
Industrial Mathematics: Modeling in Industry, Science and Government, 1/e
Charles R. MacCluer, Michigan State University
Published August, 1999 by Prentice Hall Engineering/Science/Mathematics
Copyright 2000, 308 pp.
Cloth
ISBN 0139491996

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For seniorlevel or masters courses in Industrial Mathematics
or Modeling.
This concise, singlesource 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 ztransform, 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.
Sparse, brief writing style.
 Speaks to seasoned mathematics, engineering, and science
students in language with which they are comfortable.
Relevant mathematics, then realworld industrial extensions—Each
chapter begins with a brief review of some relevant mathematics, then
introduces the industrial extension of this same material via typical
realworld applications.
 Ensures that students have a firm understanding of
the mathematics before tackling applications and familiarizes
students with the full range of applications they are likely to encounter
in the workplace.
A modern approach to problem solving—Demonstrates
the power of interweaving analytic with computing
methods during problem solving.
 A modern mathematics worker in industry cannot be
fully effective without both analytic and computing skills.
MATLAB incorporated into exercises—Many exercises
require students to experiment with or to modify the given MATLAB
routines, all of which are available at the author's anonymous ftp
site. Other exercises ask students to generate code themselves.
 MATLAB has become the industrywide, standard computing
and simulation tool. Familiarity with MATLAB will be invaluable on
the job and at interview time.
Openended exercises marked as “Projects”—Require
students to delimit the investigation, collect data, experiment, or
consult industrial experts; organize the data; then deliver the data
in a formal technical report.
 The student is exposed to team project development,
universal in industry.
A chapter on Technical Writing—Covers formal
technical reports, memos, progress reports, executive summaries, problem
statements, and overhead projector presentations.
 Communication skills are essential to success. Workers
in industry are judged not on their work but on how they present their
work.
(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 ztransform. 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 R^n. Hilbert Space.
Gram's Theorem on Regression.
7. Cost Benefit Analysis.
Present Value. LifeCycle 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. FrequencyDomain 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. RungeKutta Method.
13. Galerkin's Method.
Galerkin's Requirement. Eigenvalue Problems. Steady Problems.
Transient Problems. Finite Elements. Why So Effective?
14. Splines.
Why Cubics? mSplines. 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.
