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In the context of product design, it is very important to appreciate the limitations of a design from manufacturing and assembly perspective and to produce high quality products at low cost. This course will introduce methods that can provide guidance to design teams in simplifying product structure to reduce manufacturing and assembly costs, quantify improvements and how robust design concepts can be used for ensuring quality. This course aims at introducing the need to account for variability, mathematically represent it, formulate it and control it. Concepts such as quality, robustness, six sigma and orthogonal array will be discussed.
INTENDED AUDIENCE : Final year UG students, Masters and PhD Students, Engineering practitioners in industryPREREQUISITES : Basic knowledge on manufacturing such as manufacturing techniques and probability
INDUSTRY SUPPORT : Fiat Chrysler Automotive, Daimler India, Cyient, Saint Gobain
Overview
Syllabus
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COURSE LAYOUT
Week 1 : Introduction, course expected outcomes, discussion on qualityWeek 2 : Measuring quality: Quality loss function. Discussion on robustness, six sigma conceptsWeek 3 : Quantifying robustness: Signal to Noise Ratio, problem formulation using SNR. Design of experiment discussionsWeek 4 : Orthogonal array, linear graphs, triangular tables, finding optimum combinations. Case studiesWeek 5 : Design for Manufacturing: over the wall design, most influential phase in design, best practices in injection molding and Design for additive
manufacturingWeek 6 : Do’s and dont’s in manual assembly, assembly time estimation, design for robotic assembly considerationsWeek 7 : Design for Assembly: Boothroyd Dewhurst method, theoretical minimum number of parts, Xerox producibility index (XPI) methodWeek 8 : Usage of DFMA software and Design for sustainability
