The phrase “engineering science” appeared at the beginning of the eighteenth century, a full six decades earlier than the appearance of the phrase “social science.”  Engineering science, together with research and development, shifted into high gear after World War II. 

Science generally is a state of knowing or possessing knowledge that is sufficient generally, clearly conceptualized and systematized, critically examined and empirically tested.  It addresses not only what is but also what can be, because it goes beyond cataloging facts to supporting contrary-to-fact hypotheses.  Natural sciences concern with what can be under physical laws.  Engineering sciences add the constraint of utility and ask what can be of use under physical laws and other practical constraints.  An engineering science delineates the underlying principles and mechanisms for a broad type of artificial system with physical bases susceptible to deliberate design and control, for instance systems that effectively utilize heat.

Utilitarian considerations open a new dimension in engineering science.  Questions regarding what for, how to, and how good, which are usually absent in the contents of natural science, become central to the contents of engineering science.  They are represented by functional concepts.  Engineers investigate not only a system's physical structures but also its functions, or the services that it delivers to some external environment.  Structures and functions are of course interrelated, but specific studies can emphasize one or the other.  Engineering sciences roughly divide into two classes: physical and systems.  The former distinguishes topics according to underlying mechanisms, the latter according to functions.  Both are mathematical, although with their theorem-proof style, systems theories -- information, control, and computation theories -- are closer to pure mathematics.

The American Society for Engineering Education (ASEE) in 1955 identified six engineering sciences: mechanics of solids, fluid mechanics, thermodynamics, transport phenomena, electromagnetism, material structures and properties.  They share the basic laws and principles of the physical sciences but have developed substantial bodies of concrete details.  If you go to a book on engineering thermodynamics, of course you will find the laws of thermodynamics, but you will also find control volume and many other concepts that are usually absent in physics textbooks.

Engineering sciences are often integrative, because a complex system usually involves mechanisms studied in several academic disciplines.  An synthetic theory, which brings knowledge from two sciences to bear on a single topic, is more than the sum of its parts, because it must introduce novel concepts to fill in the gaps, establish interfaces, and reconcile different approximations.  For example, chemical engineering has synthesized chemistry and physics to produce a body of scientific knowledge useful for industrial chemical processing.  With the rapid advancement of bioengineering, cell or molecular biology may well emerge as a new engineering science.

ASEE also suggested a seventh candidate for engineering science: information theory.  In contrast to the other six, which are all physical, information theory is a systems science.  Systems theories abstract from most physical characteristics of a system and concentrate on the functions it performs.  For example, information theory investigates systems that perform the function of reliably transmitting messages from a source to a destination, regardless whether the messages go through copper wires, optical fibers, or satellite links, so that its results are pertinent to all media.  Three large groups of systems theories are communication (including information), control, and computation.  The former two are most indigenous to engineering.  The general nature of systems theory is discussed more fully in "Concepts of systems in engineering."

Claude Shannon’s information theory that introduced, among other results, a mathematical definition of information in communication engineering, is probably the most famous of engineering theories.  Like computers, it has been hyped by engineers and further blown up by journalists and philosophers.  Like other thoughtful engineers and scientists, Shannon was disturbed about the “bandwagon” and warned: “Although this wave of popularity is certainly pleasant and exciting to those of us working in the field, it carries at the same time an element of danger.  While we feel that information theory is indeed a valuable tool in providing fundamental insights into the nature of communication problems and will continue to grow in importance, it is certainly no panacea for the communication engineer or, a fortiori, for anyone else.  Seldom do more than a few of nature’s secrets give way at one time.  It will be all too easy for our somewhat artificial prosperity to collapse overnight when it is realized that the use of a few exciting words like information, entropy, redundancy, do not solve all problems. . .   The subject of information theory has certainly been sold, if not oversold.  We should now turn our attention to the business of research and development at the highest scientific plane we can maintain.” -- C. E. Shannon, The bandwagon.  IEEE Transactions on Information Theory, 2: 3 (1956).  Such sober and critical attitude expresses the essence of science.

Physical engineering sciences

Detailed references are found under various branches of engineering.  For general characteristics, see:

Grinter, L. E. 1955.  Report of the Committee on Evaluation of Engineering Education.  Journal of Engineering Education, 44: 25-60.

Slepian, D. 1976.  On bandwidth.  Proceedings of the IEEE, 64: 292-300. (Epistemological reflection and technical analysis of reality and its mathematical representations, based on a paradox in the bandwidth theorem).

Zadeh, L. A. 1962.  From circuit theory to system theory.  Proceedings of the IRE, 50: 856-65.

Information theory

Gappmair, W. 1999.  Claude E. Shannon: the 50th anniversary of information theory.  IEEE Communications Magazine, 37(4): 102-5.

Wyner, A. and Shamai, S. 1998.  Introduction to “Communication in the presence of noise” by C. E. Shannon.  Proceedings of the IEEE, 86: 442-6.

Biglieri, E. and Torino, P. D. 2002.  Digital transmission in the 21st century: conflating modulation and coding.  IEEE Communications Magazine, 49(5): 128-34.

Costello, D. J., Hagenauer, J. Imai, H. and Wicker. S. B. 1998.  Applications of error-control coding.  IEEE Transactions on Information Theory, 44: 2531-

Drajic, D. and Bajic, D. 2002.  Communication system performance: achieving the ultimate information-theoretic limits?  IEEE Communications Magazine, 49(6): 124-9.

Gallager, R. G. 2001.  Claude E. Shannon: a retrospective on his life, work, and impact.  IEEE Transactions on Information Theory, 47: 2681-96.

Luke, H. D. 1999.  The origin of the sampling theorem.  IEEE Communications Magazine, 37(4): 106-8.

Pierce, J. R. 1973.  The early days of information theory.  IEEE Transaction on Information Theory, IT-19: 3-8.

Shannon, C. E. 1948.  A mathematical theory of communication.  Bell System Technical Journal, 27: 379-423, 623-56.

Shannon, C. E. 1949.  Communication in the presence of noise.  Proceedings of the IRE, 37: 10-21; reprinted in Proceedings of the IEEE, 86: 447-57 (1998).

Unser, M. 2000.  Sampling – 50 years after Shannon.  Proceedings of the IEEE, 88: 569-586.

Verdú, S. 1998.  Fifty years of Shannon theory.  IEEE Transaction on Information Theory, 44: 2057-78.

Control systems

IEEE Control Systems Magazine frequently publishes historical perspectives.  Its jubilee issue 16(3) (June 1996) features invited papers on the histories of automatic, optimal, nonlinear, adaptive, stability, stochastic, and robust control.

Bennett, S. 1996.  A brief history of automatic control.  IEEE Control Systems, 16(3): 17-25

Amin, M. 2002.  Modeling and control of complex interactive networks.  IEEE Control Systems, 22(1): 22-8.

Anderson, B. D. O. 1993.  Controlled design: moving from theory to practice.  IEEE Control Systems, 13(4): 16-25.

Bellman R. and Kalaba, R. eds. 1964.  Selected Papers on Mathematical Trends in Control Theory, NewYork: Dover.

Bennett, S. 1979.  A History of Control Engineering: 1800-1930.  London: IEE Press.

Bennett, S. 1993.  A History of Control Engineering: 1930-1955.  London: IEE Press.

Black, H. S. 1977.  Inventing the negative feedback amplifier.  IEEE Spectrum, 14(12): 55-61.

Bode, H. W. 1960.  Feedback – the history of an idea.  Reprinted in Selected Papers on Mathematical Trends in Control Theory, eds. R. Bellman and R. Kalaba, NewYork: Dover, pp. 106-23.

Evans, L. B. 1977. Impact of electronics revolution on industrial process control.  Science, 195” 1146-60.

Heck, B. S. 1999.  Future directions in control education.  IEEE Control Systems, 19(5): 35-6.

Joshi, S. S. 1999.  The need for a systems perspective in control theory and practice.  IEEE Control Systems, 19(6): 56-63.

Kailath, T. 1997.  Nobert Wiener and the development of mathematical engineering.  In Communications, Computation, control, and Signal Processing, ed. A. Paulraj, W. Raychowdbury, and C. D. Schaper, Boston: Kluwer, pp. 35-65.

Kalman, R. E. 1969.  Elementary control theory from the modern point of view.  In Topics in Mathematical System Theory, by R. E. Kalman, P. L. Falb, and  M. A. Arbib, New York: McGraw Hill, pp. 25-68.

Mayr, O. 1970.  The Origins of Feedback Control.  Cambridge: MIT Press.

Mayr, O. 1971.  Adam Smith and Concepts of Feedback System.  Technology and Culture, 12: 1-22.

McRur, D. and Graham, D. 1981.  Fifty years of flight control: triumphs and pitfalls of the systems approach.  AIAA Journal of Guidance and Control, 4: 353-62.

Mindell, D. A. 2002.  Between Human and Machine: Feedback, Control, and Computing Before Cybernetics.  Cambridge: MIT Press.

Schmidt, S. F. 1981.  The Kalman filter: its recognition and development for aerospace applications.  Journal of Guidance and Control, 4: 4-8.

Sussmann, H. J. and Willems, J. C. 1997.  300 years of optimal control: from the Brachystochrone to the maximum principle.  IEEE Control Systems, 17(3): 32-44.

Theories of computation

ACM. 1987.  ACM Turing Award Lectures: the First Twenty Years, New York: ACM Press. (Contains A. J. Perlis’s “The synthesis of algorithmic systems,” D. E. Knuth’s “Computer programming as an art,” E. W. Dijkstra’s “The humble programmer,” D. M. Ritchie’s “Reflection on software research,” and more.”

Borwein, J. M. and Borwein, P. B. 2001.  Challenges in mathematical computing.  Computing in Science and Engineering, 3(3): 48-54.

Chabert, J. 1999.  A History of Algorithms.  Berlin: Springer.

Hamming, R. W. 1968.  One man’s view of computer science.  In ACM Turing Award Lectures, ACM Press, pp. 207-18.

Hartmanis, J. 1995. On computational complexity and the nature of computer science.  ACM Computing Surveys, 27: 7-16.

Hopcroft, J. E. 1990.  Reflections on computer science.  Annual Review of Computer Science, 4: 1-12.

Knuth, D. E. 1977.  Algorithms.  Scientific American. April, 236(4): 63-80.

Laplante, P., ed. 1996.  Great Papers in Computer Science.  New York: IEEE Press.

Loui, M. C. 1996.  Strategic directions in research in theory of computing.  ACM Computing Surveys, 28: 565-89.

Mertens, S. 2002.  Computational complexity for physicists.  Computing in Science and Engineering, 4(3): 31-48.

Metropolis, N., Howlett, J., and Rota, G. eds. 1980.  A History of Computing in the Twentieth Century.  New York: Academic Press.

Pollack, S. V. 1982.  The development of computer science.  In Studies in Computer Science, ed. S. V. Pollack, Washington, D.C.: The Mathematical Association of America, pp. 1-51.

Saiedian, H. ed. 1996.  An invitation to formal methods.  Special issue in Computer, April, 29(4): 16-30.

Sullivan, F. ed. 2000.  The top 10 algorithms.  Special issue in Computing in Science and Engineering, 2(1): 22-79.