How can you optimize and test systems for robustness?

Systems engineering is a discipline that deals with the design, integration, and management of complex systems. One of the main goals of systems engineering is to ensure that the systems are robust, meaning that they can perform well under various conditions and uncertainties. But how can you optimize and test systems for robustness? In this article, we will explore some of the methods and tools that can help you achieve this objective.

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1 Define system requirements and objectives

The first step in optimizing and testing systems for robustness is to define the system requirements and objectives clearly and explicitly. These should include the functional, performance, reliability, safety, and environmental aspects of the system, as well as the constraints and trade-offs involved. The system requirements and objectives should also reflect the needs and expectations of the stakeholders, such as the customers, users, regulators, and operators.

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Sarah Brougham

Safety & Reliability Engineer at Safran
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An example of this is considering a wide range of users. People maintaining and people operating the system day to day are both users of your system and it is important to consider all perspectives. This helps find potential gaps in your system requirements.

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2 Identify sources of uncertainty and variability

The next step is to identify the sources of uncertainty and variability that can affect the system performance and behavior. These can include internal factors, such as component failures, human errors, or software bugs, or external factors, such as environmental changes, user inputs, or disturbances. The sources of uncertainty and variability should be characterized and quantified using appropriate methods, such as statistical analysis, modeling, or simulation.

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3 Design system architecture and components

The third step is to design the system architecture and components that can meet the system requirements and objectives while being robust to the sources of uncertainty and variability. This involves selecting the best combination of system elements, such as hardware, software, data, interfaces, and processes, that can work together to achieve the desired system functions and properties. The design process should also consider the system life cycle, such as the development, operation, maintenance, and disposal stages.

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Sarah Brougham

Safety & Reliability Engineer at Safran
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It should also consider use cases for how the system might be used during those different lifecycle phase. For example if your system will need to be repaired during a maintenance phase, have we considered how a technician might be able to repair it? What do they need to access, how easily do components need to be removed and what time frames might they be working to?

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4 Apply optimization techniques and tools

The fourth step is to apply optimization techniques and tools that can help you find the optimal or near-optimal solutions for the system design. Optimization techniques and tools are methods that can help you maximize or minimize a certain objective function, such as cost, performance, or reliability, subject to certain constraints, such as resources, time, or quality. Some examples of optimization techniques and tools are linear programming, nonlinear programming, genetic algorithms, or neural networks.

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5 Conduct robustness analysis and testing

The fifth step is to conduct robustness analysis and testing that can help you evaluate and verify the system performance and behavior under various conditions and uncertainties. Robustness analysis and testing are methods that can help you measure and improve the system's ability to withstand or adapt to changes or disturbances without compromising its functionality or quality. Some examples of robustness analysis and testing are sensitivity analysis, Monte Carlo simulation, fault tree analysis, or failure mode and effects analysis.

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6 Implement feedback and improvement mechanisms

The sixth and final step is to implement feedback and improvement mechanisms that can help you monitor and update the system performance and behavior over time. Feedback and improvement mechanisms are methods that can help you collect and analyze data from the system operation and use, identify and correct errors or deviations, and implement changes or enhancements to the system design or configuration. Some examples of feedback and improvement mechanisms are control systems, data analytics, or agile methods.

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7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?

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Sarah Brougham

Safety & Reliability Engineer at Safran
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Considering the use of methodologies like Model Based Systems Engineering (MBSE) can help your system be more adaptable and ensure your changes flow through the system. This can make it easier to flow new knowledge through the system as it arises.

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How can you optimize and test systems for robustness?

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1 Define system requirements and objectives

2 Identify sources of uncertainty and variability

3 Design system architecture and components

4 Apply optimization techniques and tools

5 Conduct robustness analysis and testing

6 Implement feedback and improvement mechanisms

7 Here’s what else to consider

Systems Engineering

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How can you optimize and test systems for robustness?

1

2

3

4

5

6

7

1 Define system requirements and objectives

2 Identify sources of uncertainty and variability

3 Design system architecture and components

4 Apply optimization techniques and tools

5 Conduct robustness analysis and testing

6 Implement feedback and improvement mechanisms

7 Here’s what else to consider

Systems Engineering

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