The primary purpose of SE is to ensure that all components of a system work together effectively to meet objectives within budget and schedule constraints.

An interfacing system is any external system that shares an interface with the SoI (e.g., physical, data, energy). An interoperating system is a specific type of interfacing system that interacts with the SoI in its operational environment to perform a shared function, supporting the SoI’s primary purpose.

Emergent behavior refers to system behavior that cannot be solely predicted or understood by analyzing individual system elements. It arises from the complex interactions between elements and their relationships, often leading to unexpected or unpredictable outcomes at the system level.

The rapid acceleration of design-to-market life cycles has pushed SE methods and tools to become more adaptable and efficient. This has led to the adoption of agile methods, model-based systems engineering (MBSE), and digital engineering (DE) approaches to manage complexity and streamline development processes.

Considering enabling systems during the SoI lifecycle is crucial because these external systems provide vital services for development, production, and operation. Overlooking their availability or potential delays can result in significant cost increases, schedule slips, and even project failure.

A system boundary is a conceptual line that separates the System of Interest (SoI) from its surrounding environment or context. It defines what elements belong to the system and what lies outside its scope, clarifying the system’s interactions and responsibilities.

Uncertainty in SE refers to the lack of complete knowledge about various factors such as future demand, technology performance, or stakeholder preferences. Unmanaged uncertainty translates into risk, which represents the possibility of negative consequences or deviations from desired outcomes due to these unknowns.

A cognitive bias is a systematic error in thinking that arises from our brain’s tendency to simplify information processing. These biases can influence decision-making by leading to flawed judgments, inaccurate risk assessments, and an overreliance on intuition over data.

A “state” represents a specific condition or configuration of a system at a given point in time, defined by a set of observable variables. A “mode” describes a distinct operating capability of the system, potentially involving a subset of system functions being performed at varying levels of capacity.

One example of an SE heuristic is, “Don’t assume the original problem statement is necessarily the best, or even the right one.” This highlights the importance of critically