A Practical Guide to Problem-Solving Techniques in Systems Engineering

A Practical Guide to Problem-Solving Techniques in Systems Engineering
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In the world of systems engineering, identifying and addressing issues is a significant part of the job. To ensure the smooth operation of complex systems, engineers employ various practical problem-solving techniques. Problem-solving techniques are not limited to solving issues specific to any one system, but can also be applied when generating new product ideas and solutions.

We'll start by exploring some common analytical and systematic problem-solving techniques, including thought experiments, the 5 Whys, and root cause analysis, before looking at some more creative techniques.

Analytical and Systematic Problem-Solving Techniques

Thought Experiments

A thought experiment is a disciplined imagination process that engineers use to ponder a problem or system without conducting physical experiments. By using hypothetical scenarios, engineers can predict potential challenges and find solutions without the cost and time of real-world testing.

For instance, consider the design of an urban traffic control system. Engineers can create a thought experiment about how the system would handle an emergency, such as a major traffic accident during rush hour. This mental exercise could help identify potential bottlenecks or gaps in the system, allowing engineers to design more effective controls or contingency plans.

5 Whys

The 5 Whys technique, originally developed by Toyota, is a simple yet effective method to drill down to the root of a problem. By repeatedly asking "why?" in response to the previous answer, engineers can uncover the underlying cause behind an issue.

Imagine a server crash in a data centre. The 5 Whys process might look like this:

  1. Why did the server crash? Because it overheated.
  2. Why did it overheat? Because the cooling system failed.
  3. Why did the cooling system fail? Because the coolant was not circulating.
  4. Why was the coolant not circulating? Because the pump was broken.
  5. Why was the pump broken? Because it was not maintained as per the recommended schedule.

Through this process, we learn that the root cause of the server crash was inadequate maintenance, not merely a random hardware failure.

Root Cause Analysis (RCA)

Root cause analysis (RCA) is a systematic process for identifying the underlying causes of faults or problems. RCA aims to prevent the same problems from recurring by eliminating the root cause rather than treating the symptoms.

For example, suppose a manufacturing assembly line is regularly shutting down due to equipment failure. Rather than just fixing or replacing the equipment each time, an RCA might uncover that a specific part is consistently under high stress due to improper alignment, causing it to fail. By correcting this alignment, the systems engineer can prevent the problem from recurring.

Fault Tree Analysis (FTA)

Fault Tree Analysis (FTA) is a top-down, deductive analysis method used to explore the many different causes of a specific failure or undesirable outcome. It graphically represents the logical relationships between subsystem failures, potential human errors, and external events in the form of a tree.

Suppose a software system suffers from frequent downtime. The FTA would start with the undesired event at the top (downtime), and then branch out into various potential causes such as software bugs, hardware failure, network issues, and so on. Each of these branches can then be subdivided further into more specific faults, allowing the engineer to understand all potential causes of the problem and prioritise the most likely or serious ones for remediation.

Simulation Modelling

Simulation modelling is a powerful tool that allows systems engineers to predict the behaviour of a system under different conditions. By creating a digital twin of a real-world system, engineers can understand the system's response to changes in variables, identify potential issues, and test solutions.

For instance, in a complex logistics operation, a simulation model can be used to understand the impact of adding a new product line or increasing order volume. This could reveal potential bottlenecks or inefficiencies, allowing proactive adjustments to be made before they become real-world problems.

Creative Problem-Solving Techniques

Beyond the analytical and systematic problem-solving techniques traditionally used in engineering, there are numerous creative methods that can be applied. These techniques stimulate lateral thinking, enabling you to view problems from a fresh perspective and identify innovative solutions. Here are a few examples:


Brainstorming is perhaps one of the most commonly used creative problem-solving techniques. It involves gathering a group of people and encouraging them to freely share their thoughts and ideas related to a specific problem. The key is to refrain from any judgment or criticism during the brainstorming process to encourage free thought and out-of-the-box ideas.


SCAMPER is a creative-thinking technique that uses seven types of transformations: Substitute, Combine, Adapt, Modify, Put to another use, Eliminate, and Reverse. By examining a problem through these different lenses, you can generate novel solutions. For example, if you're trying to enhance the efficiency of a manufacturing process, you might "Adapt" a method from a completely different industry or "Combine" two existing processes into one.

Mind Mapping

Mind Mapping is a visual tool that helps structure information, enabling you to better analyse, comprehend, and generate new ideas. Starting with a central concept, you add nodes branching out into related subtopics. This can reveal unexpected connections and encourage creative problem-solving.

Six Thinking Hats

This technique, devised by Edward de Bono, involves viewing a problem from six distinct perspectives, symbolised by hats of different colours. The white hat considers facts and information, the red hat looks at the issue emotionally, the black hat uses caution and considers risks, the yellow hat optimistically thinks about benefits, the green hat encourages creativity, and the blue hat manages the process and oversees the big picture.

Analogy Thinking

Analogy thinking, or analogous thinking, is a method of comparing the problem at hand to other similar situations or phenomena. By drawing parallels, you might find creative solutions that you would not have considered otherwise. For example, an engineer might draw inspiration from the natural world, such as how a bird flies or a tree distributes nutrients, to solve a complex mechanical or systems problem.


In conclusion, problem-solving in systems engineering represents a harmonious blend of art and science. It's not about completely discarding systematic, logical techniques, but instead complementing them with creative strategies. This combination of traditional and creative methods equips systems engineers with the tools to predict, identify, and address issues effectively and efficiently. By fostering a balance between analytical and innovative thinking, fresh insights can be gained and novel solutions developed. This fusion is often where the most impactful solutions are found. As these techniques are regularly practiced and mastered, they can lead to smoother operations, reduced downtime, and ultimately more successful projects. The artistry lies in the creativity, and the science in the application and understanding of these tools, culminating in an exciting, evolving, and rewarding field.

This content was generated using OpenAI's GPT Large Language Model (with some human curation!). Check out the post "Explain it like I'm 5: What is ChatGPT?" to learn more.