| | april 20148CIOReviewopinionin myI have come to realize that engineering, even at its finest, is an iterative business. As well as we can understand our customers' requirements, and with our past history, experience, skills, talents and engineering acumen, we come to the realization that our knowledge is not perfect. There will undoubtedly be conditions that we discover along our product development journeys that we did not realize at the inception of a program or project. There will be environmental conditions we did not expect, or interactions with other elements of the system we did not foresee. There is always a certain amount of variation in the manufacturing processes used to make our products that may not be completely quantified as we begin our designs. These facts all lead to the understanding that we need to have iterative learning loops in our development and validation processes. To address these pressures, engineers have been developing simulation and modeling technologies that enable these learning loops to occur quickly and cost effectively. Costly and time consuming physical prototypes, allowing only one or two learning loops, can now be performed in math, allowing many more iterations and developments to occur to optimize and refine the design in days, rather than months. Global automakers and suppliers are turning to globally knitted engineering organizations designed to leverage corporate resources 24/7. Math-based modeling and simulation tools assist the engineering teams in making multiple design iterations, many that run while they are home asleep. The systems assist with "designing in" product performance attributes such as durability, reliability, By Terry J. Woychowski , SVP-Engineering & Quality, AAMAmerican Axle & Manufacturing, Inc. [NYSE: AXL] is a manufacturer of automobile driveline and drivetrain components and systems. Detroit, MI based AAM has a market cap of $1.35 Bn.The Use of Modern Technologies in Driveline Engineering
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