Failure Analysis in Engineering Systems

I’ve been waiting a long time to show an example of what gets me up in the morning… Because in this world, failure isn’t the end — it’s the start of real insight! 💥 During hot-fire testing, an additively manufactured GRCop-42 combustion chamber failed — and with it, offered a powerful #FailureAnalysis case study on the critical role of process rigor in additive manufacturing, especially when builds are interrupted. We conducted a full failure analysis: reviewing test day data, manufacturing records, post-processing steps, and metallurgical characteristics of both the failed chamber and adjacent components. 🔬 Key findings: •⁠ ⁠Failure occurred at a build interruption location, witness line, with metallographic analysis revealing higher porosity than expected. •⁠ ⁠This localized porosity reduced tensile strength and elongation, triggering the failure. •⁠ ⁠Interestingly, test bars with emulated build interruptions showed no performance degradation — confirming that proper restart procedures preserve part integrity. Additive manufacturing offers incredible promise, but as this work shows, it also demands discipline. Especially when the stakes are rocket engines. 🔗 Full article: https://lnkd.in/ekg-t4MH Ben Williams, Colton Katsarelis, Will Tilson, and Paul Gradl, thank you for the collaboration in making this fun analysis and article! #AdditiveManufacturing #RocketEngines #FailureAnalysis #MaterialsScience #GRCop42

A design that worked for years suddenly starts failing. Everyone looks at the drawing. The drawing hasn't changed. So what happened? Here are a few things I've seen change quietly in production... while engineering assumed nothing was different: 🔷 𝐓𝐡𝐞 𝐬𝐮𝐩𝐩𝐥𝐢𝐞𝐫 𝐜𝐡𝐚𝐧𝐠𝐞𝐝. Same material spec on paper. Different mill. Different melt practice. Different grain structure. 𝘛𝘩𝘦 𝘤𝘦𝘳𝘵 𝘴𝘢𝘺𝘴 𝘪𝘵 𝘱𝘢𝘴𝘴𝘦𝘴. 𝘛𝘩𝘦 𝘧𝘢𝘵𝘪𝘨𝘶𝘦 𝘭𝘪𝘧𝘦 𝘴𝘢𝘺𝘴 𝘰𝘵𝘩𝘦𝘳𝘸𝘪𝘴𝘦. 🔷 𝐓𝐀𝐊𝐓 𝐭𝐢𝐦𝐞 𝐠𝐨𝐭 𝐩𝐮𝐬𝐡𝐞𝐝. Production needed more throughput. So weld travel speed went up. Braze dwell time went down. Cure cycles got shortened. 𝘕𝘰𝘣𝘰𝘥𝘺 𝘶𝘱𝘥𝘢𝘵𝘦𝘥 𝘵𝘩𝘦 𝘦𝘯𝘨𝘪𝘯𝘦𝘦𝘳𝘪𝘯𝘨 𝘭𝘪𝘮𝘪𝘵. 𝘉𝘦𝘤𝘢𝘶𝘴𝘦 𝘯𝘰𝘣𝘰𝘥𝘺 𝘢𝘴𝘬𝘦𝘥. 🔷 𝐅𝐢𝐱𝐭𝐮𝐫𝐢𝐧𝐠 𝐰𝐚𝐬 "𝐚𝐝𝐣𝐮𝐬𝐭𝐞𝐝." A clamp wore out. A locator pin was shimmed. Alignment shifted by 0.020". 𝘛𝘩𝘢𝘵 𝘪𝘴 𝘯𝘰𝘵𝘩𝘪𝘯𝘨 𝘰𝘯 𝘢 𝘱𝘳𝘪𝘯𝘵 𝘵𝘰𝘭𝘦𝘳𝘢𝘯𝘤𝘦. 𝘛𝘩𝘢𝘵 𝘪𝘴 𝘦𝘷𝘦𝘳𝘺𝘵𝘩𝘪𝘯𝘨 𝘰𝘯 𝘢 𝘧𝘢𝘵𝘪𝘨𝘶𝘦-𝘤𝘳𝘪𝘵𝘪𝘤𝘢𝘭 𝘫𝘰𝘪𝘯𝘵. 🔷 𝐀 𝐬𝐞𝐜𝐨𝐧𝐝 𝐬𝐡𝐢𝐟𝐭 𝐰𝐚𝐬 𝐚𝐝𝐝𝐞𝐝. Different operators. Different technique. Same WPS, different execution. 𝘗𝘳𝘰𝘤𝘦𝘴𝘴 𝘷𝘢𝘳𝘪𝘢𝘵𝘪𝘰𝘯 𝘥𝘰𝘶𝘣𝘭𝘦𝘥 𝘰𝘷𝘦𝘳𝘯𝘪𝘨𝘩𝘵. 𝘍𝘢𝘪𝘭𝘶𝘳𝘦 𝘳𝘢𝘵𝘦 𝘧𝘰𝘭𝘭𝘰𝘸𝘦𝘥. 🔷 "𝐖𝐞'𝐯𝐞 𝐚𝐥𝐰𝐚𝐲𝐬 𝐝𝐨𝐧𝐞 𝐢𝐭 𝐭𝐡𝐢𝐬 𝐰𝐚𝐲" 𝐛𝐞𝐜𝐚𝐦𝐞 𝐭𝐡𝐞 𝐚𝐧𝐬𝐰𝐞𝐫. The original process engineer left. The tribal knowledge left with them. 𝘞𝘩𝘢𝘵 𝘳𝘦𝘮𝘢𝘪𝘯𝘴 𝘪𝘴 𝘩𝘢𝘣𝘪𝘵, 𝘯𝘰𝘵 𝘦𝘯𝘨𝘪𝘯𝘦𝘦𝘳𝘪𝘯𝘨. If your failure rate changed but your drawing didn't, the answer is almost never in the CAD file. It is on the shop floor. We investigate the full chain: design, process, and production variation to find where the physics actually shifted. If parts that "used to work" are now failing, DM me. I'll tell you what to look for first. #Engineering #FailureAnalysis #Manufacturing #Reliability #Fatigue #QualityControl #MechanicalEngineering

Enhancing Reliability in EV Power Electronics: #FMEA for Traction Inverter Design ⚡🚗 In electric vehicles (EVs), the traction inverter plays a crucial role in converting DC #battery power into AC power for the electric motor. A failure in this system can lead to power loss, reduced efficiency, or even vehicle breakdown. To ensure reliability and performance, we use Failure Modes and Effects Analysis (FMEA) to identify and mitigate potential failures in the EV inverter system. 📌 FMEA considers: ✔ Severity (S) – Impact of failure (1 = low, 10 = critical). ✔ Occurrence (O) – Likelihood of failure happening (1 = rare, 10 = frequent). ✔ Detection (D) – How easily the failure can be detected (1 = easily detectable, 10 = undetectable). ✔ Risk Priority Number (RPN) = S × O × D – A score to prioritize risks. 🔴 Key Failure Modes in EV Traction Inverter 🔹 IGBT/MOSFET Short Circuit → Overcurrent, overheating, potential powertrain shutdown. ⚠️ S = 10 | O = 4 | D = 3 | RPN = 120 👉 Mitigation: Advanced short-circuit protection, thermal monitoring, robust gate driver design. 🔹 IGBT/MOSFET Open Circuit → No power transfer to the motor, loss of acceleration. ⚠️ S = 9 | O = 3 | D = 3 | RPN = 81 👉 Mitigation: Redundant power paths, fault detection circuits. 🔹 Gate Driver Malfunction → Incorrect switching, increased losses, reduced efficiency. ⚠️ S = 9 | O = 5 | D = 4 | RPN = 180 👉 Mitigation: Shielding against EMI, optimized PCB layout, reliable driver components. 🔹 DC Link Capacitor Degradation → Higher voltage ripple, increased heat, reduced motor performance. ⚠️ S = 8 | O = 5 | D = 4 | RPN = 160 👉 Mitigation: High-quality capacitors, active cooling, periodic diagnostics. 🔹 DC Link Capacitor Short Circuit → Inverter shutdown, potential vehicle breakdown. ⚠️ S = 10 | O = 3 | D = 3 | RPN = 90 👉 Mitigation: Overvoltage protection, pre-charge circuit, high-reliability capacitors. 🔹 Control Board Software Failure → Incorrect switching signals, unstable power delivery, or sudden inverter failure. ⚠️ S = 9 | O = 4 | D = 5 | RPN = 180 👉 Mitigation: Watchdog timers, redundant safety logic, secure software updates. 🔹 Temperature Sensor Failure → No thermal protection, leading to possible overheating and failure. ⚠️ S = 9 | O = 4 | D = 3 | RPN = 108 👉 Mitigation: Redundant sensors, real-time thermal diagnostics. 🔹 Cooling System Failure (Liquid Cooling/Pump Malfunction) → Excessive heat buildup, inverter derating, or failure. ⚠️ S = 10 | O = 5 | D = 4 | RPN = 200 👉 Mitigation: Preventive maintenance, thermal shutdown features, and redundant cooling circuits. Why FMEA is Critical for EV Inverters ✅ Ensures safety and reliability in electric drivetrains. ✅ Improves efficiency and thermal management for long-term operation. ✅ Reduces risk of breakdowns and increases vehicle lifespan. As #EV adoption grows, traction #inverter must be designed for high performance and durability under real-world conditions.

When a Small Design Detail Becomes a Major Integrity Threat: Lessons from a WHB Failure A failure analysis of a Waste Heat Boiler (WHB) tube highlights how subtle design geometry can significantly impact long-term integrity. In this case, severe localized tube wastage was observed approximately 100–150 mm from the tubesheet, near the ferrule end. Interestingly as per the published data: * No abnormal water chemistry was detected * No signs of microstructural degradation or decarburization * Hardness remained within normal limits *Oxide identified was magnetite (Fe3O4), typical for steam oxidation CFD modeling revealed that the sudden enlargement at the ferrule end created flow recirculation and a localized spike in heat flux. This high local heat flux generated a steep temperature gradient across the tube wall, accelerating steam-side oxidation. The excessively formed magnetite was then eroded by high velocity water/steam flow, leading to progressive wall thinning and eventual failure. Ferrule end geometry (chamfering, flaring, or abrupt diameter transition) can significantly influence local heat transfer behavior. Increased local heat flux can dramatically accelerate oxidation kinetics even when materials and operating chemistry are within design limits. Integrity is not ONLY about material selection, but about detailed thermal–hydraulic design. This case reinforces an important engineering principle: Minor geometric details can drive major damage mechanisms. Paper is after access source on science direct, check and download from here: https://lnkd.in/dtw6MMxj Authors: Suwarno Suwarno Abdul Jabar I'jazurrohman Fajar Dwi Yudanto Vivien S. Djanali

Most manufacturers treat symptoms, not causes. They fix the machine. Retrain the operator. Blame the supplier. Then wonder why problems keep coming back. Root cause analysis isn't about finding someone to blame. It's about finding the system failure that allowed the problem. Here's your toolkit for different scenarios: WHEN EQUIPMENT FAILS UNEXPECTEDLY: → 5 Whys Analysis - Simple questioning technique → Fishbone Diagram - Visual mapping of contributing factors   → Fault Tree Analysis - Logical breakdown of failure sequences → Timeline Analysis - Chronological review of events WHEN QUALITY ISSUES ARISE: → Statistical Analysis - Data-driven investigation → Process Mapping - Visual workflow analysis → Design of Experiments - Systematic testing of variables → Mistake Proofing Review - Error prevention assessment → Supplier Analysis - Investigation of incoming materials WHEN SAFETY INCIDENTS OCCUR: → Incident Reconstruction - Detailed event recreation → Policy Review - Analysis of existing protocols → Human Factors Analysis - Training and procedural review → Witness Interviews - Structured personnel discussions → Equipment Inspection - Thorough machinery examination → Corrective Action Planning - Systematic prevention measures The method matters less than the mindset. Are you asking "Who made the mistake?" Or "What system allowed this mistake to happen?" One question leads to blame. The other leads to solutions. Your choice determines whether problems disappear permanently. Or just hide until next time. Which root cause analysis method does your team use most often?

Weld Defect and Fracture Failure: Recent project I worked on with William Weimer (Metallurgist). We were asked to determine why multiple brackets were experiencing similar fracture failures and how to prevent this failure from occurring. Via low power microscopy and SEM (image below), Will discovered the weld in the area of fracture was not fully penetrating. He also determined the loading was a one-time occurrence (either static or impulsive) and not due to fatigue. My computational analysis showed the fractured leg was the highest loaded leg (image below). In the simulation which did not include the weld defect, I discovered inelastic failure was due to buckling, creating local instability in the typically fractured leg (image below). This emphasized the fracture failure was not due to typical plastic deformation, but due to weld defect discovered by Will. We both determine via our respective disciplines that shear stress (both transverse and torsional) was significant (fea image below). We discovered multiple witness marks indicating the type and direction and loading (multiple images below). The computational simulations aided us to determine the likely load vector magnitude. In the end, we were able to use our materials and mechanical analysis to determine why the fractures occurred, the type of loading that caused the failure, and provided multi redesigns to mitigate future failures (1/3 shown here). This was a great project showing the power of the combination of materials and mechanical engineering! U.S. Coast Guard Elizabeth City State University #materialsscience #materialsengineering #mechanicalengineering #materials #mechanical #engineering #microscopy #machinedesign #fea #engineeringanalysis

🔍Quality Engineer Part 5: FMEA & Risk Analysis "What's the worst that could happen?" That question right there... is the beginning of FMEA. Failure Modes and Effects Analysis is how engineers, QA, and manufacturing teams predict failures before they happen, assess the risk, and put controls in place. But trust me, it’s not just paperwork. It’s critical thinking, cross-functional collaboration, and risk-based decision-making. Let me give you two examples 👇 ☕ Relatable Life Example You’re making coffee before work. You skip checking the water tank. Boom — no water. Next thing? You’re late, stuck in traffic, angry, and caffeine-deprived. 😤 Your FMEA might look like: Failure Mode: No water in coffee machine Effect: Delayed morning, bad mood, low productivity Severity: 7 Occurrence: 5 (you’ve done it before) Detection: 3 (no alarm on your machine) RPN = 7 × 5 × 3 = 105 Control? ✔ Add checking water to your nightly routine. FMEA is basically engineering-level overthinking with results. 😄 Now lets understand in 🧪 Technical (Pharma) terms: We were introducing a new automated blister packaging line. Before going live, we ran a PFMEA with Quality, Engineering, and Production. We identified failure modes like: Tablet misfeed Foil misalignment Seal integrity failure For each one, we scored: Severity (S) – How bad is the impact? (Patient safety = 9/10) Occurrence (O) – How often could this happen? (Misfeeds = 6/10) Detection (D) – Can we catch it before release? (Cameras = 7/10) 📊 Risk Priority Number (RPN) = S × O × D = 378 That’s high. So we: Added redundant camera systems Improved PM schedule Added auto-reject logic for seal deviation Result: Lower RPN, better control, smoother validation. 💡 Why It Matters FMEA teaches you to: Think ahead Collaborate cross-functionally Prioritize risk Drive process improvement It’s one of those tools that once you learn it, you start seeing it everywhere. 🎓 Want to Learn more on PFMEA from Experts? If you're interested in mastering PFMEA, here is one of the best industry-recognized programs: ✅ ASQ - World Headquarters - PFMEA Training Program 🔗 https://lnkd.in/ehpP3_cR This course is practical, detailed, and align with what the industry expects from process engineers and QA professionals. 💡 Takeaway FMEA isn’t just a form — it’s a way of thinking. If you can understand how and where things go wrong, you’ll always be one step ahead — whether you're on the shop floor or in a boardroom. #FMEA #RiskAnalysis #QualityEngineering #CAPA #Validation #MedicalDevices #PharmaIndustry #ProcessImprovement #LinkedInLearning

Problems don’t appear out of nowhere. They grow from something deeper. Surface symptoms shout. Root causes whisper. Most teams chase the noise. The best ones listen for the signal. Because every failure has a story. And every story has a source. Ask why. Then ask it again. Peel back the layers until the real answer shows itself. That’s the power of 5 Whys. Simple. Direct. Uncomfortable in all the right ways. Map it out when things get messy. Let the bones of the problem show. People. Methods. Materials. Machines. Environment. A fishbone diagram doesn’t fix the issue. It reveals the battlefield. When the stakes rise and the systems get tangled, trace the logic. Build the fault tree. See how tiny branches lead to big failures. How one weak link can take everything down. Look for patterns too. Not all causes weigh the same. A Pareto chart shows what’s loudest. A scatter plot shows what’s linked. Both point you toward leverage. Group the chaos when ideas flood the room. Affinity diagrams turn noise into themes. Suddenly the fog clears. Suddenly the next step feels obvious. Root cause analysis isn’t a toolset. It’s a mindset. A refusal to treat symptoms as solutions. A commitment to fix what actually breaks. The right tool depends on the moment. A quick meeting needs 5 Whys. A broad search needs a fishbone. A system failure needs a fault tree. But the goal never changes. Find the truth. Name it. Solve it so it stays solved. Great organizations don’t just correct problems. They prevent them. And that discipline is what builds systems people can trust.

How to Perform Root Cause Analysis (RCA) for Industrial Maintenance Root Cause Analysis (RCA) is a structured method used to identify the underlying reasons for equipment failures, recurring breakdowns, or performance issues (bad actors). The goal is to find the true cause (not just symptoms) and implement long-term solutions.    Step-by-Step RCA Process for Maintenance Teams  1. Define the Problem - Clearly describe the issue (e.g., "Pump bearing fails every 3 months"). - Gather data: - Failure history (MTBF - Mean Time Between Failures) - Maintenance logs - Operational conditions (load, temperature, vibration)  2. Collect Evidence - Inspect the failed component (photos, measurements). - Check maintenance records (was lubrication missed?). - Interview operators (any unusual sounds/behaviors before failure?). - Use condition monitoring data (vibration analysis, thermography, oil analysis).  3. Identify Possible Causes (5 Whys or Fishbone Diagram) - 5 Whys Method (Ask "Why?" repeatedly until reaching the root cause): - Why did the bearing fail? → Overheating - Why was it overheating? → Insufficient lubrication - Why was lubrication insufficient? → Automatic greaser was clogged - Why was it clogged? → No scheduled inspection - Why no inspection? → Missing from PM checklist - → Root Cause: Preventive maintenance program lacks bearing lubrication checks. - Fishbone (Ishikawa) Diagram (Categories: Man, Machine, Method, Material, Environment, Measurement): - Helps visualize all possible contributing factors.  4. Determine the Root Cause - Verify which cause(s) directly led to the failure. - Rule out unlikely factors (e.g., "Operator error" vs. "Defective seal design").  5. Develop & Implement Corrective Actions - Short-term fix (replace the bearing). - Long-term solution (update PM schedule, install better lubrication system).  6. Monitor Effectiveness - Track KPIs (downtime reduction, extended component life). - Adjust if the problem persists.    Example: RCA on a Hydraulic Pump Failure 1. Problem: Hydraulic pump leaks oil weekly. 2. Evidence: Seal wear, oil contamination found. 3. 5 Whys: - Why leak? → Seal damaged - Why damaged? → Contaminated oil - Why is it contaminated? → Filter not replaced - Why not replace? → No scheduled filter change - Why no schedule? → Missing from a maintenance plan 4. Root Cause: Lack of scheduled filter replacement. 5. Solution: Update PM checklist, train technicians.    Key Takeaways - RCA prevents recurring failures, saving time & money. - Use structured methods (5 Whys, Fishbone, FMEA). 

FMEA: Empowering Risk Mitigation and Process Excellence In a rapidly evolving industrial landscape, where quality, reliability, and efficiency are paramount, Failure Mode and Effects Analysis (FMEA) stands as a cornerstone methodology in ensuring robust systems and processes. What is FMEA? FMEA is a structured, systematic approach for identifying potential failure modes in a process, product, or system and analyzing their impact. By evaluating the severity, occurrence, and detectability of these failures, teams can prioritize actions to mitigate risks before they escalate into costly problems or safety hazards. The process involves the following key steps: 1. Defining the Scope: Establishing the boundaries of the analysis – whether it’s for a product design, manufacturing process, or service delivery. 2. Identifying Failure Modes: Brainstorming and listing all possible ways a component or process could fail to perform its intended function. 3. Assessing Risk: Using a Risk Priority Number (RPN) to quantify and rank risks based on severity, likelihood of occurrence, and ease of detection. 4. Implementing Mitigations: Developing and applying corrective actions to address high-priority risks, reducing their impact and frequency. 5. Monitoring & Updating: Continuously refining the analysis to reflect changes in design, process improvements, or new insights. Why Does FMEA Matter? Proactive Problem Solving: FMEA allows organizations to address issues during the design or planning phase, reducing downstream costs and delays. Enhanced Safety and Compliance: By anticipating and mitigating risks, FMEA ensures adherence to industry standards and protects stakeholders. Improved Customer Satisfaction: Delivering reliable products and services builds trust and strengthens brand reputation. Cross-Functional Collaboration: FMEA fosters teamwork across departments, leveraging diverse expertise to uncover hidden risks. Applications Across Industries Manufacturing: Identifying process bottlenecks and ensuring quality in production lines. Automotive: Enhancing the reliability and safety of components, from engines to electronics. Energy: Ensuring the durability of systems in power plants and renewable energy projects. FMEA in the Era of Digital Transformation As industries embrace Industry 4.0 technologies, FMEA is evolving alongside. Tools like AI, IoT, and big data analytics are enhancing FMEA's predictive power, enabling real-time monitoring of systems and rapid identification of potential failures. For example, predictive maintenance systems can integrate FMEA findings to preempt equipment failures, reducing downtime and extending asset life. Similarly, AI-driven algorithms can analyze historical data to refine risk assessments, making FMEA more dynamic and precise. #FMEA #RiskManagement #ContinuousImprovement #QualityAssurance #OperationalExcellence #LeanManufacturing #Engineering