Engineering Systems Integration, Testing, and Validation

Developing and implementing interventions in engineering systems must undergo rigorous testing before being deployed into their operational environment. An engineering system’s complexity determines the sophistication of the testing needed to demonstrate its ability to meet intended objectives. In this chapter, we explore the various testing methodologies that shed light on the behaviour of a system. This section introduces the reader to the general role of life cycle cost of systems in testing, including reference engineering systems that can leverage such a testing approach. Within section “Engineering Systems Considerations and Interventions”, the implications of various types of system complexity are presented along with the implications that tight and loose coupling can have on systems. This section includes an example taken from the International Space Station that illustrates various considerations involved with testing engineering systems. Section “Testing Methodologies” discusses the finer details of systems testing by presenting current challenges for testing engineering systems, suitable testing approaches, and the roll of test planning (design of experiments) in engineering systems development. Section “Developments in Testing” of this chapter presents an example of a drone delivery system that leverages a decision support system to help optimise test strategies in situations where the system is too complex to test manually, and trade-offs must be made between test coverage, cost, and delivery time. At the heart of the methodology presented in this section is an algorithm that can help lead to smarter testing decisions through the prioritisation and sequencing of tests. This is accomplished by integrating a parametric cost model, knowledge gradient algorithm, and Bayesian updating algorithm. The chapter aims to support systems engineers coordinate and plan tests that help decision-makers learn as much about a system as quickly as possible while gaining confidence that the system is ready for deployment.