What’s the difference between a Master’s in Industrial Engineering vs. Systems Engineering?
5 June, 2021
The Eiffel Tower. The Hoover Dam. And going back much further—The Pyramids of Giza. Engineering marvels have had a prevalent place in history since the dawn of humanity. And, of course, so have the engineers who created them.
Engineering is a vital profession not only for keeping our technology and infrastructure running, but for exploring and designing new systems and ideas. As the pace of technological evolution accelerates, so do the opportunities for engineers to build remarkable innovations. In the last few years, engineers have created floating bridges for light rail lines and upgraded 3D printing machines that operate far faster than previous machines.
There have also been dramatic improvements in healthcare thanks to engineering and medical technology. For example, in 2018, the Department of Defense introduced a new “pacemaker” for the brain that could boost memory for people with Parkinson’s, Alzheimer’s disease, and epilepsy.
This article will discuss two branches of engineering that rely on a systems point of view: systems engineering and industrial engineering. In addition to examining career outcomes and skills required for these two disciplines, we’ll explore the roles that these engineers fill in pushing technology forward.
What is the difference between industrial and systems engineering?
The Institute of Industrial & Systems Engineer (IISE) describes the focus of systems and industrial engineering as follows: “Industrial and systems engineering is concerned with the design, improvement and installation of integrated systems of people, materials, information, equipment and energy.”
Systems engineers design and optimize complex systems. They work with an array of other technology professionals, including software engineers, hardware engineers, and programmers.
Industrial engineers manage and improve manufacturing processes and service operations. An industrial engineer is primarily concerned with finding ways to better utilize machinery, employees, and additional assets that impact operations.
Though not all engineering jobs require an advanced degree, earning a master’s degree in either systems engineering or industrial engineering can help you enter senior-level roles and possibly increase your earning potential.
Let’s take a closer look at the difference between a master’s in systems engineering vs. a master’s in industrial engineering.
Master’s in Systems Engineering | Master’s in Industrial Engineering | |
---|---|---|
Common Core Courses | Systems Engineering Processes, Engineering Statistics, Theory of Linear Systems | Fundamentals (or Survey) of Optimization, Stochastic Modeling, Production System Analysis |
Key Focuses | Reliability testing, linear systems, simulation modeling and analysis, quality control | Optimizing manufacturing operations, production control, supervising high-tech production processes |
Key Skills Needed | Linux, requirements analysis, systems engineering | Project management, process improvement, data analysis |
Source: PayScale.com
Systems engineering graduate programs
Pursuing a master’s degree in systems engineering can help you develop a wide range of applicable skills. Graduate engineering programs can vary significantly based on the disciplines they cover. For example, the University of Arizona’s online Master of Science in Systems Engineering program is part of the Department of Systems and Industrial Engineering, established in 1961 as the nation’s first department of systems engineering. The master’s program focuses on the design, analysis, and modeling of advanced systems. It also teaches additional skills needed for project management, like staying on budget and meeting project requirements.
Systems engineering curricula include core courses such as the systems engineering processes, a thesis, and projects such as model analysis and research reports. UA’s online Master’s in Systems Engineering is highly customizable, allowing students to create an individual academic plan to fit their professional goals.
Our systems engineering courses focus on both technical proficiency with engineering concepts and principles, and project management. For example, the Simulation Modeling and Analysis course explores discrete event simulation, model development, variance reduction, and other key concepts. The Advanced Production Control course has a project management focus, teaching models in analysis, planning, and control of production systems.
Careers with a Master of Science (MS) in Systems Engineering
Job | Average salary |
---|---|
Principal Systems Engineer | $131,000 |
Senior Systems Engineer | $111,000 |
Project Engineer | $89,000 |
Electrical Engineer | $85,000 |
Mechanical Engineer | $81,000 |
Source: PayScale
Systems engineers use expert knowledge of engineering, computer science, and mathematics to design computing technology, software, and other systems. They work within a variety of disciplines, including electric power, information technology, sewage, telephones, and military defense. According to PayScale, the average salary with a systems engineering master’s degree is $103,000.
These are typical responsibilities of a systems engineer:
- Oversee the installation of new software and hardware
- Check existing systems for structural integrity, and suggest improvements
- Install operating systems and other software
- Apply tech solutions to strengthen systems and troubleshoot computer problems
- Provide direction to IT staff
- Acquire, test, install, and maintain project components and operating systems
- Develop client-specific software programs
- Implement security systems and backups to maintain data safety
- Review control documents
In addition to their everyday responsibilities, systems engineers are expected to keep their technology skills up-to-date. For example, one of the key trends in machine learning is a shift in where the data processing actually takes place. Rather than store these algorithms in the cloud, many organizations are moving machine learning to the “edge” of their networks—by moving these algorithms to embedded devices and microcontroller-based systems.
In fact, edge computing is changing the way engineers design and optimize networks. Instead of sending data on a potentially lengthy trip to remote data centers, edge computing allows it to be processed closer to the source. This gives organizations the ability to analyze data in near real time. It also reduces latency, which is especially important in industries where every second counts, like manufacturing, finance, or in autonomous vehicles.
Industrial engineering graduate programs
The University of Arizona Master of Science in Industrial Engineering program helps students develop key skills in industrial engineering, including how to supervise high-tech production processes and optimize manufacturing operations. The program provides students with an in-depth exploration of technical skills including automation, traffic modeling, and computer-integrated manufacturing.
Industrial engineering courses cover topics such as optimization, quality and reliability, and simulation systems. For example, Fundamentals of Optimization studies constrained and unconstrained optimization problems from a numerical standpoint. Advanced Quality Engineering explores advanced techniques for statistical quality assurance. The Advanced Production Control course has a project management focus, teaching models in analysis, planning, and control of production systems.
Like systems engineering, The UA online Master’s in Industrial Engineering is also highly customizable. The industrial engineering curriculum includes three different paths—project, thesis, and coursework—to help students achieve their specific career goals.
Related Content: Master’s in Industrial Engineering vs. MBA
Careers with a Master of Science (MS) in Industrial Engineering
Job | Average salary |
---|---|
Data Scientist | $96,000 |
Process Engineer | $73,000 |
Industrial Engineer | $69,000 |
Manufacturing Engineer | $68,000 |
Supply Chain Analyst | $63,000 |
Source: PayScale
According to U.S. Bureau of Labor Statistics, where engineers work is dependent on the challenges they are trying to solve. For example, if an industrial engineer is working on a production issue, they might observe workers in a factory. Industrial engineers may also work in office settings, where they analyze production data and identify opportunities for creating efficiencies.
As the manufacturing industry pushes for adoption of technologies like artificial intelligence and robotics that are capable of completing more complex tasks, demand for skilled engineers is likely to grow. According to the Skills Gap in U.S. Manufacturing study, over the next decade (from 2015 to 2025) 3.5 million manufacturing jobs will likely be needed, and 2 million are expected to go unfilled due to the skills gap—one of the major contributing factors to this gap is the lack of STEM education among younger generations of employees. As a result, the engineers who can navigate the complexities of optimizing automated processes and production will be well-positioned for advanced roles in the industry.
The manufacturing industry itself is shifting, driven forward by innovations in artificial intelligence and automation. For example, Dex-Net —created by U.C. Berkeley professor Ken Goldberg and his student Jeff Mahler—is a software that allows robots to deftly handle objects, even when the AI had no prior exposure to these objects, and sort through them at record speed. Another example is Daisy, Apple’s recycling robot that strips apart iPhones and allows the materials to be reused.
According to PayScale, the average salary with an industrial engineering master’s degree is $78,000. The U.S. Bureau of Labor Statistics shows that there is expected to be faster than average job growth for industrial engineers between 2016 and 2026.
As the systems and machinery that make the modern world run become increasingly complex, engineering leaders will need to retain multidisciplinary knowledge. For example, though industrial engineers might not have to write algorithms, they might need to design or optimize equipment that an algorithm interacts with. These challenges will likely grow as our systems become more deeply interconnected and as embedded AI becomes more commonplace. For engineers that continue to deepen their domain knowledge and learn to apply engineering principles to novel technology and scenarios, there will be numerous opportunities to play a major role in these technological evolutions.