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Industrial Mathematics Charles R. MacCluer

Industrial Mathematics By Charles R. MacCluer

Industrial Mathematics by Charles R. MacCluer


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Summary

This book provides a concise, single-source survey of all the mathematics most useful in industry today-- particularly modeling and the unit $.

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Industrial Mathematics Summary

Industrial Mathematics: Modeling in Industry, Science and Government by Charles R. MacCluer

For senior-level or masters courses in Industrial Mathematics or Modeling.

This concise, single-source survey of all the mathematics most useful in industry, provides graduating seniors or MS students with a last chance to prepare for the marketplace. Typically, such students are well grounded in the fundamentals of mathematics but not in its practice. They usually have little experience in modeling or in the particular extensions of mathematics useful in industrial problems-e.g., they may know power series but not the z-transform, orthogonal matrices but not factor analysis, Laplace transforms but not Bode Plots. Likewise, they usually have no experience with problems incorporating the unit $. Mathematicians in industry must be able to see their work from an economic viewpoint. They must be able to communicate with engineers using their common dialect, the dialect of this book.

Table of Contents

(NOTE: Each chapter concludes with Exercises.)

1. Statistical Reasoning.

Random Variables. Uniform Distributions. Gaussian Distributions. The Binomial Distribution. The Poisson Distribution. Taguchi Quality Control.



2. Monte Carlo Methods.

Computing Integrals. Mean Time between Failure. Servicing Requests. The Newsboy Problem (reprise).



3. Data Acquisition and Manipulation.

The z-transform. Linear Recursions. Filters. Stability. Polar and Bode Plots. Aliasing. Closing the Loop. Why Decibels?



4. The Discrete Fourier Transform.

Real Time Processing. Properties of the DFT. Filter Design. The Fast Fourier Transform. Image Processing.



5. Linear Programming.

Optimization. The Diet Problem. The Simplex Algorithm.



6. Regression.

Best Fit to Discrete Data. Norms on Rn. Hilbert Space. Gram's Theorem on Regression.



7. Cost Benefit Analysis.

Present Value. Life-Cycle Savings.



8. Microeconomics.

Supply and Demand. Revenue, Cost, and Profit. Elasticity of Demand. Duopolistic Competition. Theory of Production. Leontiev Input/Output.



9. Ordinary Differential Equations.

Separation of Variables. Mechanics. Linear ODEs with Constant Coefficients. Systems.



10. Frequency-Domain Methods.

The Frequency Domain. Generalized Signals. Plants in Cascade. Surge Impedance. Stability. Filters. Feedback and Root Locus. Nyquist Analysis. Control.



11. Partial Differential Equations.

Lumped versus Distributed. The Big Six PDEs. Separation of Variables. Unbounded Spatial Domains. Periodic Steady State. Other Distributed Models.



12. Divided Differences.

Euler's Method. Systems. PDEs. Runge-Kutta Method.



13. Galerkin's Method.

Galerkin's Requirement. Eigenvalue Problems. Steady Problems. Transient Problems. Finite Elements. Why So Effective?



14. Splines.

Why Cubics? m-Splines. Cubic Splines.



15. Report Writing.

The Formal Technical Report. The Memo. The Progress Report. The Executive Summary. The Problem Statement. Overhead Projector Presentations. Approaching a Writing Task. Style. Writer's Checklist.



References.


Index.

Additional information

CIN0139491996G
9780139491993
0139491996
Industrial Mathematics: Modeling in Industry, Science and Government by Charles R. MacCluer
Used - Good
Hardback
Pearson Education (US)
19990929
308
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in good condition, but if you are not entirely satisfied please get in touch with us

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