2. Artificial Intelligence in Design Engineering MEC 1

3. Contents Definitions. Key Engineering Design Processes. Key Technologies. Weak and Strong AI. Applying AI to Engineering Designs. Benefits of AI. Merits and Challenges. Ethical Issues. 2MEC

4. Engineering Design Application of engineering principles to design and develop products, systems, and processes that meet specific requirements. Encompasses various disciplines - mechanical, electrical, software, industrial engineering etc. Use of tools like computer-aided design, software, simulation, and prototyping. 3MEC

5. ABET* Definition Process of devising a system, component, or process to meet desired needs. A decision-making process (often iterative). Application of basic sciences, mathematics, and engineering sciences to convert resources optimally to meet a stated objective. Fundamental elements of design process include establishment of objectives and criteria, synthesis, analysis, construction, testing, and evaluation. MEC4 * Accreditation Board for Engineering and Technology, October 2017

6. Engineering Design Identifying opportunities. Developing requirements. Performing analysis and synthesis. Generating multiple solutions. Evaluating solutions against requirements, considering risks. Making trade-offs to obtain high-quality solution. MEC5 Approaches to Addressing ABET Engineering Design Requirements Jeffrey W. Fergus

7. Design Engineering Iterative, systematic process for solving problems. Involves creativity, experience, and accumulated disciplinary knowledge. Dynamic process, not a rigid method. Result of engineering design process not always a product, can be a process or a computer program. 6MEC

8. Design Engineering Design engineers employed in a wide range of industries : - Aerospace. - Automotive. - Consumer electronics. - Biomedical engineering. - Robotics/IT. - Manufacturing. - Construction. - Electronics/Telecommunications. 7MEC

9. Key Engineering Design Phases Ideation and conceptual phase – identify the engineering problem and develop a concept. Creation – design (fabricate) a prototype of the concept (usually a CAD model). Redefine and enhance the design. Validate the design – test with CAE. Build – develop optimal production processes for the design. 8MEC

10. Artificial Intelligence Enables computers and machines to simulate human learning, comprehension, problem solving, decision making, creativity and autonomy. Machine learning - creating models by training an algorithm to make predictions or decisions based on data. 9MEC

11. Artificial Intelligence Deep Learning – use of multilayered neural networks (deep neural networks) to closely simulate complex decision-making power of human brain. Generative AI (gen AI) - deep learning models to create complex original content— long-form text, high-quality images, realistic video or audio etc. in response to a user’s prompt or request. 10MEC

12. Artificial Intelligence 11MEC

13. How can AI help? Gather and analyze reference information. Generate design ideas and alternatives. Optimize parameters and complex combinations. Create more efficient designs. Design more quickly than humans. Create layouts and 3D models. Program design tools. Quality reviews of designs. 12MEC

14. How can AI help? A 3D rendering service developed by AI 13MEC

15. Key Technologies Machine Learning – Algorithms analyze data and learn patterns to predict outcomes or optimize designs. – Techniques include supervised, unsupervised, and reinforcement learning. Computer Vision – Enables AI systems to interpret and process visual design data. – Useful in quality control, defect detection, and reverse engineering. 14MEC

16. Key Technologies Natural Language Processing (NLP) – Assists in processing and analyzing engineering documents, standards, and user feedback. Neural Networks and Deep Learning – Mimic human cognition to solve complex design problems. – Effective in recognizing patterns in multidimensional datasets. 15MEC

17. Traditional vs AI Algorithms 16MEC

18. Weak and Strong AI Weak AI : or narrow AI, - AI systems designed to perform a specific task or a set of tasks. eg : Voice Assistant Apps – Alexa, Co-pilot. Strong AI: or artificial general intelligence (AGI) or general AI, with ability to understand, learn and apply knowledge across a wide range of tasks at levels equal to or more than human intelligence. Strong AI 17MEC

19. Virtual Assistants A large language model (LLM) that interacts in a human-like manner. Can perform a range of tasks or services based on user input such as commands or questions. Typically utilizes online chat (chatbot, eg :Chat GPT) capabilities to simulate human conversation, also called a visual dialog model. Some virtual assistants can interpret human speech and respond via synthesized voice. Assist engineers in finding information and making informed decisions. 18MEC

20. Chatbot Answering Questions 19MEC

21. Chat GPT Design of a Biomimetic Fan Regulator MEC20

22. Digital Twins Combines human expertise and machine intelligence to permit evolution of work in new and unexplored ways. To design virtual replicas of products in a virtual world, simulate processes and improve operations over time. Allows design engineers to test products before expending resources to produce them. Anticipates problems, prevents mistakes before occurence. Detects anomalies, automates repair processes. MEC21

23. AI in Transportation Design Intelligent Transportation Systems (ITS) leverage AI to enhance traffic management, safety, and efficiency. Data collected and analyzed through sensors and cameras to identify congestion, areas of speeding, predict traffic patterns, and optimize traffic flow. A proactive approach to traffic management. 22MEC

24. Intelligent Transportation Systems Can adjust traffic lights and reroute vehicles to minimize congestion. Reduce travel time. Minimize the likelihood of accidents. Create a safer travel environment. Provide alerts for emergency response. Provide traffic insights for design purposes. 23MEC

25. Automated Highway Systems AI technologies to control vehicle movements based on real-time information on surroundings. Connected vehicles to make driving more reliable and efficient. V2V (Vehicle to Vehicle). V2I (Vehicle to Infrastructure). V2P (Vehicle to Pedestrian). V2G (Vehicle to Grid). V2D (Vehicle to Device like smartphone). 24MEC

26. Smart Highways Interconnections between several items..... Dynamic real time responses to changing traffic and weather. Instant updates to road conditions ahead. 25MEC

27. Road Design Software to design roads. Civil 3D, OpenRoads, and other civil software will soon have AI toolkits released. Softree RoadEng Optimal has an AI toolbar ton help make design decisions and make adjustments to a previous design to achieve project objectives. Software can quickly optimize routes between points, keep grades within maximum and minimum ranges, minimize cut and fill quantities, avoid no-go zones, and adjust for crossings. 26MEC

28. Traffic Simulation Trafficware by Cubic and PTV Vissim with AI. Use of AI to test traffic flow scenarios and alternative arrangements for infrastructure projects. Enables engineers to visualize traffic issues and make informed decisions to optimize traffic management. 27MEC

29. Structural Design Software with AI capabilities for structural design. Can optimize a structural design based on desired objectives such as minimizing cost, weight, or footprint. Can create or modify a design based on project limitations. Can identify problems/failures in the design and modify the design. Programs with feedback or reinforced learning. User can identify areas where the program did not make a desirable design decision. 28MEC

30. Design Optimization Topology, Shape and Sizing Optimization possible. 29MEC

31. Automotive Design Design and optimize the shape of vehicles. Helps to maximize aerodynamic efficiency and reduce drag forces. Used in a variety of aerospace applications to reduce weight while still meeting structural strength and deflection requirements. 30MEC

32. Design of Structures Design from ground up based on initial directions such as building purpose, number of occupants, location, space available, height restrictions, budget, etc. Identify horizontal and vertical irregularities and evaluate modification options to remove them. STAAD Pro utilizes AI for complex load analysis, including running various seismic and wind load combinations and analyzing the results for each structural member. 31MEC

33. CFD Modelling Computational fluid dynamics (CFD) modeling helps civil, process, mechanical, and biomedical engineers simulate designs involving moving liquids and gases. AI allows engineers to simulate more iterations in shorter times and view the results very quickly. Software such as Solid Works, Ansys Fluent, Xflow etc. 32MEC

34. Machine and Engine Design AI has the potential to handle the complexity and vast amount of information involved in a full engine simulation. Mechanical Software packages such as Engine Builder, Engine Analyzer Pro, Fusion 360. Simulations to anticipate weaknesses and make design modifications to make engines more robust. 33MEC

35. Electrical Design AI models can simulate complex electrical systems, predict performance, and provide insights and tools that guide the design of more efficient and robust systems. Software for electrical design with AI such as Altair HyperWorks, Ansys Electronics Desktop, MATLAB Simscape Electrical, Siemens NX with AI capabilities 34MEC

36. Circuit Design AI to automatically generate circuit schematics and layout designs, and how to use simulation tools to test and evaluate circuit performance. Tools such as Cadence, Snapmagic Copilot, Synopsis.ai copilot with AI capabilities. Use of Chat GPT to choose a circuit diagram. 35MEC

37. Predictive Maintenance Proactive approach. Avoids surprising failures, extends the lifespan of equipment, minimizes downtime, optimizes performance, and reduces resources. AI driven software can continuously analyze electrical installations to predict potential malfunctions before they occur. 36MEC

38. Smart Grid Management AI to oversee and optimize electricity distribution. Remote terminal units installed on various electrical lines in the distribution system to collect real-time data from the electrical grid. AI software with predictive analytics and machine learning to achieve forecast demand, adapt to supply changes, prevent outages and resource reduction. 37MEC

39. Smart Grid Management Smart Grid Arrangement for a Solar Panel 38MEC

40. Artificial Intelligence in Engineering Design Generative Design : - To explore design options based on constraints and objectives. -Use techniques like topology optimization to create lightweight, high-performance designs. -Use in aerospace, automotive, and architecture. 39MEC

41. Artificial Intelligence in Engineering Design Predictive Analytics and Optimization: - Machine learning models to predict design performance under various conditions. - Parameter optimization for better efficiency, durability, and cost-effectiveness. 40MEC

42. Artificial Intelligence in Engineering Design Simulation and Modeling: - Predicting real-world behavior of designs. -Reducing the need for physical prototypes. -Savings in time and costs. Automation of Repetitive Tasks: - Automating CAD modeling, component selection and other routine tasks. - Frees up engineers to focus on creative and strategic problem-solving. 41MEC

43. Artificial Intelligence in Engineering Design Design Customization: - analyzing user preferences, generating personalized designs. - Useful in consumer products and medical applications. 42MEC

44. Artificial Intelligence in Engineering Design Failure Analysis and Risk Assessment: - To identify potential design flaws and predict failures. - - A nalyzing historical data and real-time inputs to enhance safety and reliability. 43MEC

45. Benefits of Artificial Intelligence Improved Efficiency: Reduces time and costs in the design cycle. Innovation: Encourages out-of-the-box solutions by exploring unconventional design spaces. Accuracy: Enhances precision in simulations, predictions, and optimizations. Sustainability: Optimizes designs for reduced material usage and energy consumption. 44MEC

46. Benefits of Artificial Intelligence Automation of repetitive tasks - automate routine, repetitive and often tedious tasks. More and faster insight from data - generate and evaluate various design possibilities automatically. Enhanced decision-making – accurate and reliable. Fewer human errors – flagging before they occur. 24x7 availability – no machine fatigue!. Reduced physical risks – automation of dangerous works!. 45MEC

47. Challenges Data Dependence – Requires large, high-quality datasets for training AI models. Interpretability – Difficult to understand and trust AI-generated solutions in critical applications. Integration – Requires compatibility with existing engineering workflows and tools. Ethical and Social Concerns – Balancing automation with the human role in decision- making and creativity. Job Security?..... unskilled? 46MEC

48. AI Driven Designs Not as a replacement for engineers. As a tool that augments their capabilities. More efficient workflows. Frees engineers to focus on more creative and strategic aspects of their work. New opportunities for innovation and problem-solving. Integrating human and artificial intelligence to achieve better outcomes – Collaborative Intelligence. 47MEC

49. Design by Morphing Optimal design for objects considering their aerodynamic, hydrodynamic, thermal, and/or structural performance. Drawbacks of currently used methods of optimal design based on Trial and Error approaches or Gradient-based methods overcome. ​ Dependence on designer heuristics, complexity and computational costs reduced. MEC48

50. Design by Morphing MEC49

51. Ethical Issues MEC50

52. Deep Fakes Synthesized images, videos, or audio edited or generated using artificial intelligence tools.using artificial intelligence May depict real or non-existent people, satellite images or buildings. Can scramble our understanding of truth. Raises a set of challenging policy, technology, and legal issues. AI algorithms called encoders used in face- replacement and face-swapping technology. Decoder retrieves and swaps images of faces, which enables one face to be superimposed onto a completely different body. MEC51

53. Deep Fakes Generative Adversial Network : neural network technology uses generator and discriminator algorithms to develop all deepfake content. Convolutional neural networks - analyze patterns in visual data, used for facial recognition and movement tracking. Autoencoders - a neural network technology identifies the relevant attributes of a target such as facial expressions and body movements, and imposes these attributes onto the source video. MEC52

54. Deep Fakes Natural language processing - used to create deepfake audio. NLP algorithms analyze attributes of a target's speech and generate original text using the attributes.NLP High-performance computing - a type of computing that provides the significant necessary computing power deepfakes require. Video editing software - not always AI-based, but frequently integrates AI technologies to refine outputs and make adjustments that improve realism. MEC53

55. Deep Fake Architecture MEC54 https://www.researchgate.net/figure/General- DeepFake-Architecture_fig1_382579812

56. Deep Fake MEC55 https://cacm.acm.org/research/beyond-deep-fakes/

57. MEC56

58. Deep Fakes MEC57 Left : Original Photograph Right : Image generated in Midjourney with word prompts alone (www.linkedin.com).www.linkedin.com Midjourney is an AI based text to image converter.

59. AI Hallucinations Large language model perceives patterns or objects that are nonexistent or imperceptible to human observers. Creates nonsensical or altogether inaccurate outputs. AI algorithms produce outputs that are not based on training data. Incorrectly decoded by the transformer / do not follow any identifiable pattern. MEC58

60. AI Hallucinations AI model trained on dataset comprising biased or unrepresentative data. Adversarial attack by adding small amounts of specially-crafted noise to an image. Leads to unnecessary medical interventions. Contributes to the spread of misinformation. MEC59

61. Solving AI Hallucinations Establish chosen AI system’s responsibilities and limitations. Adversarial training to counter adversarial attack. AI models trained on diverse, balanced and well-structured data. Data templates to ensure output consistency and reduce the likelihood of faulty results. Define boundaries for AI models using filtering tools. MEC60

62. Solving AI Hallucinations Test and refine the system continually. Human intervention to validate and review AI outputs. Stop them before they happen! MEC61

63. Conclusion Artificial Intelligence (AI) is transforming engineering design by automating processes, enhancing creativity, and improving decision- making. AI tools can analyze vast datasets, optimize complex systems, and simulate real- world scenarios, enabling engineers to develop innovative solutions more efficiently. 62MEC

64. References Artificial Intelligence in Engineering Design - SunCam online continuing education course material. https://www.ibm.com/think/topics/artificial- intelligence https://www.ibm.com/think/topics/artificial- intelligence https://www.arcweb.com/industry-best- practices/understanding-role-ai-generative- engineering-design https://www.arcweb.com/industry-best- practices/understanding-role-ai-generative- engineering-design https://indiaai.gov.in/article/the-art-and-algorithms- of-deepfake-ai-a-comprehensive-study https://indiaai.gov.in/article/the-art-and-algorithms- of-deepfake-ai-a-comprehensive-study https://funginstitute.berkeley.edu/capstone- project/design-by-morphing/ https://funginstitute.berkeley.edu/capstone- project/design-by-morphing/ Chat GPT and other Internet Sources. 63MEC

65. AI Ready ? 64MEC