Enterprise Systems Optimization Lab (ESOL)

Emily Scott


ISE Professor Harrison Kim
ISE Professor Harrison Kim

An ISE laboratory is at the forefront of advancing research in the area of complex systems design and sustainability.


The Enterprise Systems Optimization Lab (ESOL), led by Professor Harrison Kim, provides students with training in systems optimization that allow them to enter the workforce with the ability to impact real-life systems.

Founded in 2005 and housed on the fourth floor of the Transportation Building, ESOL is has been an extension of Kim’s research in systems design and optimization.

“I’m the guy who does systems design and design and analytics in the context of optimization,” Kim said.

Systems, he explained, could be anything from products to infrastructure, with a variety of different aspects — such as environmental, performance, or sustainability.

In this area of research, Kim is known for developing a method called Analytical Target Cascading (ATC). This method provides a way to take complex system design problems and break them down into manageable sizes.

“Sometimes it could be hierarchical, so you decompose it so that you can manage it on a smaller scale, and then coordinate those pieces together,” Kim said. “It’s like collaboration. One person cannot do everything, so what do you do? You form a team of experts, they work together.”

Kim said to think of ATC as “a mathematical model of systems design.”

Though he said he has been known as “the ATC guy” throughout his career, Kim said the core ideas of complex system design have evolved. Currently, he is interested in incorporating the role of data and analytics.

“Back in the days when people designed complex systems . . . somebody gave you a requirement, you’d design your complex system, achieve your system design by meeting this requirement, that’s it,” Kim said. “Now, it’s a little different. A lot of data coming from the usage of the product is available.”

He gave an example in product reviews on websites like Amazon and Google. Because designers can listen to what the market has to say and then incorporate this into their product design, the design process is affected.

After developing ATC, Kim thought of a way to incorporate these large amounts of data to help design systems or products better.

“That’s where we get this idea of this design analytics,” Kim said. “It’s basically the integration of data science and systems design, and we do these together for the purpose of designing complex systems that not only satisfy design and manufacturing but also incorporate the usage and entire life cycle of the product.”

Kim decided to start the Enterprise Systems Optimization Laboratory in 2005 to explore these areas of his research and provide students with adequate training to enter the field by working on a variety of projects. The lab has trained a number of successful students that have entered industry and academia.

Projects in the lab have included developing different methodologies and frameworks for mapping a product’s life cycle, optimizing systems, and making decisions in the design process. These frameworks could affect industries such as automotive, consumer electronics, wind energy, manufacturing, heavy-duty equipment and much more.

In the future, Kim hopes to continue doing work that has an impact.

“The work that I do in the lab has direct impact either in industry or in the world, that’s what I’m getting most excited about,” he said. “Whether it’s through people, like students working in different aspects, or particular products . . . those are the times that I can see what I do is actually having direct impact on real world applications.”

He is particularly interested in working on the energy side of systems optimization, especially in renewable energy systems.

“I’ll continue to work with design analytics, using available data, information abundantly available, and trying to incorporate that in the complex system design and try to understand better how the product is used,” Kim said.

Kim said he has enjoyed working with students over the years, including his advisement of several Senior Design Projects.

“To see how students start from the beginning and try to master those industry problems . . . those are the times that I feel that, yeah, this career is pretty good.”


Predictive life cycle design framework by capturing user-centered data.
Predictive life cycle design framework by capturing user-centered data.


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