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The Role of Manufacturing Process Design in Technology Commercialization
Published in Harriet B. Nembhard, Elizabeth A. Cudney, Katherine M. Coperich, Emerging Frontiers in Industrial and Systems Engineering, 2019
Brian K. Paul, Patrick McNeff, Sam Brannon, Michael O’Halloran
To aid in the calculation of the production cost, a MATLAB program was developed to make all raw material and processing calculations based on the format of an input spreadsheet. The format of the input data is shown in Table 14.4. The resultant calculations are plotted in a production cost curve as shown in Figure 14.11. The characteristic curve is an exponential decay with asymptotic behavior that moves toward minima as the utilization of all machine tools in the MPD is maximized. The production volume at which the curve approaches the minimum production cost is considered the knee in the curve. In Figure 14.11, the curve appears to reach near minima between 1,000 and 2,000 units/year.
Shrinkage Estimators
Published in Norman Matloff, Statistical Regression and Classification, 2017
One way to choose λ is visual: For each predictor variable, we draw a graph, the ridge trace, that plots the associated estimated coefficient against the value of λ. We choose the latter to be at the “knee” of the curve. The function lm.ridge () in the MASS package (part of the base R distribution) can be used for this, but here we will use the function ridgelm () from regtools, due to its approach to scaling. Here is why:
Mooring system design optimization using a surrogate assisted multi-objective genetic algorithm
Published in Engineering Optimization, 2019
Ajit C. Pillai, Philipp R. Thies, Lars Johanning
In Figure 6, the minimum cost solution and minimum fatigue solution are both highlighted. These solutions represent the extents of the Pareto front and can be thought of as the solutions to single-objective optimization problems along either of these objectives. From the shape of the curve, it is apparent that the two objectives are indeed competing; however, there is a high density of solutions near the knee of the curve that may potentially represent a good compromise solution between the two extremes. In fact, though the minimum cost solution coincides with the maximum fatigue damage solution, there are many solutions with similar cost values at significantly lower fatigue levels.