System Engineering
To understand what system engineering was in the 60s and 70s, we must first distract ourselves from the modern view. Looking at IBM's system engineer job posting, one might assume that a system engineer is someone who deals with applications and servers, like a software engineer, then concludes that the word "system" means operating systems. Although the role is not totally irrelevant to system engineering in its original meaning, the job description and other modern information could be misleading. Not only in industry, system engineering also still exists in education. According to System Engineering Research Center, there were over 300 universities that had system engineering program and over 700 programs in total in 2017.
System engineering emerged from the need to manage complex systems (Schlager, 1956, p.64). It dated back to 1940s and was established in Bell Laboratories, since the Bell Lab was the first to encounter complex systems in all industries when they were developing national telephone networks (Schlager, 1956, p.64; International Council on Systems Engineering). Such complexity involved multiple engineering components, and it was not enough to just work with the components independently. The construction of systems must be precisely planned and executed, and that was the time industry needed a specific role called system engineer.
An introduction of the system science program in 1967-68 course catalog. It acknowledged in the first sentence that the program was interdisciplinary. In fact, in the following years, this program would be merged into a department which offered several interdisciplinary programs, related but unique in their own ways. The topics covered by system science were all closely related to the actual operation of systems. Math modeling and simulation helped designing the structures and do estimations. Signals or information flow was a key part in complex systems as they allowed communication among the components. Then came in the need for automation, which was what computers excelled at. Finally, optimization dealt with enhancements in efficiency and reduction of errors. It is interesting that digital computers happened to be invented just in time to solve the system engineering problems. Although the first computer models were built by the Bell Lab, the same organization that promoted system engineering, the early computers were only meant to perform calculations rather than running programs, not to mention automating a system. It was like a beautiful coincidence.
The system science program seemed like a good fit to what the industry wanted from a system engineer, and the courses did match the program description, but did the courses really match the industrial needs? The system science undergraduate curriculum was full of its own courses (SE, system engineering) with a few math courses, much like the modern computer science curriculum. However, dealing with complex systems in application did require knowledge of various types of engineering, and moreover, the program stated it was "multidisciplinary." For comparison, there was another program called "industrial engineering" whose required courses were a true menagerie. What caused the discrepancy? It turned out that the term "system engineering" was not well defined by then. Schlager (1956) pointed out that system engineering had five main stages: "planning, analysis, optimization, integration, and evaluation," and people could refer any of the stages as "system engineering." Poly's system science program, which concentrated on control signals and the use of digital computers, was meant to teach the analysis part, with less focus on other stages. Other stages, however, would be targeted by other fields of study. For example, Poly's industrial engineering program might have been focusing on integration given its variety of engineering courses, and the operations research program could be dealing with optimization.
We could further compare system science, which is supposedly the early-day version of computer science, with computer science concentration in electrical engineering. The most important fact was that system science curriculum did not contain any EE course. The courses with SE tag did not fill up this gap since they were basically theoretical analyses. This difference might remind us about modern day computer science and computer engineering, where CE focuses on hardware construction of digital computer starting from circuits and processors, while CS puts more emphasis on software side such as programming, only reaching assembly languages and machine codes at the lowest level of computer hierarchy. Still, system science was not really the same as modern computer science, given that the main subject was still systems and computers only acted as a tool. It was similar to the math and civil engineering case where they had their own form of "computer techniques" course ---- all of them wanted to solve practical problems with the help of computers, the difference being that computers played a critical role in system engineering compared to the other two fields. This explained the curriculum design of four CS courses for system science, one for math and civil engineering, and none for others (except EE). As technology upgraded, computers became smaller, easier to use, and more accessible to individuals, resulting in more exposure to various fields of study. Tandon's intro to programming has become a requirement for all majors, not only engineering.
As of 1970, system science has been merged into the department of operations research and industrial engineering. The department changed its name to "operations research and system analysis" (ORSA). It stated that it encompassed multiple fields such as operations research, industrial engineering, management science, system analysis, and system engineering. This new department could be recognized as the system engineering in a broader sense, dealing with all aspects of complex systems. The course tag for the original system science changed from SE (system engineering) to SA (system analysis).