The radical concepts of engineering stochastic optimization are introduced and a method for solving uncertain problems is developed according to the satisfied estimation of probabilistic values to stochastic constraints and the use of a quasi-gradient searching direction. The method is applied to engineering designs with linear or nonlinear stochastic constraints
Systems Engineering and Lean Thinking Systems Engineering grew out of the space industry in response to the need to deliver technically complex systems that worked flawlessly upon first use SE has emphasized technical performance and risk management of complex systems
This 90 minutes lecture to be delivered via telelink addresses a class of mit undergraduates unrolled in Engineering Design and Rapid prototyping Course. The students have been introduced to the basic optimization concepts of design variables design space, objective function, constraints and numerical search methods. Building on this elementary basis, the purpose of the lecture is to make the students aware of a reaud range of theoretical and practical issues that arise when optimization is applied in real-life engineering. To that end a gamut of topics is presented with emphasis on the qualitative exposition rather than in-depth mathematics. The topics include
Systems Engineering and Lean Thinking Systems Engineering grew out of the space industry in response to the need to deliver technically complex systems that worked flawlessly upon first use
ENGINEERING ECONOMICS II INVESTMENT ANALYSIS Companies(and individuals) invest money in order to earn money Examples Build a factory to make washing machines and dryers → Open laundromat Write novel(what is being invested here?) Get a degree in chemical engineering
