Topology Optimisation (TO) in Industrial Design and Hiatus

         Currently, there is a continuous increase of demand on product design and development to reduce costs, energy into manufacturing and using, material to manufacture and disposed, and time to market; in other words, to optimise products. For product development and manufacture companies, optimise them projects is mandatory to survive in the market in long-term.

Traditional methods to find the optimum between cost and performance are not so efficient in general, such as try and error, designers and engineers experience, and gradual evolution of products on the market and benchmark. The problem of these approach methods is that numerous interactions are necessary to find the optimum solution, requiring a long time and higher cost to do it, and there is no guarantee that the solution found in fact is the best possible. Therefore, at this moment the TO is being acclaimed as the best alternative to do it (Brennan, 2014; Larsson, 2016; Sigmund & Maute, 2013). On another hand, biomimicry has been an excellent alternative to find inspiration of concept (Figure 1, Figure 2, Figure 3, Figure 4). The evolutionary process of nature by natural selection had optimised along millions of years the design of living species. This evolution is what some TO algorithms do, them mimics the natural evolution, but only spending a couple of minutes to do it. It is not a coincidence that the most of form generated by TO are organic and look like bones or other natural structures.  Although biomimicry can give directions in the concept, the final form is far from optimal before several interactions, and it leaves us again to looking for TO. Next articles will be discussed TO algorithmic and Biomimicry respectively.

Figure 1 - Design created by Engineer Eiji Nakatsu inspired on a kingfisher bird to prevent the sonic boom of Japan´s 200-mph bullet train when emerging from a tunnel. FONT: ASME

Figure 2 - The Bionic Car. Its aerodynamic has inspired on boxfish, and its structure has optimised by Soft Kill Option (SKO) method, which mimics the structure of trees and bones. FONT: Daimler.

Figure 3 - The leading edge of wind turbine inspired on whale´s fins increase the aerodynamic performance. FONT: WhalePower Corporation.

Figure 4 - Honeycomb shaped advanced composite materials provide a high strength-to-weight ratio. Inspired on bee´s nest cells that support heavyweights. FONT: Asknature.

Another highlight is that the TO and additive manufacturing are opening a new way of products form and design when complex and organic forms with high performance will become easier and more feasible to produce. There is a strong possibility that in next years, the dominant form and design concept around us will be made by organic forms created by TO and Generative Design. As the history of product design shown, the advances of manufacture, material and technologies are some of the main forces that drive how products look like (Figure 5).

Figure 5 – N-14 Thonet´s chair, launched in 1859 with the creation of steam-bending technology. This process allowed to produce a massively and cheapy product (composed of only six elements). Until 1930 has sold more than 50 million of units and it has influenced profoundly chairs concepts (Thonet GmbH, 2015).

Once that the TO is an active tool to find the best form, different of FEM analysis that is more passive due that it needs a form preconceived, the TO is capable of leading the design process since the begin of development. As defended by (Brennan, 2014): “It effectively puts the ‘function’ in front of the ‘form’ in the ‘form/function’ equation”. In other words, adopting the TO is possible to merge engineering and design simultaneously in the process, once that the function can find the form. Moreover, many forms could be found as so efficient as each one, where is necessary only pick which one is adequate for the design requirements (Next articles will be discussed about design requirements) (Figure 6). Another benefit to putting the TO in begin of the design process is the capacity to save time and reduce cost avoiding concept changes due to the test phase of the design. However, these potential benefits are not so direct and certain, once the best-found form for application performance, is not so easy to be manufactured or is required post-treatment in CAD, increasing time and cost of development.

Figure 6 - Example of bicycle frames created by Topology Optimisation. All them are structurally optimised, but the design requirements can eliminate some proposals. FONT: Autodesk.

               

            Gu discusses a trying to compare and measure the winnings with and without the use of TO (Gu, 2013):

Figure 7 - Workflow using not the Topology Optimisation in the initial phase of development (a) and including the Topology Optimisation in the initial stage (b). (Gu, 2013).

            In the traditional process (a), the optimisation only comes in as a plus point to add values. The physical test is the core of development to validate the simulation. Each arrow represents a manual step done by the engineers and designers. In the process with TO and shape/sizing (b), the box of TO intends to replace the box of concept proposal based on prior experience. If necessary, the step shape/sizing could be done autonomously. TO solves the problem from the most extensive possible design space and may generate a near-optimal concept to start designing with. This method avoids suboptimal concept that may be proposed based on prior experience. Subsequently avoids long and tedious design iterations and possible excessive weight/cost upon completion (Gu, 2013).

             

            However, in every company, to decide to replace an old method for a new one, is required some measurement of how many is the gain. If the adoption of TO in initial steps to concept design can save time and investments, on the other hand, the concept found could become a bottleneck in the manufacturing analysing and process, returning all savings obtained before. This dilemma is stronger when an unprecedented product will be designed, in which no data for comparison is available. Estimate the winnings and penalties with TO until the design has been validated is still a hard task. As defended by Gu (2013),many publications of TO industrial application demonstrate the effectiveness of one TO concept but often lack of a systematic sensitivity study that can measure the real gains in comparison with traditional methods of designing. It is estimated that these studies will become a standard task to validate the TO concepts.

            Get the better form of a product is not only a matter of performance and cost to manufacture. The product design and development universe has many other variables. Many of these are intangible and not possible to incorporate into software as quantitative constraints. An evaluation of all constrains and a trying to develop a methodology to merge all these with the use of the TO for product design and development is the main purpose and the challenge of this dissertation.

BILBIOGRAPHY:

Brennan, J. (2014). 20 Years of Topology Optimization: Birth and Maturation of a Disruptive Technology. Retrieved March 1, 2018, from https://insider.altairhyperworks.com/20-years-topology-optimization-birth-maturation-disruptive-technology/

Gu, W. (2013). On Challenges and Solutions of Topology Optimization for Aerospace Structural Design. 10th World Congress on Structural and Multidisciplinary Optimization, 1–7.

Larsson, R. (2016). Methodology for Topology and Shape Optimization : Application to a Rear Lower Control Arm.

Sigmund, O., & Maute, K. (2013). Topology optimization approaches: A comparative review. Structural and Multidisciplinary Optimization, 48(6), 1031–1055. https://doi.org/10.1007/s00158-013-0978-6

Thonet GmbH. (2015). SIMPLY LEGENDARY: THE UNIQUE SUCCESS STORY OF THONET’S ORIGINAL VIENNA COFFEE HOUSE CHAIR 214. Retrieved March 9, 2018, from http://en.thonet.de/service/press/history-214.html