Engineering Design Process Steps

🚗 Imagine this: You launch a new car model after years of effort. Production is smooth, the assembly line is world-class… but six months later, the headlines scream “Massive Recall.” Billions lost. Reputation damaged. All because of a design flaw that was locked in during the product development phase. Takao Sakai once said: 👉 “95% of Toyota’s profits are determined in the product development phase, not production.” And it’s true across industries: In aerospace, material choices made at the design table decide 80% of lifecycle costs. In electronics, overengineering features adds cost but not value. In manufacturing, late design changes cause delays that no production efficiency can recover. ⚡ The real challenge? Most companies pour their energy into fixing problems on the shop floor instead of preventing them during development. 💡 The smarter way: Apply Design for Manufacturability (DFM) & Concurrent Engineering. Run early simulations & prototypes to detect risks. Involve quality, supply chain, and production teams at the concept stage. Use Voice of Customer (VOC) to cut out features no one wants but everyone pays for. The truth is simple: ✅ Every mistake caught in design costs a fraction of fixing it in production. ✅ Every smart decision in development compounds into long-term profit. 🔑 What’s one thing your team does during product development that safeguards future profitability? 👇 Share your experience—it might spark ideas for someone else! #Lean #ProductDevelopment #DesignThinking #Innovation #BusinessExcellence #Quality #TQM

Technical drawings can be powerful storytelling tools, not just construction documents. Once in a while, you can use technical drawings to showcase both your design concept and technical expertise without going too abstract. In the below image, I tested creating ventilation diagrams using gradients in Illustrator, combined with technical details and human scale references. ☀️ The result? A drawing that communicates clearly while maintaining visual interest. Here's the thing: it's all about visual hierarchy. ✔️ Yes, these drawings don't replace construction documents. But they're incredibly useful for: → Portfolio presentations that demonstrate technical competency → Client presentations that need clarity over artistic flair → Concept comprehension during design development → Bridging the gap between pure diagrams and working drawings The sweet spot is when your drawing is precise enough to show you understand the technical side, yet refined enough to tell your design story. What's your go-to tool for technical presentation drawings?

I had a fascinating conversation with Steve Quinlan of NatWest Group recently, and it really highlighted a fundamental issue in how many product teams approach experimentation. Too often, "experimentation" is seen as something that happens after a feature is built. This is the cart-before-the-horse. You've already invested significant time and resources, and now you're hoping to validate if it was worth it. True experimentation should be about validating and developing ideas before they enter serious development and as they go through design. Steve sits with a 'prototyping' function at Natwest created with this purpose in mind. They focus on de-risking development by rigorously testing and iterating on ideas early in the process. This approach not only saves valuable resources but also ensures that the final product truly meets customer needs. Moreover, Steve's team's work disambiguates from the narrow view that experimentation is just about A/B testing. It's about a broader, more strategic approach to product research, discovery and validation. It begs the question: how many product teams are missing out on this critical early-stage validation? How often are we building features based on assumptions rather than solid evidence, even if they are 'tested' before release? Shifting our mindset to prioritize prototyping and early-stage experimentation can revolutionize how we build products and drive innovation. How does your team ensure that experimentation is integrated into the entire product development lifecycle, not just tacked on at the end? #experimentation #cro #productmanagement #growth #digitalexperience #experimentationledgrowth #elg  

Failure Mode and Effects Analysis (FMEA) is a systematic, proactive method for evaluating a process or design to identify where and how it might fail, and to assess the relative impact of those failures. It is one of the most critical "Core Tools" used to prevent problems before they occur, rather than reacting to them after the fact. Types of FMEA There are two primary types used in manufacturing: DFMEA (Design FMEA): Focuses on potential failure modes caused by design deficiencies (e.g., material properties, geometry, tolerances). PFMEA (Process FMEA): Focuses on failures in the manufacturing and assembly process (e.g., human error, machine calibration, environmental factors). The FMEA Calculation: RPN vs. AP In older versions (AIAG 4th Ed.), risks were calculated using the Risk Priority Number (RPN). In the newer AIAG & VDA handbook, there is a shift toward Action Priority (AP). The Three Scoring Factors (1–10 Scale) Severity (S): How serious is the impact on the customer or the next process? Occurrence (O): How frequently is the cause of the failure likely to happen? Detection (D): How likely are your current controls to catch the failure before it reaches the customer? Formula: RPN = S \times O \times D The 7 Steps of FMEA (AIAG & VDA Standard) The modern approach follows a 7-step structure to ensure a thorough analysis: Planning & Preparation: Define the scope (what is being analyzed?). Structure Analysis: Break down the design or process into components or steps. Function Analysis: Describe what each step or component is supposed to do. Failure Analysis: Identify the Failure Mode (what goes wrong), the Effect (consequence), and the Cause (why it happened). Risk Analysis: Assign scores for Severity, Occurrence, and Detection to determine the Action Priority (High, Medium, or Low). Optimization: Develop recommended actions to reduce high risks (prioritizing Severity and Occurrence). Results Documentation: Summarize and communicate the results and actions taken. Example: PFMEA for a Welding Process Process Step: Robotic Spot Welding. Potential Failure Mode: Weak weld/Incomplete fusion. Potential Effect: Structural failure of the vehicle (Severity: 9 or 10). Potential Cause: Electrode tip wear or low current. Current Controls: Visual inspection every 50th part. Recommended Action: Install automated current monitoring sensors to detect drops in real-time. Why FMEA is Vital Safety: Identifies failures that could harm the end-user. Cost Savings: It is much cheaper to change a drawing or a process step now than to handle a product recall later. Knowledge Base: It acts as a "lessons learned" document for future engineering teams.

🌞 How I Designed a 15kW Hybrid Solar PV System (Step by Step) Designing a solar PV system isn’t just about choosing panels and batteries. It requires a structured approach that ensures the system meets real energy needs while staying efficient and reliable. Here’s the process I followed for my recent 15kW Hybrid Solar PV system design: 1️⃣ Energy Audit – I collected data on appliances, their wattages, and usage hours. This helped determine the daily energy requirement and peak load demand. 2️⃣ Site Survey – I assessed the location for roof/ground space, orientation, tilt angle, shading, and cable run distances. This ensures the design is practical and site-specific. 3️⃣ Data Processing in Excel – Using my customized Excel program, I analyzed the data to calculate energy consumption and accurately size the system. 4️⃣ Component Sizing – Based on the results, I sized the PV modules, inverter, battery bank, and charge controller to match the client’s demand. 5️⃣ System Design in AutoCAD – I created the schematic diagram, mapping out PV modules, inverter, batteries, and protection devices for clarity and implementation. 6️⃣ Simulation in PVsyst – Finally, I tested the design with PVsyst to validate system performance, efficiency, and real-world output. 💡 This process ensures the system is not just technically sound but also optimized for long-term performance and cost-effectiveness. ✅ By combining technical analysis, site assessment, and simulation software, I can deliver solar solutions that are reliable, sustainable, and tailored to client needs. 👉 Would you like me to break down one of these steps in detail in my next post? 📩 If you’re interested in a customized solar solution for your home, business, or project, feel free to reach out.

What if we’ve been optimising drones in the wrong direction? For years, the logic was simple: Add weight → lose efficiency. Lose efficiency → lose range. Then EPFL built 𝐑𝐀𝐕𝐄𝐍. It's a 620g fixed-wing drone. And 230g of that weight is legs. Legs that walk, hop over obstacles, and jump into flight without a runway or catapult. The part that forces a reset is:  Jump takeoff is reported to be 𝟏𝟎𝐱 𝐦𝐨𝐫𝐞 𝐞𝐧𝐞𝐫𝐠𝐲 𝐞𝐟𝐟𝐢𝐜𝐢𝐞𝐧𝐭 𝐭𝐡𝐚𝐧 𝐚 𝐬𝐭𝐚𝐭𝐢𝐜 𝐥𝐚𝐮𝐧𝐜𝐡. The legs aren’t extra mass. They’re stored energy, released intelligently. Most UAV design has optimised for airborne purity such as lighter frames, cleaner aerodynamics, longer uninterrupted flight. But real environments aren’t pure. Forests don’t offer launch strips. Urban debris doesn’t provide smooth clearings. Disaster zones don’t cooperate with aerodynamics. RAVEN signals something bigger: It forces us to think optimising only for flight. And start focusing on transition. A drone that can: Land anywhere Reposition by walking instead of hovering Conserve battery while stationary Relaunch without external systems isn’t just an aircraft. It’s an adaptable mobility platform. And that matters. Because the next frontier of autonomy is about environmental versatility. Future operations from search and rescue to infrastructure inspection to defense deployments, will demand systems that operate across surfaces, not just above them. A swarm that can perch, move on ground, conserve power, and relaunch behaves differently from one forced to stay airborne. We’ve treated weight as inefficiency. Maybe some weight is capability. The breakthrough won’t always come from removing mass. Sometimes it comes from giving mass a purpose. #Drones #Robotics #AerospaceEngineering #AutonomousSystems #Innovation #FutureTech

Proactive Risk Assessment Effective risk management is fundamental to operational excellence. Before commencing any task regardless of its scale or complexity a structured risk assessment must be conducted to safeguard people, assets, the environment, and organizational performance. A disciplined approach should address the following key considerations: 1). Hazard Identification – What could go wrong? Systematically identify all potential hazards associated with the task, including: Unsafe acts and unsafe conditions Equipment or system failures Human factors and competency gaps Environmental influences Process deviations or procedural non-compliance Early hazard identification is the foundation of risk prevention. 2). Likelihood Assessment – How likely is it to occur? Evaluate the probability of occurrence by considering: Historical incident data and near-miss trends Effectiveness of existing control measures Task complexity and operational pressures Workforce competence, training, and supervision Site-specific and environmental conditions Understanding likelihood enables informed decision-making and prioritization. 3). Consequence Evaluation – What would be the impact? Assess the severity of potential outcomes across critical dimensions: People: Injury, occupational illness, or fatality Assets: Equipment damage, downtime, financial loss Environment: Pollution, contamination, regulatory breach Quality & Compliance: Defects, rework, contractual or legal non-conformance Reputation: Brand damage and stakeholder confidence Both probability and impact must be evaluated together to determine overall risk exposure. 4). Control Effectiveness – Are safeguards adequate? Confirm that preventive and protective measures are: Properly implemented Clearly communicated Understood by all involved personnel Monitored for effectiveness Controls may include engineering solutions, administrative procedures, permit-to-work systems, isolation protocols, supervision, training, and appropriate PPE. 5). Risk Reduction – Can the risk be minimized further? Where risk remains unacceptable, apply the Hierarchy of Controls in order of effectiveness: Elimination Substitution Engineering Controls Administrative Controls Personal Protective Equipment (last line of defense) Continuous improvement should always be the objective. Risk management is not a reactive exercise conducted after an incident, it is a proactive leadership responsibility embedded in daily operations. #SHEQ #RiskLeadership #OperationalExcellence #SafetyCulture #RiskManagement

Good engineering is wasted if you build the wrong product. The other day, I meet a founder. He says “Oh, you’re a CTO?” He hands me his phone. “Can you look at my app? I'm not sure my engineering team did a good job.“ I say “it’s hard to be sure just by clicking around, but the layout seems fine, the performance is snappy. What’s wrong with it?” “Well, people aren’t using it enough” Ah, the plot thickens. As it happens, the engineering team is doing fine. But they’re contractors. They’re given Figma mocks and do a pixel-perfect implementation. But how do those mocks get created? They’re just following an arbitrary roadmap based on the founder’s intuition. Having strong intuition for what your users want is helpful, but it never happens in a vacuum. Your job as a founder is to talk to your users. A lot. When you all you have is a wireframe, show your users and look for validation that it meets a real need they’d be willing to pay for. When you have a higher-fidelity prototype, do it again. Summarize, and share these summaries with your engineers. Everyone who touches execution should be reading them. Once you’ve launched, mine insights from your monitoring tools. Do new features improve these metrics? If early testers aren’t engaging, ask why. Always assume you’re missing some key insight about user needs and be relentless in squeezing this insight from your users. Until you have product-market fit, the most valuable thing your users have for you isn’t their money, its their honest feedback. Getting this feedback isn’t easy, but it’s the shortest path to iterating on your product effectively. If you’re not doing this, you’re likely wasting precious time and engineering resources. 10 hours of talking to users saves you 100s (1000s?) of hours building the wrong thing.

💡 Stop Guessing: The Right Risk Assessment Drives Your Strategy Choosing the right type of Risk Assessment is not a detail—it's a critical strategic decision. Too often, organizations use a one-size-fits-all approach and end up misallocating resources or missing key threats. The key difference often lies in the data. Qualitative Risk Assessment uses expert judgment and descriptive, non-numeric scales (like High/Medium/Low) to rate severity and likelihood. This helps small teams prioritize quick fixes with a simple heat map. For a data-driven approach, Quantitative Risk Assessment is essential. It uses numerical values (P, %, frequency) to evaluate risk and forecast potential losses or calculate the ROI on controls. A middle ground is the Semi-Quantitative method, which assigns numeric scores (like 1-5 or 1-10) to impact and likelihood, offering more structure than a purely qualitative approach. Risk isn't static. In evolving situations, a Dynamic Risk Assessment is an on-the-spot, real-time evaluation performed when risks shift rapidly or new ones emerge unexpectedly. Furthermore, a Continuous Risk Assessment is a proactive, ongoing process where risks are constantly monitored and adjusted based on new information or threats. Finally, for operational precision, you must choose between: Generic Risk Assessment: A general evaluation covering common hazards across similar tasks or environments. Use this for standardized operations. Site-Specific Risk Assessment: A focused evaluation of risks unique to a particular location, event, or project setup, considering the environment and layout. Choosing based on your environment, data availability, and industry needs is the key to making stronger decisions. #RiskManagement #CyberSecurity #BusinessStrategy #RiskAssessment #DecisionMaking #Security

⚡ Utility-Scale Solar PV Power Plant – EPC & Grid Training Overview ⚡ Designing and executing a utility-scale solar PV plant is not just about installing modules; it’s about engineering the complete power flow from DC generation to grid synchronisation. This visual breaks down the end-to-end EPC & utility perspective of a solar PV power plant, exactly how engineers, DISCOMs, and utilities evaluate projects. 🔹 What this overview covers: 🔸 Solar PV Generation (DC Side): PV modules convert solar irradiation into DC power; performance depends on layout, tilt, temperature, and soiling control. 🔸 String & Combiner Architecture: Proper string sizing, protection, and combiner design ensure safety, reduced mismatch losses, and ease of maintenance. 🔸 Inverter System (DC → AC): Inverters act as the brain of the plant — managing MPPT, grid synchronization, harmonics, and protection compliance. 🔸 AC Collection & Protection: Well-engineered LT panels, earthing, and protection coordination are critical for plant reliability and fault isolation. 🔸 Step-Up Transformer & Evacuation: Voltage is stepped up to evacuation level (11/33/66 kV) to minimize losses during power export. 🔸 Switchyard & Grid Interfacing: Grid compliance systems including relays, CT/PTs, isolators, and breakers ensure utility-approved power injection. 🔸 Transmission / DISCOM Network: Power flows into the utility network following grid codes, evacuation limits, and scheduling norms. 🔸 SCADA, Metering & Monitoring: Real-time monitoring of MW, voltage, frequency, CUF, alarms, and performance ratios ensures bankability and grid trust. 📌 Why this matters for EPC & utilities: ✔ Better design = fewer losses ✔ Compliance = smoother approvals ✔ Monitoring = higher plant availability ✔ Engineering clarity = long-term asset performance Good solar EPC execution is about engineering discipline, grid compatibility, and lifecycle performance, not just MW installation.