System Adaptability

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Lead Authors: Haifeng Zhu and Eileen Arnold

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Need introductory text.

Overview

Dictionary Definition

The term adapt means “to make fit (as for a new use) often by modification” (Merriam-Webster, Inc.). The term adaptation is traditionally used in natural ecosystems as “modification of an organism or its parts that makes it more fit for existence under the conditions of its environment” where the conditions can be either positive or negative (Andersen & Gronau, 2005).

Systems Engineering Meaning

[Art: A Google Search for "Systems Engineering Meaning" will pull this up - suggest perhaps rewording. Maybe "Adaptability in Systems Engineering"]

Following the dictionary definition, System Adaptability is a system’s ability to satisfy mission and requirement changes, with or without modifications (Zhu, 2015) (Jackson, 2016) (Zhu, et al., 2016). A system is more adaptable if it supports mission and requirement changes at less cost which is an indication how difficult a system is to adapt.

The adaptability concept is applicable to both real and conceptual systems as defined in (Sillitto, Hillary, et al. , 2017).

There are concepts that are related to system adaptability such as system resilience, flexible design, and design reuse. System resilience has traditionally focused on graceful degradation and recovery of a system's performance, triggered by adverse events and planned for in advance. System adaptability focuses on solutions for changes caused by either adversarial or beneficial events. Flexible design in industrial engineering (Saleh, Mark, & Jord, 2009) often requires up-front investment and justification of redundant designs or facilities, with more than 50 kinds of flexibilities defined and studied. System adaptability looks into future changes to inform the current design choices for reduction of unnecessarily redundant designs. System adaptability encourages reuse, but does not promote it at the expense of higher cost.

Three Fundamental Factors

To compare the adaptabilities among different systems, Mission and Requirement Evaluation Space (MRES), Design Space and Switching Cost are the three minimum factors needed.

Mission and Requirement Evaluation Space (MRES)

Current practices assume each requirement is for current needs and is often subject to budget constraint perceptions. MRES differs in that it uses systems thinking to project to the future, and identifies requirements with high risk of change. These uncertain requirements may come from stakeholder’s decisions, market changes, technology progresses and engineering uncertainties, etc. (Zhu, 2023) which are optional potential needs. MRES is a collection of current needs (i.e. requirements and missions) and optional potential needs, that can be distinguished with a “required/optional” attribute as an example. These projections into the future provide valuable information to the current design for adaptability.

Design Space

To have a comparison function defined, one needs to have at least two systems. A collection of different systems being designed is called Design Space (or Trade Space) in which Tradeoff Studies (or Trade Studies) (Cilli & Parnell, 2014) (NASA, 2016) are performed to select a design, based on a set of decision factors, one of which can be the systems’ adaptabilities.

Switching Cost

If the adaptation needs modifications, the ease of modifications indicates the degree of adaptability. The cost of switching from one system design/state to another design/state is called Switching Cost which is a good indicator of how difficult it is to adapt.

Note that the cost here may not necessarily be a financial cost, and can be time, fuel, complexity as adopted in (Zhu, et al., 2016) or any metric that the designers and/or users are concerned about with regard to the difficulty of modifications. Traditional financial cost estimation assumes a system is developed from scratch, which in reality is rarely exercised. Many products are developed by modifying designs from prior products, where the cost is actually a switching cost. Methods of estimating the switching cost for a complete generic system, rather than individual components or systems of a specific kind, were initiated mainly by two research teams: a process-based method was developed and later reported in (Zhu, 2018) and a parametric approach was developed in COSYSMO (Alstad, 2019).

Summary

MRES, Design Space and Switching Cost are three factors that are highly recommended when comparing adaptable systems, based on the development history of system adaptability.

Development History

There are two other major prior works on system adaptability, by (Gu, Hashemian, & Nee, 2004) and (Ross, Rhodes, & Hastings, 2007). (Gu, Hashemian, & Nee, 2004) defines adaptability as a normalized saving in switching from one product to another, emphasizing the costs as the main considerations. In (Ross, Rhodes, & Hastings, 2007), for a design A and another design B, if A can be modified to become B, a link is created between A and B. They define the adaptability of a design as the outdegree or filtered outdegree from that design. A design’s outdegree counts the links from this design to the other designs. In a design space, some designs support the mission better than others. Without considering the support to missions or requirements, measuring the cost to switch to another design (Gu, Hashemian, & Nee, 2004) or how many other designs one design can switch to (Ross, Rhodes, & Hastings, 2007) can result in inverted measures, where an entity that would receive a higher value of the measurement result than another entity receives with a lower value result. A design that is able to switch with low cost to many other designs that are of no or low value for missions may receive a higher adaptability score than another design that actually supports the needed missions.

Fundamentally, these two works capture only two of the three fundamental factors described in Section 1.3 without the MRES factor, which is needed to prevent inverted measures.

In an eco-system, a species adapts in order to survive and exist longer. In systems engineering, being able to support future missions/requirement needs prolongs the service life of the system and extends its existence, which is well aligned with the eco-system definition of adaptability.

There are domain-specific definitions of adaptability and switching costs in IT, control and self-adaptive systems areas. For details, please refer to the “Related Areas” section in (Zhu, et al., 2016).

Demonstrating Adaptability: An Aerospace Example

In the following example, a high-level abstraction of an aircraft engine is used to illustrate how to evaluate the adaptability of system designs (Zhu, et al., 2016) using MRES, Design Space and Switching Costs.

MRES

Capturing the flight missions for our engine example is the first step. The following operations set the stage for our key mission requirements:

1. One engine inoperative
2. Takeoff Gradient of Climb
3. Climb Rate
4. Cruise Range

Three typical types of aircraft are used in commercial airline operations:

• a city-to-city short range aircraft,
• a regional jet and
• a transatlantic jet.

One engine inoperative support is required per aviation regulations. In addition, Takeoff Gradient of Climb, Climb Rates, and Cruise Range are as indicated in Table 1.