Updated: Nov 7, 2019
5 things you should know about Generative designing.
What is Generative designing ?
Engineers and designers are limited in time, resources, and energy that can be spent on a given
design problem to fully explore both the design and manufacturing options that may be available.Due to these constraints, they resort to heuristic, evolutionary, incremental improvements to previous design solutions created with proven, or in-use fabrication methods. As a result, components are often over-designed to meet performance criteria with
minimal change to the status quo making innovation and differentiation difficult.
Generative design is a new, disruptive technology poised to upend the current
state of design and engineering. No longer is the designer or engineer limited
by their imagination, previous design history, or their past experience.
Generative design is a design exploration tool that simultaneously generates multiple solutions based on real-world design goals, product performance requirements, and manufacturing constraints.
Generative design then delivers hundreds of design alternatives for consideration and trade-off studies in less time than a human can develop and evaluate 1 or 2 alternatives. The value of generative design is its ability to expose the design team to a greater number potential manufacturing- aware solutions to a specific set of design constraints, saving time and offering
alternatives they wouldn’t have otherwise imagined or considered.
IMPROVE PRODUCT PERFORMANCE
Light weighting or material optimization can improve a product’s performance profile and can reduce product costs by reducing the amount of materials used in the design. Light weighting initiatives are pervasive in the automotive and aerospace industries where even incremental reductions in mass can result in dramatic savings in fuel costs.
How Generative design works ?
Artificial intelligence (AI) is the simulation of human intelligence processes by machines, especially computer systems. These processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self-correction.
Cloud computing is the delivery of computing services—including servers, storage, databases, networking, software, analytics, and intelligence—over the Internet (“the cloud”) to offer faster innovation, flexible resources, and economies of scale. You typically pay only for cloud services you use, helping lower your operating costs, run your infrastructure more efficiently and scale as your business needs change.
Difference between Generative designing and topology optimization.
Topology optimization takes a 3D design space and whittles away material within it to achieve the most efficient design. The method doesn’t care about aesthetics, traditional approaches, or any other of the design constraints that you would normally use in the design phase. Instead, it produces a single optimal shape of a part or system constrained only by the available design space.
But topology optimization is not a new concept. For years, engineers have used this method to find an optimal distribution of material in a 3D model to meet their goals, such as to reduce mass, avoid a resonance mode, or minimize thermal stress or deformation.
Generative design is a way to autonomously generate optimal designs from a set of system design requirements. With generative design, engineers can interactively specify the functional requirements and goals of their design, including preferred materials and manufacturing processes—and the generative engine will automatically produce a manufacture-ready design. The end result is being able to interact with the technology to create superior designs and innovative products more quickly.
Topology optimization works on subtractive manufacturing and generative design works on subtractive and additive manufacturing both.
Topology optimization removes the material where the stress concentration is minimum and generative designing works with stress concentration and other factors also,such as constraints,load,obstacle,and manufacturing process.
According to me topology optimization is the subset of generative designing.
Knowledge you require before making a generative design.
FORCES OR LOAD
MANUFACTURING PROCESS AVAILABLE
FACTOR OF SAFETY REQUIRED
WHICH SOFTWARE YOU SHOULD BE USING ?
Today there are many opportunities for generative design that have a quantifiable return on investment, enabling a viable path to production for low volume, short run, and custom components using additive manufacturing, CNC methods, or both. Additionally, generative design can be used as a starting point for companies that want the benefits of generative design without the cost of additive manufacturing.
Additive manufacturing time and costs continue their downward trajectory; as they fall below certain thresholds, new business models will become viable. At some point in the not too distant future, there will be an inflection point. Additive manufacturing costs for high volume production will not only become justifiable, it will also be necessary to remain competitive. As with any inflection point, the business environment will quickly evolve to manufacturers who disrupt the market and those whose business is disrupted. It is incumbent upon today’s forward thinking
companies to get out in front of this trend. By beginning to explore what is possible today and what the future may hold when the inflection point occurs, companies are ready, prepared, and have in place proven processes, methods, and practices to be successful with generative design and additive manufacturing.