Material Selection & Concept Design
Material selection and concept design for a product are likely the most critical determinants of the success of a structural plastics product design in end-use and the marketplace. The design team must rely on skill or chance to determine:
- Should the material be organic or metallic?
- Is the product's performance going to be dominated by strength, stiffness, or other attributes?
- How many components will the product consist of? How will those components be made? How will the components be assembled or attached?
The answers to these questions may seem obvious at first, but even small changes to the material selection or concept design can have large impacts on downstream product development including manufacturing, supply chain, and marketing strategies. Reflection during post-mortem analysis often shows that biases were introduced or assumptions were made resulting from a limited scope of the design universe. Accordingly, methods including formal specification, risk analysis, and failure modes and effects analysis (FMEA) are critical to ensuring the best possible structural plastics product design.
Internal printer chassis consisting of modular sub-component designs
Advances in numerical techniques have fueled advances in artificial intelligence and optimization. While we have investigated techniques such as simulated annealing and neural networks to assist in topology (shape) optimization, we have consistently found that constrained optimization techniques (e.g. simplex, gradient, and others) provide significant capabilities with respect to understanding and improving the design's behavior while identifying and managing dominating constraints. Typical objectives are to improved the product's strength and stiffness in a variety of end-use conditions while reducing material cost, manufacturing cost, and design envelope or environmental impact.
These optimization techniques are readily extensible to multiple objective, Pareto optimization, and robustness modeling in lean and Six Sigma decision frameworks. The advantage of these techniques is that they allow formal exploration of trade-offs between different design objectives as well as statistical analysis of performance and risk.
As another application of optimization related to structural plastics product design, we also have extensive experience in material constitutive modeling to provide fitted material model coefficients for a variety of elastic, viscosity, and viscoelastic constitutive equations. The fidelity of these models can be quantified relative to observed test data to provide a rational basis for simulation-based design and optimization.