Abstract
Our modern life has grown to depend on many and nearly ubiquitous large complex engineering systems. Transportation, water distribution, electric power, natural gas, healthcare, manufacturing, and food supply are but a few. These engineering systems are characterized by an intricate web of interactions within themselves but also between each other. Furthermore, they have a long-standing nature that means that any change requires an intervention into a legacy system rather than a new “blank-slate” system design. The interventions themselves are often costly with implications lasting many decades into the future. Consequently, when it comes to engineering system interventions, there is a real need to “get it right.” This chapter discusses two types of engineering system interventions, namely, those that change system behavior and those that change system structure. It then discusses the types of measurement that can be applied to evaluating such interventions. More specifically, it contrasts experimental, data-driven, and model-based approaches. It recognizes that only the last of these is appropriate for interventions that change system structure. Consequently, the chapter concludes with a taxonomy of engineering system models including graphical models, quantitative structural models, and quantitative behavioral models. The chapter concludes with a discussion of promising avenues for future research in the area, namely, hetero-functional graph theory and hybrid dynamic systems.
Original language | English |
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Title of host publication | Handbook of Engineering Systems Design |
Subtitle of host publication | With 178 Figures and 54 Tables |
Pages | 709-733 |
Number of pages | 25 |
ISBN (Electronic) | 9783030811594 |
DOIs | |
State | Published - 1 Jan 2022 |
Keywords
- Engineering systems
- Evaluation
- Interventions
- Life cycle properties
- Measures