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GURUMOORTHY RAMACHANDRA reposted thisSheet Metal Forming Facts (Industry-Used) Blank diameter in deep drawing is calculated from volume constancy, not guesswork → material volume before = material volume after forming. Draw Ratio (DR = Db / Dp) decides whether a cup can be drawn in one stage or needs redraw operations. For low-carbon steel, Limiting Draw Ratio (LDR) typically lies between 2.0 – 2.2 under normal conditions. Higher draw ratio increases thinning at the cup wall, especially near punch radius. Punch radius < 4× sheet thickness significantly increases risk of tearing and cracking. Die clearance is always kept slightly higher than sheet thickness to control material flow and reduce friction. Blank holder force (BHF) is critical: Too low → wrinkling Too high → tearing Material flow stress, not ultimate tensile strength, governs deep drawing behavior. Springback increases with: higher yield strength lower thickness larger bend radius In production dies, most failures are due to poor process parameters, not wrong CAD geometry. ♻️Repost and follow Sanjeet Kumar for more Want to learn more: No warry Join with the link below https://lnkd.in/gH8eQPft #AutomotiveDesign #MechanicalEngineering #AutomotiveEngineering #ProductDesign #CAD #CATIA #SiemensNX #SolidWorks #SheetMetalDesign #DesignEngineer #Fresher #OpenToWork #ManufacturingEngineering #DesignForManufacturing #FormingCalculations #AutomotiveDesign #MetalForming #ProductDevelopment #DFM #FEA #ToolDesign #EngineeringExcellence #LinkedInLearning #MechanicalDesign #TechnicalContent #DishuExplains
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GURUMOORTHY RAMACHANDRA reposted thisGURUMOORTHY RAMACHANDRA reposted thisWhen products scale globally, PLM data types decide what survives. What holds up in one plant, region, or market often breaks the moment scale is introduced. More variants. More suppliers. More regulations. More change. The only thing that keeps this from collapsing is how cleanly PLM data is separated and governed. Here’s how the core PLM data types make global scale possible, without slowing teams down. - Master Data Creates a single, shared identity for parts, materials, and attributes across regions. Without this, every system invents its own version of the truth. - BOM Data Allows the same product to exist in multiple forms - engineering, manufacturing, service - without forcing one view to fit all use cases. - Document Data Preserves design intent, certifications, and regulatory proof across geographies. Critical when compliance requirements differ by market. - Change Data Ensures design updates propagate consistently across plants, suppliers, and ERP systems. This is what prevents local fixes from becoming global failures. - Configuration Data Enables regional variants, options, and rules without cloning products. Essential for mass customization at scale. - Manufacturing Data Adapts products to plant-specific realities - routings, tooling, and work instructions - while staying aligned with the core design. - Quality Data Closes the loop between production, suppliers, and engineering. Global scale only works when issues are visible everywhere, not hidden locally. - Integration Data Keeps PLM, ERP, MES, and suppliers in sync. At scale, integration isn’t plumbing - it’s survival. Global PLM success isn’t about more features. It’s about respecting data boundaries. The companies that scale are the ones that know exactly what data belongs where, and enforce it relentlessly. Which PLM data type is breaking first as your products scale - BOMs, changes, or configurations? For a deep dive into PLM, MES, or CAD and to elevate your understanding of PLM, connect with us at PLMCOACH and Follow Anup Karumanchi for more such information. #plmcoach #plm #teamcenter #siemens #3dexperience #3ds #dassaultsystemes #training #windchill #ptc #training #plmtraining #architecture #mis #delmia #apriso #mes
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GURUMOORTHY RAMACHANDRA reposted thisGURUMOORTHY RAMACHANDRA reposted thisFive pillars. One connected system. Zero guesswork. That’s the real promise of digital manufacturing. When these pillars work together, data flows. When they don’t, teams fill gaps with assumptions. Here’s how the system actually holds up: 1. CAD / PDM – Engineering intent Defines product geometry, drawings, revisions, and design history. This is where accuracy starts. 2. PLM – Product control Manages change, configurations, approvals, and traceability. This is how products evolve without chaos. 3. ERP – Business planning Turns designs into materials, costs, schedules, and orders. This is where engineering meets money and time. 4. MES – Shopfloor execution Executes plans, captures real-time production data, and enforces quality. This is where plans face reality. 5. Supply Chain – External alignment Coordinates suppliers, logistics, inventory, and demand. This is where risk and resilience are managed. Digital manufacturing isn’t about adding tools. It’s about connecting decisions end to end. Break one pillar, and guesswork creeps in everywhere. For a deep dive into PLM, MES, or CAD and to elevate your understanding of PLM, connect with us at PLMCOACH and Follow Anup Karumanchi for more such information. #plmcoach #plm #teamcenter #siemens #3dexperience #3ds #dassaultsystemes #training #windchill #ptc #training #plmtraining #architecture #mis #delmia #apriso #mes
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GURUMOORTHY RAMACHANDRA reposted thisGURUMOORTHY RAMACHANDRA reposted thisAgentic AI: The Big Picture 🧠🤖 Most conversations about AI stop at models. But the real shift is happening above them. This diagram captures something important: ➡️ AI isn’t just generating content anymore. ➡️ It’s planning, deciding, coordinating, and acting. We’ve moved through clear layers: AI & ML → turning data into predictions Deep Learning → handling complex patterns GenAI → generating text, images, code AI Agents → executing tasks autonomously Agentic AI → orchestrating entire workflows with memory, goals, and governance What makes Agentic AI different isn’t intelligence alone, it’s agency: Long-term goals Tool orchestration Memory & context Self-reflection and recovery Safety, guardrails, and governance This is where AI stops being a feature and starts becoming a digital teammate. The big question isn’t “Can we build this?” It’s “How do we deploy it responsibly, securely, and at scale?” If you’re building products, systems, or teams around AI, this stack matters. What layer are you currently working in? 👇 Curious to hear where others are focusing.
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GURUMOORTHY RAMACHANDRA reposted thisGURUMOORTHY RAMACHANDRA reposted thisEveryone is talking about Agentic AI, but very few actually understand how it works under the hood. 🤖 Traditional AI answers questions; Agentic AI solves problems. Here is the simple 4-step breakdown of how these autonomous systems move from a raw query to a smart, executed outcome. 𝟏. 𝐈𝐧𝐩𝐮𝐭 𝐒𝐨𝐮𝐫𝐜𝐞𝐬 (The Ears) Agentic AI doesn't just rely on a static prompt. It pulls real-time data from: Knowledge bases & Documentation Live APIs & Web data System logs & User history 𝟐. 𝐀𝐈 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐢𝐧𝐠 (The Brain) This is where the magic happens. Instead of just "predicting the next word," the agent: Analyzes the intent and context. Retrieves relevant long-term and short-term memory. Plans a multi-step strategy to reach the goal. Selects the right tools for the job. 𝟑. 𝐀𝐜𝐭𝐢𝐨𝐧 𝐋𝐚𝐲𝐞𝐫 (The Hands) This is the differentiator. Unlike a standard chatbot, an agent performs real actions: Executing code or terminal commands. Collaborating with other specialized agents. Self-Correction: If an error occurs, it re-evaluates and tries a different path. Scheduling future tasks autonomously. 𝟒. 𝐎𝐮𝐭𝐩𝐮𝐭 (The Result) The final result isn't just a text response—it’s a completed task. It’s a context-aware, verified solution that feels truly autonomous.
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GURUMOORTHY RAMACHANDRA reposted thisGURUMOORTHY RAMACHANDRA reposted this📊 𝗛𝗼𝘄 𝘁𝗼 𝗖𝗹𝗲𝗮𝗿𝗹𝘆 𝗘𝘅𝗽𝗹𝗮𝗶𝗻 𝗔𝗜 — 𝗙𝗿𝗼𝗺 𝗔𝗻𝗮𝗹𝘆𝘁𝗶𝗰𝘀 𝘁𝗼 𝗜𝗻𝘁𝗲𝗹𝗹𝗶𝗴𝗲𝗻𝘁 𝗦𝘆𝘀𝘁𝗲𝗺𝘀⚡ One of the biggest challenges I see in learning AI and Data Science is confusion, not complexity. People hear terms like Predictive, Generative, or Agent-based systems and assume they’re all the same. They’re not — and understanding the difference is what separates tool users from solution builders. 𝐀𝐈 & 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐜𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞 :-https://lnkd.in/gg2ScfwJ 𝗧𝗵𝗶𝘀 𝗳𝗿𝗮𝗺𝗲𝘄𝗼𝗿𝗸 𝗯𝗿𝗲𝗮𝗸𝘀 𝗔𝗜 𝗶𝗻𝘁𝗼 𝘁𝗵𝗿𝗲𝗲 𝗽𝗿𝗮𝗰𝘁𝗶𝗰𝗮𝗹 𝗹𝗮𝘆𝗲𝗿𝘀 👇 𝟏️⃣ 𝐓𝐫𝐚𝐝𝐢𝐭𝐢𝐨𝐧𝐚𝐥 𝐀𝐈 — 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧 𝐒𝐮𝐩𝐩𝐨𝐫𝐭 🔸Forecast demand and risk using historical data 🔸Classify and route data at scale 🔸Detect anomalies like fraud or system failures 👉 Best for structured problems and rule-driven environments. 𝟐️⃣ 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐢𝐯𝐞 𝐀𝐈 — 𝐂𝐫𝐞𝐚𝐭𝐢𝐨𝐧 & 𝐀𝐜𝐜𝐞𝐥𝐞𝐫𝐚𝐭𝐢𝐨𝐧 🔸Generate content, code, and designs from prompts 🔸Automate workflows like reporting, data cleaning, and documentation 🔸Use business knowledge through retrieval-based systems 👉 Best for productivity, ideation, and faster execution. 𝟑️⃣ 𝐀𝐠𝐞𝐧𝐭𝐢𝐜 𝐀𝐈 — 𝐄𝐱𝐞𝐜𝐮𝐭𝐢𝐨𝐧 & 𝐎𝐫𝐜𝐡𝐞𝐬𝐭𝐫𝐚𝐭𝐢𝐨𝐧 🔸Build agents that plan, decide, and act 🔸Coordinate multiple agents across tools and systems 🔸Integrate intelligence directly into products and platforms 👉 Best for end-to-end automation and real-world deployment. 𝗪𝗵𝘆 𝘁𝗵𝗶𝘀 𝗺𝗮𝘁𝘁𝗲𝗿𝘀 𝗳𝗼𝗿 𝗹𝗲𝗮𝗿𝗻𝗲𝗿𝘀 𝗮𝗻𝗱 𝗽𝗿𝗼𝗳𝗲𝘀𝘀𝗶𝗼𝗻𝗮𝗹𝘀 🔸You stop learning tools in isolation 🔸You understnd where each capability fits in a business problem 🔸You design systems, not just models or dashboards In our AI & Data Science program, we teach this exact progression — from analytical foundations → intelligent generation → autonomous systems — with real use cases, not theory-heavy slides.
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GURUMOORTHY RAMACHANDRA reposted thisGURUMOORTHY RAMACHANDRA reposted this🚦 𝗛𝗼𝘄 𝘁𝗼 𝗦𝘁𝗮𝗿𝘁 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁𝘀 – 𝗔 𝗦𝘁𝗿𝘂𝗰𝘁𝘂𝗿𝗲𝗱 𝗣𝗮𝘁𝗵 𝗧𝗵𝗮𝘁 𝗔𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗪𝗼𝗿𝗸𝘀 AI Agents are not a single tool or framework. They are systems that combine reasoning, memory, tools, and autonomy to solve real-world problems. The biggest mistake I see professionals make is jumping straight to frameworks without understanding the layers beneath. 𝐀𝐈 & 𝐃𝐚𝐭𝐚 𝐒𝐜𝐢𝐞𝐧𝐜𝐞 𝐂𝐞𝐫𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐂𝐨𝐮𝐫𝐬𝐞 :-https://lnkd.in/gg2ScfwJ A practical way to approach AI Agents is to think in levels of capability, not hype. 🔹𝗟𝗲𝘃𝗲𝗹 𝟭: 𝗚𝗲𝗻𝗔𝗜 & 𝗥𝗔𝗚 𝗕𝗮𝘀𝗶𝗰𝘀 (𝗙𝗼𝘂𝗻𝗱𝗮𝘁𝗶𝗼𝗻) Before agents, you must understand how modern language models work. • What Generative AI is and where it is used • How large language models generate responses • Prompt design and output control • Retrieval-Augmented Generation (RAG) fundamentals • Vector databases and embeddings • Calling models through APIs and tool integrations This level builds control and reliability. Without it, agents behave unpredictably. 🔹𝗟𝗲𝘃𝗲𝗹 𝟮: 𝗔𝗜 𝗔𝗴𝗲𝗻𝘁 𝗘𝘀𝘀𝗲𝗻𝘁���𝗮𝗹𝘀 (𝗧𝗵𝗶𝗻𝗸𝗶𝗻𝗴 & 𝗔𝗰𝘁𝗶𝗻𝗴) Here, models move from answering questions to taking actions. • Agent workflows and task decomposition • Memory for recalling past interactions • Multi-step reasoning and planning • Single-agent and multi-agent coordination • Evaluation, safety, and guardrails • Using RAG inside agent workflows This level teaches agents how to think, decide, and adapt. 🔹𝗟𝗲𝘃𝗲𝗹 𝟯: 𝗔𝗱𝘃𝗮𝗻𝗰𝗲𝗱 𝗔𝗴𝗲𝗻𝘁 𝗦𝗸𝗶𝗹𝗹𝘀 (𝗣𝗿𝗼𝗱𝘂𝗰𝘁𝗶𝗼𝗻-𝗥𝗲𝗮𝗱𝘆) This is where agents become usable in real environments. • Autonomous loops and self-updating tasks • Custom tools, APIs, and system integrations • Performance optimization (cost, latency, accuracy) • Error handling and observability • Deploying agents for real users This level separates experiments from real systems. 🧠 𝗞𝗲𝘆 𝗜𝗻𝘀𝗶𝗴𝗵𝘁 AI Agents are not about replacing humans. They are about amplifying decision-making, automation, and execution when designed correctly. If you are serious about learning AI Agents: Start with foundations → build reasoning → then add autonomy. Skipping steps creates fragile systems. Structured learning creates reliable ones.
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GURUMOORTHY RAMACHANDRA shared thisModular design helps on customisation and faster solutionsGURUMOORTHY RAMACHANDRA shared thisModMed MV Panel is ready for dispatch with a fully customized design. Optimized busbar and protection coordination ensure safety and reliability. Robust mechanical design built for demanding industrial environments. Customer is very happy with the engineering and quality. Proud to deliver solutions, not just panels — Modutec.
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GURUMOORTHY RAMACHANDRA reposted thisGURUMOORTHY RAMACHANDRA reposted this❓ Looking for an enclosure that adapts to your automation challenges? ✔️ MODUTEC has the answer. When reliability is non-negotiable, MODUTEC Modular Enclosures deliver unmatched performance, protection, and flexibility for industrial automation. 🔧 Why choose MODUTEC? Because your control panels deserve more than a box — they deserve engineering that evolves with your system. 💡 What makes our enclosures stand out? ✔ Adaptable design for any automation layout ✔ Rigid construction built to handle industrial harshness ✔ Enhanced IP protection with PU gasket ✔ 3-point locking system for maximum security ✔ Adjustable mounting plate for quick configuration ✔ Integrated drawing pouch for operational convenience 🌐 Built for Industry. Trusted for Safety. Upgrade your automation with proven, innovative panel solutions from Modutec Ready Panels Pvt. Ltd., Bangalore. 📩 Connect with us: Sales@modutec.net 🔗 Visit: www.modutec.net
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GURUMOORTHY RAMACHANDRA liked thisGURUMOORTHY RAMACHANDRA liked thisAt the CVS Health Innovation Lab, we learned early on that with the pace of AI evolution, what you build today can quickly become obsolete tomorrow. So instead of waiting for perfect conditions, we leaned into what we do best, putting emerging capabilities to work on hard, real business problems. Over the past year, the team embraced AI not as a buzzword, but as a true force multiplier. From exploring bold ideas to code generation and dashboarding to storytelling, we used it to tackle problems that once felt too hard to touch. 🚀 We worked on over 100 innovative ideas and hard problems: a 4x increase year over year and with it, our team's visibility across the organization grew in ways we hadn't anticipated. Which led to… 🤝 10x growth in internal stakeholders. Today, more people come to us than we go to them. Not because we simply solve problems, but because we listen, and make every collaboration feel like a partnership worth coming back to. Which led to… 🏆 One of the best employee engagement scores at CVS: 100% participation, 94% overall engagement, and three other categories at a perfect 100%. Score went up 4th time in a row in 2 years. But the number I'm most proud of is the team! A small but mighty team that transformed itself into a true shared service, partnering with all domains across CVS and proving that when you pair human judgment with emerging technologies, there's no ceiling on what's possible. Proud of what this team has accomplished and even more excited about what comes next. We never stop exploring what's next! #CVSHealth #Innovation #AI #EmployeeEngagement #DigitalTransformation #EnterpriseAI #InnovationLab
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GURUMOORTHY RAMACHANDRA liked thisGURUMOORTHY RAMACHANDRA liked thisYour resume is probably the reason you’re not getting interviews. Not your experience. Not your degree. Not the job market. Here’s what’s really holding you back: ❌ Generic CVs ❌ Buzzwords like “team player” or “go-getter” ❌ Paragraphs nobody has time to read ❌ No links to your actual work Here’s how to fix it 👇 ✅ Tailor your headline and keywords ↳ Match your job title + skills to each role ✅ Hyperlink your portfolio or LinkedIn ↳ Make it one click to see your best work ✅ Prove soft skills with examples ↳ Don’t say you’re “great at teamwork” — show it ✅ Use 2–4 sharp bullet points per job ↳ Use STAR or XYZ methods to show impact ✅ Ditch blocks of text ↳ Recruiters spend 6–8 seconds on your CV. Make every word count. Your resume isn’t your life story. It’s your highlight reel. Make it look like one. Image credit to :careerflow.ai on Instagram ------ DM us to be featured on our next post Your Guide to Landing the Right Job, Faster. Follow How To Find A Job for more content like this.
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