check Cards" to automate validation, highlight errors (like quantity mismatches), and facilitate team collaboration directly within the BOM.●  The Future of Intelligence: How the "Flow" concept integrates data across enterprise systems, allowing companies to transition from manual, error-prone processes to a streamlined, automated digital thread. Featured Guest ●  Oleg Shilovitsky: CEO and Co-founder of OpenBOM, and author of the widely-read industry blog Beyond PLM. With over 25 years in the data management and manufacturing space, Oleg brings a unique perspective on bridging the gap between engineering and the supply chain. Resources & Links ●       OpenBOM: Explore the platform and its latest AI capabilities. ●       Beyond PLM: Oleg’s blog on PLM, digital transformation, and modern manufacturing strategies. Support the Show  If you enjoyed this episode, please subscribe, follow, and leave a review. Your feedback helps us bring you more content on the future of digital engineering.  Share this episode with a colleague who is tired of fixing BOMs in Excel!  Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

  5. Sep 1 ·  Video

    #151: The Untold Origins of PLM, with Doug Macdonald

    How did we get from CAD and PDM to the PLM systems we use today? And have we really moved beyond PDM? In Stay Sharp Episode 151, hosts Juliann Grant and Jonathan Scott sit down with Doug Macdonald, a longtime PLM industry veteran and self-described “lifelong innovation enthusiast and recovering advocate for PLM,” to explore the history of product lifecycle management—and how the technology evolved alongside the products and businesses it was designed to support. Doug has been part of the industry since the early days of CAD/CAM and PDM, working across development, consulting, sales, advocacy, and marketing roles at companies including PTC, SAP, Sherpa, Aras, and CIMdata. His career provides a unique perspective on how the technology evolved and why some of the fundamental assumptions behind today's PLM platforms still remain. From CAD Files to PDM The conversation begins with the emergence of PDM as CAD moved into the mainstream. What started as a practical need to manage files, versions, and engineering data gradually became something much more significant. As companies accumulated more product data in centralized repositories, managing versions and protecting that information became increasingly important. The repository itself also created an unexpected consequence: once a company's intellectual property and product history were deeply embedded in a system, moving to another CAD platform became considerably more difficult. How PDM Evolved into PLM From there, the discussion follows the evolution toward PLM. As products became more complex, organizations needed to manage more than CAD files. Parts and assemblies led naturally to bills of material (BOMs), while increasing amounts of product data created a need for change management and configuration management. The terminology evolved as well. The industry moved through concepts such as PDM, collaborative product commerce (CPC), and ultimately PLM—even though many of the underlying capabilities were continuing to evolve rather than being completely reinvented. Has PLM Really Moved Beyond PDM? One of the central questions of the episode is whether PLM ever truly became something separate from PDM—or whether much of PLM remains an extension of PDM. Today's PLM platforms may include capabilities for quality, materials management, software, electronics, and other aspects of the product lifecycle. Yet, as Jonathan and Doug discuss, many organizations still primarily use these systems for managing CAD data, versions, structures, and related engineering information. That creates an interesting gap between the vision of PLM and how organizations actually use it. The MCAD Connection The conversation also examines the continued influence of mechanical CAD on the PLM market. Many of the industry's largest PLM platforms remain closely connected to CAD, and the hosts explore how that relationship may influence both product strategy and the architecture of today's systems. If MCAD remains a major source of revenue, there is an obvious incentive to continue building around that foundation. But products and manufacturing organizations have changed. Modern companies increasingly operate through complex global supply chains and collaborative networks rather than the highly vertically integrated models that characterized earlier generations of manufacturing. The question becomes whether today's PLM architectures have evolved enough to support that new way of working. Why Aren't Companies Using More of Their PLM Capabilities? If PLM platforms contain so many lifecycle capabilities, why aren't organizations using all of them? The discussion considers whether some modules were developed around the requirements of individual customers or particular historical markets rather than broader industry needs. A capability can exist within a platform without necessarily being the right fit for the way organizations operate today. This raises a larger question about the future of PLM: Are today's platforms designed for the manufacturing world we have—or the manufacturing world we used to have? What You'll Take Away In this episode, you'll hear: How CAD/CAM helped drive the emergence of PDMWhy managing versions and product data became such a critical problemHow PDM evolved toward BOM management, change management, and ultimately PLMThe role of collaborative product commerce in the industry's evolutionWhy PLM may still be heavily rooted in PDMHow the continued connection between MCAD and PLM influences the marketWhy some organizations aren't using the full range of capabilities available in PLM platformsHow the shift from vertically integrated companies to complex supply-chain networks challenges traditional PLM architecturesWhy understanding PLM's history may be essential to understanding where it needs to go nextWhat's Next? This conversation is only the beginning. Doug will return for a future episode to discuss where PLM and product platforms are headed next—and what the next generation of these systems may look like. Listen to Episode 151 and then stay tuned for the next conversation. Have thoughts about the evolution of PLM? Leave us a comment—we'd love to hear what you think. Until next time, stay sharp! Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

  6. Aug 25 ·  Video

    #150: 150 Episodes In - What We Got Right (and Wrong) in Digital Engineering

    150 Episodes of Digital Engineering Conversations—and Counting It’s a milestone worth celebrating: Stay Sharp in Digital Engineering has reached 150 episodes! In this special episode, co-hosts Juliann Grant and Jonathan Scott take a break from the usual guest format to look back at nearly three years of Stay Sharp. Together, they revisit the topics, trends, guests, and conversations that have shaped the podcast—and consider what’s still left to explore. From the beginning, the podcast has focused on the rapidly changing world of digital engineering, manufacturing, and product development. But as the hosts reflect on 150 episodes, one thing becomes clear: while the technology continues to change, many of the fundamental challenges remain remarkably consistent. From PLM to AI—and Everything in Between PLM has been a recurring theme since the earliest episodes. The hosts revisit the early What Is PLM? series, which remains one of the podcast's strongest-performing topics, and discuss why questions about PLM's role within the enterprise are still relevant today. They also look at how the conversation has expanded into other areas, including MES, quality, integration, migration, and data management. These may not always be the most glamorous subjects, but they are often where digital transformation succeeds—or fails. AI has become another major theme. While the hype around AI can sometimes feel repetitive, Juliann and Jonathan discuss why the conversation continues to evolve as companies move from experimentation toward practical implementation. A recurring lesson from many of their AI conversations is the importance of the underlying data foundation—and the fact that there is still no single answer for how organizations should approach it. Digital Twins, Digital Threads and MBSE The podcast's Digital Twin series gave the hosts an opportunity to explore a term that is often overused and misunderstood. Conversations with practitioners helped put digital twins into context and demonstrate how organizations are applying the concept in the real world. Digital thread has been another important—and still evolving—theme. Rather than viewing digital thread as a single project, the hosts describe it as an incremental process of connecting data and information across systems and business processes. Model-Based Systems Engineering (MBSE) is another topic they expect to remain relevant for years to come. Discussions with experts including Chris Finley and David Long helped demonstrate both the practical applications of MBSE and why it extends well beyond the traditional examples many people associate with it. The Less Glamorous Side of Digital Transformation Some of the most valuable conversations have focused on topics that don't always generate headlines: integration, migration, data quality, and unstructured data. The hosts reflect on conversations about everything from the massive amounts of information associated with aircraft to CAD migration and the challenges of moving data between systems and formats. These discussions reinforce an important reality: digital transformation isn't just about adopting new technology. It also means dealing with the existing data, systems, processes, and technical debt that organizations have accumulated over time. Digital Engineering and the Defense Industrial Base The podcast also spent considerable time exploring digital engineering and the defense industry, including cybersecurity, CMMC, and the Defense Industrial Base (DIB). Juliann and Jonathan discuss the potential opportunities for small and midsize manufacturers to participate in the DIB, as well as the challenges organizations face as cybersecurity and compliance requirements evolve. The People Behind the Technology Technology may be at the center of digital transformation, but many Stay Sharp conversations have highlighted another critical factor: people. The hosts discuss the importance of organizational culture, adoption, change management, partnerships, and the relationships between technology providers, customers, service providers, and systems integrators. Their Digital Product series has also provided an opportunity to go beyond product features and specifications to understand the people and cultures behind different software companies. As Jonathan points out, conversations reveal things about a company that aren't always apparent from a website or product sheet. A Few Favorite Guests With 150 episodes and an impressive roster of guests, there are plenty of conversations worth revisiting. Juliann and Jonathan highlight several memorable guests, including Brion Carroll, Patrick Hilberg, Jos Voskuil, Michael “Fino” Finocchiaro, Martin Eigner, Chris Finlay, David Long, Dan Miklovic, and others. They also give a special shout-out to Jen Ferello, who helped get the podcast off the ground and remains an important part of the Stay Sharp story. And, of course, the hosts recognize the many guests who have shared their expertise throughout the first 150 episodes. What's Next for Stay Sharp? Reaching 150 episodes isn't the end of the conversation. If anything, the hosts discover that there are still more questions than ever. They want to hear from listeners about the topics they should cover, companies and industries they should explore, and guests they should invite onto the show. They also plan to use LinkedIn surveys to make it easier for listeners to weigh in. Most importantly, Juliann and Jonathan thank everyone who has listened, shared feedback, approached them at conferences, appeared as a guest, or helped make the podcast possible. After 150 episodes, Stay Sharp in Digital Engineering is still doing what it set out to do: having thoughtful conversations about the technology, people, and ideas that help professionals stay sharp in digital engineering. Here's to the next 150 episodes. Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

  7. Aug 18 ·  Video

    #149: Product Memory: The Context Layer Behind Every Product Decision

    In this episode, we sit down with Oleg Shilovitsky, industry expert, author of Beyond PLM, and CEO of OpenBOM, to explore a transformative concept he calls "product memory." If you’ve ever looked back at a product design decision two years later and wondered, "Why did we make that choice?", you aren't alone. Oleg explains why product memory is the missing context layer that connects decisions to data, filling the gaps that traditional PLM, PDM, and ERP systems often miss. We discuss the "three parents" of product memory—including the critical role AI plays as a forcing function—and dive into the complex questions surrounding data ownership, security, and the future of business models in a post-SaaS world. Key Takeaways: What is Product Memory?  It’s a context layer that captures the "why" behind decisions, relationships, and conversations across a product's lifecycle—not just the static records found in PLM.The Three Parents of Product Memory: The concept is born from the need to capture decision-making context, the technological capability of context graphs, and the acceleration provided by AI agents.AI as a Forcing Function: Unlike previous tech trends (like cloud adoption), AI requires structured context to be effective. Without proper "memory," AI agents hallucinate, making the capture of this context an urgent priority rather than a "nice-to-have."Security & Ownership: While product memory raises questions about data privacy and intellectual property, Oleg argues it should be treated like any other process—with clear protocols and security standards.Future of Monetization: As we move beyond seat-based SaaS models, the industry is exploring new ways to monetize data and outcomes, though the exact business models for product memory are still emerging.Resources Mentioned: Beyond PLM Blog: https://beyondplm.comUpcoming Book: From CAD Files to Product Memory by Oleg Shilovitsky (available soon via beyondplm.com).If you found deep dive into the future of manufacturing valuable, please like, subscribe, and share it with a colleague or network peer who is tackling these same digital engineering challenges.  Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

  8. Aug 11 ·  Video

    #148: The Question Every Digital Thread Has to Answer

    What if you could answer a complex engineering change request in minutes instead of days? In this episode of Stay Sharp: In Digital Engineering, hosts Juliann Grant and Jonathan Scott welcome back Chris Finlay, former Vice President of Engineering Innovation at SAIC and current Digital Systems Engineering Director at Raytheon, to explore the tangible, practical benefits of the digital thread. We move past the buzzwords to discuss how to break down engineering silos, improve traceability, and implement a digital strategy that actually delivers value. Key Takeaways The Power of Traceability: Discover how digital threads allow you to query designs in real-time, moving from manual, document-based matrices to instantaneous verification.Breaking the Silos: Learn how a digital thread integrates disparate engineering domains—from systems architecture to mechanical CAD and software—allowing teams to collaborate without needing to master every single tool.The Role of Configuration Management: Understand why CM is the backbone of a successful digital thread, especially when moving from document-based artifacts to an "Authoritative Source of Truth."Start with the End in Mind: Get actionable advice on how to begin your implementation journey by focusing on your specific business goals rather than trying to trace every single data point at once.Episode Highlights Traceability on Steroids: Chris shares a real-world example from a Navy program where a complex engineering trace was completed in minutes, not days, saving hours of manual labor.The "Digital Cable" Concept: We discuss how the digital thread functions like a multi-strand cable, connecting various engineering disciplines and providing a single, consistent version of the truth.Impact Analysis: How a well-crafted digital thread enables you to perform impact analysis in minutes, revealing exactly which components are affected by a change—revealing complexity that was always there, but previously invisible.Overcoming Implementation Barriers: Advice for organizations of all sizes on how to start, when to automate, and why you should focus on "ad-libbing" and refining your processes rather than simply digitizing old workflows.Connect with Us Guest: Chris Finlay, Digital Systems Engineering Director at RaytheonPodcast: Stay Sharp in Digital EngineeringJoin the Conversation: Have questions for Chris or thoughts on this episode? Leave us a comment or contact us at podcast@razorleaf.com  If you enjoyed this deep dive into digital engineering, please rate, review, and subscribe on Spotify or Apple Podcasts. Share this episode with a colleague who is looking to streamline their engineering workflows!  Music is considered “royalty-free” and discovered on Story Blocks. Technical Podcast Support by Jon Keur at Wayfare Recording Co. © 2026 Razorleaf Corp. All Rights Reserved.

Ratings & Reviews

5
out of 5
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About

Welcome to 'Stay Sharp in Digital Engineering,' the ultimate podcast for all things digital in the manufacturing industry by Razorleaf. Join us as we take a deep dive into the multifaceted world of digital transformation, exploring topics such as the digital thread, digital twins, IDEs, model-based strategies and delving into the frontiers of cutting-edge technologies like PLM, MES, Integration, and more. Our expert hosts, Jonathan Scott, Jen Ferello, Juliann Grant, and Eric Doubell, will be your guides, providing valuable insights, captivating interviews, and the latest industry updates to ensure you remain at the forefront of the ever-evolving digital landscape. Whether you're a technology enthusiast, a business leader, or simply curious about the digital realm in manufacturing, this podcast is your essential resource for staying sharp and well-informed.