Designing a component, process or a control system to achieve minimum or maximum of a single objective (or goal) often results in a single optimum solution describing the shape, dimensions, process or strategy of solving the task. Although such an optimized solution may already provide a new and innovative way of achieving the best objective value, it is almost never the case that practitioners are solely interested in a single objective. Moreover, a single optimum solution does not often provide adequate information to *learn* much about the problem, a matter which is ideally desired in engineering and scientific problem-solving tasks. In this seminar, we shall discuss an “innovization” procedure involving a multi-objective optimization algorithm for finding a set of trade-off optimal solutions. An investigation of such solutions is then expected to reveal useful design principles common to high-performing solutions. A number of interesting engineering case studies will be discussed to demonstrate how useful and innovative design principles can be deciphered by considering two or three-objective optimization problems. Such design innovations are difficult to achieve by any other means and the proposed systematic procedure should find a wide-spread applicability in the coming years.