Enhancing Creativity In Engineering Design

Traditional Design vs Generative Design – A Shift in Engineering Thinking In the world of mechanical and aerospace engineering, design methods are evolving rapidly. The image above clearly illustrates the contrast between Traditional Design and Generative Design using an example of aircraft seat mounting brackets. 🔹 Traditional Design This approach relies on human intuition, experience, and established standards. Designers use basic geometric shapes and overengineer components to ensure safety, often leading to excess material usage and heavier parts. In the image, the traditional bracket weighs 1,672 grams, made with solid material and a blocky design to ensure strength. However, it lacks material efficiency and may contribute to increased fuel consumption in aircraft. 🔹 Generative Design This is an advanced, AI-driven design process. Engineers input goals (like weight reduction, strength requirements, material type, and load conditions), and the software generates multiple optimized design solutions. The result is often an organic, lattice-like structure that removes unnecessary material. In the image, the generatively designed bracket weighs only 766 grams — a 55% weight reduction — while still meeting performance criteria. 💡 Key Differences: Design Process: Human-driven vs AI-assisted Material Usage: Excessive vs optimized Shape: Simple, blocky vs complex, organic Efficiency: Heavier and stronger than needed vs lightweight and just as strong Generative design is not just a trend—it's a strategic shift toward sustainable, high-performance engineering. It helps industries like aerospace, automotive, and manufacturing to save weight, reduce cost, and innovate faster. This transformation is a perfect example of how technology is redefining the boundaries of what's possible in design and engineering. --- #TraditionalDesign #GenerativeDesign #MechanicalEngineering #CAD #DesignInnovation #AerospaceEngineering #LightweightDesign #TopologyOptimization #FutureOfEngineering #AutodeskFusion360 #EngineeringTransformation #ProductDesign #AIInEngineering

Before Elon Musk became a bit weird and obsessed with celebrating orange men and disparaging childless cat lady superstars, he did one thing really well. And from that one thing, he generated wealth that enabled him to keep disrupting industries. He mastered the art of first principles thinking. By stripping down complex problems to their most fundamental elements, he was able to challenge conventional wisdom and pioneer innovative solutions. This approach allowed him to revolutionise industries that others thought were untouchable. For example, the aerospace industry. Instead of accepting the astronomical costs of traditional rocket launches, he questioned every assumption underlying those expenses. SpaceX developed reusable rockets, drastically reducing the cost of space travel and opening new frontiers for exploration. Similarly, with Tesla, he reinvented what an electric car could be by focusing on performance, design, and sustainability. By re-evaluating the basics, he turned around the whole car industry. So, how do we approach this ourselves? Start by questioning every assumption. Break down the problems you face into their most basic components. Don’t settle for “that’s just how it’s done.” Instead, ask yourself why things are the way they are and how they could be different. Consider alternative methods, challenge existing processes, and be willing to think differently from the crowd. It’s about stripping away preconceived notions and looking at the core of the issue with fresh eyes. By adopting first principles thinking, we can uncover innovative solutions and drive meaningful change in our own fields. It’s not reserved for tech giants or industry leaders; it’s a tool anyone can use to make a real impact. How do you challenge the “that’s not how it’s done” thinking in your organisations? How do you approach this in a way that doesn’t alienate? #elonmusk #futuresthinking #criticalthinking Enjoy this? ♻️ Repost it to your network and follow me Holly Joint I write about a tech-driven future, strategy, leadership, culture and women at work. All views are my own.

Most people think “innovation” only means inventing a new product. That’s a narrow view. Joe Tidd and John Bessant offer a much more powerful lens: the 4Ps of Innovation Space — a framework to spot, classify, and intentionally design innovation across your organisation. ☑ Product Innovation ↳ Changes in what the organisation offers. ↳ iPhone, Tesla’s EVs, and Telemedicine in hospitals. ☑ Process Innovation ↳ Changes in how things are made or delivered. ↳ Lean production at Toyota, Amazon's warehouse automation, and online banking. ☑ Position Innovation ↳ Changes in how products are perceived or positioned. ↳ Lucozade is pivoting to an energy drink and baking soda as a deodoriser. ☑ Paradigm Innovation ↳ Changes in the underlying business model or mental model. ↳ Netflix shifting to streaming, Airbnb’s platform model, and microfinance disrupting traditional banking. These 4 types of innovation unlock new possibilities. Here’s why this matters: ↳Most orgs focus only on products and miss other high-impact levers. ↳Operational or positioning changes can be cheaper, faster, and equally valuable. ↳Paradigm shifts are hard — but that’s where market leaders are made. You don’t need to reinvent the wheel. You need to innovate from multiple angles. Start with this question: Which of the 4Ps are we currently underutilising? P.S. If you like content like this, please follow me.

Sometimes, finding a compelling problem instantly inspires possibilities. Other times, crickets. Rather than waiting around for lightning to strike, we recommend that teams take a more proactive approach, and deliberately provoke their own imaginations. One of the most effective, powerful, and fun tools we have created for such self-provocation missions is what we call “Analogous Exploration.” Building upon the extensive research demonstrating the power of unexpected new combinations, we encourage folks to seek radically unexpected sources of inspiration to provoke their thinking. This means not only leaving the room, and not only leaving the building, but also leaving the industry and the conventional definition of “competitor set” behind. Analogous Exploration is not benchmarking. One early application of this radical tool was with a struggling Semiconductor Company whose sales organization had been refined over time to cater predominantly to its largest customers (who ordered hundreds of millions of units annually). The company’s senior leaders felt they needed to “reinvent the customer experience for smaller customers,” and asked for our help. (Story too long for LinkedIn tldr: they instituted a radical new information-sharing agreement with their largest distribution partner, which they believe is one of the largest supply chain innovations in their industry in the last 50 years.) The COO of the company jokingly confided later that they had been watching the competition closely… but the competition didn’t know how to solve their problems either! By deliberately seeking out unexpected sources of inspiration, the organization was able to jump-start revolutionary innovations that serve the smaller businesses every bit as well as they already did the large customers. Getting out of the box like this will not feel efficient. But it is effective. We have since seen Australian financial services organizations glean insights for how to establish trust with new customers from a barber shops & tattoo parlor (those are fascinating stories), Israeli tech companies learn from farmers’ markets, New Zealand fisheries take notes from prominent tea purveyors and bespoke coffee shops, and Japanese conglomerates attracting top-tier millennial talent based on insights from a rock climbing studio and a belly dancing instructor. Despite their differences, one critical commonality among each of these environments is that the teams positioned to solve the newly-defined problem lacked the requisite inputs to trigger fresh ideas. Imagination is fueled by fresh input, and yet all too often, teams are stuck in a conference room, post-it pads in hand, banging their heads against an all-too-ironically spotless whiteboard. Analogous Exploration is a tool to help folks get out of their context on purpose, with intention, to come back with the inspiration they need to fuel fresh thinking.

I’ve been mentoring engineering leaders recently, and one theme keeps coming up: Engineering is evolving—and so must we. When I worked on Google’s index 2 decades ago, it was just a few billion pages. Scaling to trillions and beyond required a mindset shift. We physically visited datacenters, mapped rack affinity & topologies, hardcoded these for performance—because no off-the-shelf solution existed. Fast forward to today: engineers can spin up a datacenters worth of compute with a config change—or better yet, it happens dynamically. That kind of shift isn’t just about tools. It’s about thinking differently. Now, AI is demanding another leap. You can’t say “I’m just backend developer” or “I only do mobile” or "I only work on models". You are now supervisors. System thinkers. Outcome owners. You are not just writing code—you are orchestrating intelligence. And that requires a new kind of engineering leadership. One that breaks silos, rethinks roles, and embraces the unknown.

🎥 𝗜𝘁 𝗹𝗼𝗼𝗸𝘀 𝗹𝗶𝗸𝗲 𝘀𝗰𝗶𝗲𝗻𝗰𝗲 𝗳𝗶𝗰𝘁𝗶𝗼𝗻, 𝗯𝘂𝘁 𝗶𝘁’𝘀 𝘃𝗲𝗿𝘆 𝗿𝗲𝗮𝗹 𝗲𝗻𝗴𝗶𝗻𝗲𝗲𝗿𝗶𝗻𝗴. 🚀 What you’re seeing isn’t a concept from a futuristic film. It’s a real-world challenge in Directed Energy Deposition (DED). When pushing for high deposition rates in thin-walled structures, buckling becomes a serious issue. And the real problem? It often occurs after the print is finished. Even the smartest process control system can’t prevent what it can’t predict. 💡 The key insight: real-time control isn’t always enough. You need to design for what happens after the process, not just during it. In this study, Procada AB printed a thin-walled demonstrator to compare two strategies for increasing stiffness: 📐 A biaxially corrugated geometry on one side, lightweight and efficient. 🧱 A simple wall thickening on the other, traditional, but heavier. The result revealed more than just mechanical differences. It showed a clear shift in mindset. Build-to-print is not enough in additive manufacturing. What we really need is build-to-spec thinking. Because designs made for sheet metal don’t automatically translate to additive. And in many cases, they shouldn’t. They deserve a redesign that fully leverages what AM can offer. ✈️ If you’re working in aerospace, defense or high-performance engineering, here’s the real question: Are you truly designing for additive manufacturing, or just printing legacy ideas with new tools? #AdditiveManufacturing #DED #DesignForAM #Aerospace #Buckling #StructuralStiffness #BuildToSpec #EngineeringExcellence #AdvancedManufacturing #FutureOfManufacturing

Rethinking Requirements in Hardware Engineering Requirements management isn’t just about checklists—it’s the difference between effective collaboration and costly missteps. Here are once-unconventional approaches to requirements now embraced by top teams 1. From “Requirements” to “Design Criteria” Early systems engineers were part engineer, part lawyer. Someone had to create “techno-legal documents” to manage external contracts. These evolved into requirements. Many cultural issues stem from using requirements incorrectly–as a weapon rather than tool for collaboration. Not all requirements need to be treated as commandments. Reframing lower-level requirements as design criteria reduces resistance among engineers, empowering them to see requirements as flexible guidelines open to questioning and adjustment. This is what you want to inspire. 2. Culture of Ownership and Accountability Drives Agility A strong requirements culture is built when engineers “own” their work. Engineers must take responsibility for the requirements they design against, creating a culture of ownership, responsibility, and systems-mindedness. Assigning a clear, single-point owner for each requirement, even across domains, encourages each engineer to think critically about their area’s requirements, establishing ownership and trust in the process. Encouraging information flow between teams helps engineers see how their work impacts others, leads to reduced and stronger system integration. Requirements should be viewed as evolving assets, not static documents. You want engineers to push back on requirements and eliminate unnecessary systems rather than add more requirements, complexity, or systems. 3. Requirements as Conversations, Not Just Checklists Requirements aren’t just specs or checklists—they’re starting points for cross-functional discussions. Every problem is a systems problem, and to solve complex challenges, engineers must be systems thinkers first and domain experts second. In traditional settings, requirements stay isolated in documents. But when teams understand why requirements exist, where they come from, and who owns them—and engage in continuous dialogue—they blur the lines between domains and foster a systems-oriented mindset. This collaborative environment accelerates problem-solving, enabling engineers to align quickly and tackle challenges together. Instead of siloed requirements for each subsystem, drawing dotted lines and encouraging information flow between teams helps engineers understand how their work affects others. This cross-functional awareness leads to fewer misalignments and stronger system integration. When you see engineers make sacrifices in their own area to benefit the overall system, you know you are on the right track. There you have it. The full guide goes into specifics on how to start implementing these ideas in tools.

The drive behind my work in the last 12 years has been that embracing the complexity sciences is something that can help software architecture break free of the theoretical pit it finds itself in. As I described at GOTO, residuality represents a break with the traditional views of complexity in software engineering, drawing a clear distinction between the ordered world of software and the disordered business environments the software must execute in. Residuality centres around leveraging the difference between these two worlds to get something done. One of the issues with the previous uses of complexity in software is the shallow embrace of some aspects of complexity theory to support the agile industrial complex. The central idea there is that complexity is simply a fact, and we should just give up trying to solve it. The failure of structural methods is interpreted as a complete inability to create any kind of conceptual base. The only way to deal with complexity is empirical - to run experiments and test our way forward cautiously. This is a fatal mistake that leaves us chasing our tails. This seems at first blush to support the idea of iteration - a complexity theory backed support of the central methods behind agile. (Leaving aside for the moment the fact that agile methods of managing the SDLC are completely orthogonal to architecture). However this naive empiricism neglects the fact that our experiments are always tinged by our conceptual understanding. If we experiment without a conceptual shift then those experiments are bounded by the already failing conceptual understanding of the environment we are working in. We will be stuck in “normal science” designing experiments that most often reinforce our conceptual biases - which have already failed or we wouldn’t be reaching to complexity theory. This approach is welcomed as it is a quasi-scientific embrace of what we already want to believe about iteration. Complexity should not be considered insurmountable. Every major step forward in our thinking has shifted our view of the complex by presenting new conceptual framing. It is this shift in conceptual framing that moves us forward, not experiments that are safe-to-fail because they’re already safely embedded in current, comfortable understandings. The gap between empirical evidence gathered and results is quickly filled with mysticism and ritual. Trebuchets were once used by trial and error and the reasons why they worked were a mystery. With a conceptual shift we got Newton’s laws and guided missles. As we move forward, we need to seek conceptual novelty, not simply running experiments based on current concepts. Unfortunately this is very difficult, and most will default back to toothless experiment, with countless wasted lines of code.

Before Uber, waiting for taxis was "normal." Before AirPods, untangling earphone wires was "just life."  Before smartphones, carrying multiple devices was "the way it is." Here’s why innovation happens at places where people don’t see a problem: After leading more than a hundred design thinking workshops at Google and Ford Motor Company, I've noticed a pattern - Breakthrough innovations often come from questioning what everyone else considers 'normal.' The key isn't finding new problems—it's seeing existing situations with fresh eyes. Here's a design thinking secret I use: - Step back from solutions. Focus on understanding the problem first. A study by the Harvard Business Review found that 70% of innovation initiatives fail due to lack of clarity on the problem being solved. - Look for invisible problems. Many customers may have frustrations they don’t voice, yet these issues can significantly impact their experience. Taking the time to understand these hidden pain points can lead to innovative solutions that truly resonate with users. - Challenge the existing norms. Henry Ford famously said, if he had asked people what they wanted, they would have said "faster horses." This suggests how true innovation often lies beyond conventional thinking. He highlighted the importance of rethinking conventional wisdom. Innovations often come from questioning the status quo, not just from seeking customer feedback. I believe that with this strategy, one can lead to finding breakthrough solutions that people appreciate later like in the case of Uber, Airpods and smartphones. What's something you do daily that's actually a problem in disguise? Let's uncover these hidden opportunities together! #DesignThinking #Innovation #UserExperience