Keychains, chairs, doors, buildings, cars, smartphones... the millions of things we use and live amidst. Every one of these drives our lives to varying degrees. That is if we look at them not as products, but as engineeringdesigns. And engineering designs are only as efficient as how appropriate and how much optimization goes into building them. Of course as the graphic says here, engineering, design and optimization are coupled within design cycles.
Quality or Performance vs. Cost (generic)
Optimization is how we arrive at a precise balance between opposing drivers of a design. A quite common case is quality (or performance) and cost, both drivers of engineering designs. As in the graphic here, in aiming for a top- notch quality/ performance, cost would be expected to climb up too! On the other hand, should we aim for a low cost, quite likely quality/ performance would drop as a result. Nevertheless, under a target quality or performance, the latter would not grow indefinitely with cost, but rather converge as seen in the graphic. From a correctly setup optimization, we should thus arrive at that optimum cost that maximizes the quality- to- cost ratio.