ESD and Health Care Systems: some strategic considerations

Proper health care delivery to a growing but aging population is becoming one of the most challenging tasks of our time. It becomes also one of the most complex. Although many tools are at hand, grand designs and implementation systems are mostly lacking. In the industrialized countries, requests for optimal medical care and the demographic evolution towards longer life have led to different health care systems but all of them may be characterized as more or less dysfunctional (see below). In many developing countries, the gaps caused by the lack of health care infrastructure and education and by economic backwardness are becoming increasingly apparent. On the other hand, the relatively new approach of engineering for solution and optimization of various complex problems, such as energy, infrastructures, transportation, manufacturing or environmental protection leads us to ask whether the logical and analytical tools developed in complex systems engineering could also be applied to the whole or parts of the health care field. A brief discussion of that issue is the purpose of this memorandum

Isoperformance An Alternative Design Methodology for Engineering Systems

Tradeoffs between performance, cost and risk frequently arise during architecting and design of complex Engineering Systems such as aerospace vehicles. A paradigm shift is occurring from the pure performance optimization approach of the past towards satisfying of performance targets under concurrent risk and cost minimization. This paper proposes “isoperformance” as a set based approach to designing engineering systems by first identifying the acceptable performance invariant set of designs from which a final design is chosen. This is in contrast to a multiobjective cost-risk minimization under performance equality constraints. This paper identifies a number of issues associated with finding the desired performance invariant set, I, given a deterministic or empirical system model that maps design variables x to objective variables J. Isoperformance is presented as a methodology that can quantify and visualize the tradeoffs between determinants (independent design variables) of a known or desired outcome. For deterministic systems the multivariable performance invariant contours can be computed using sensitivity analysis and a contour following algorithm, provided that a mathematical system model of appropriate fidelity exists. In the case of stochastic systems the isoperformance curves can be obtained via a regression analysis, given a statistically representative data set. Once isoperformance curves have been obtained, they are useful in extracting a set of performance invariant solutions. Applying additional objectives, other than performance, can then lead to a set of pareto-optimal designs. Specific examples from opto-mechanical space systems design and human factors are presented

Method and apparatus for determining and utilizing a time-expanded decision network

A method, apparatus and computer program for determining and utilizing a time-expanded decision network is presented. A set of potential system configurations is defined. Next, switching costs are quantified to create a "static network" that captures the difficulty of switching among these configurations. A time-expanded decision network is provided by expanding the static network in time, including chance and decision nodes. Minimum cost paths through the network are evaluated under plausible operating scenarios. The set of initial design configurations are iteratively modified to exploit high-leverage switches and the process is repeated to convergence. Time-expanded decision networks are applicable, but not limited to, the design of systems, products, services and contracts

Quantifying End-Use Energy Intensity of the Urban Water Cycle

The water end-use segment (WES), consisting of activities that utilize water in homes and buildings, has been identified as a major component of energy use in the urban water supply system. In this paper, an analytical framework is presented which can be used at the planning stages of new urban developments to assess future building-level water demands and associated energy requirements. The framework is applied to Masdar City, a new urban area in the United Arab Emirates, which has been targeted in its design to be a future zero-carbon and zero-waste city. Results show that the energy intensity (in electric kWh) in WES for Masdar City may range from 2.6 to 4 kWh=m3. The dominant use of energy in this segment is attributed to water heating requirements, and the total energy use for obtaining hot water is estimated to range from approximately 20 to 50 million kWh annually. It is found that the residential sector in the city can have the greatest impact in affecting energy requirements associated with water use. For every unit reduction (in L=person=day) of indoor residential water use, it is estimated that up to 225 MWh may be saved annually

A Classification of Uncertainty for Early Product and System Design

Complex systems and products evolve over years to meet new requirements, while applying tried and tested technology. To maximise the reuse of components through the life span, companies need to plan for the changes that they can anticipate, and facilitate accommodation of such changes in the original architecture and design of the system. Methods such as design for flexibility or design for changeability promote incorporation of future uncertain outcomes into system and product design in one way or another. However, the degree to which future product changes can be planned depends on the uncertainties that the system, product or product family is subject to. A deeper understanding of these uncertainties is the focus of this paper. The paper first provides a brief literature survey, and discusses the sources and nature of uncertainty. This is followed by a classification of the types of uncertainties that are often encountered and that should be considered, as well as methods and techniques for modelling these uncertainties for incorporation in system design. The paper also provides examples of uncertainties for a variety of systems and products throughout and concludes with an uncertainty checklist for system architects and product designers

Strategic Engineering Gaming for Improved Design and Interoperation of Infrastructure Systems

Large physical networks of interrelated infrastructure components support modern societies as a collaborative system with significant technical and social complexity. Design and evolution of infrastructure systems seeks to reduce wasted resources and maximize lifecycle value. Interdependencies between constituent systems call for an integrative approach to improve interoperation but many existing techniques rely on centralized development and emphasize technical aspects of design. This paper presents a simulation gaming approach to collaborative infrastructure system design leveraging the technical strengths of simulation models and the social strengths of multi-player engagement in a game execution. In a strategic engineering game, models representing each constituent infrastructure system share a common graph-theoretic modeling framework and are integrated using the HLA-Evolved standard for interoperable federated simulations. A prototype game instantiation based on a space-based resource economy supporting future space exploration is discussed with the objective of identifying how factors of game play influence insights to collaborative system design. Future work seeks to develop, execute, and evaluate the prototype game to further research the use of simulation games in supporting collaborative system design

An integrated modeling framework for infrastructure system-of-systems simulation

Design of future hard infrastructure must consider emergent behaviors from cross-system interdependencies. Understanding these interdependencies is challenging due to high levels of integration in high-performance systems and their operation as a collaborative system-of-systems managed by multiple organizations. Existing modeling frameworks have limitations for strategic planning either because important spatial structure attributes have been abstracted out or behavioral models are oriented to shorter-term analysis with a static network structure. This paper presents a formal modeling framework as a first step to integrating infrastructure system models in a system-of-systems simulation addressing these concerns. First, a graph-theoretic structural framework captures the spatial dimension of physical infrastructure. An element's simulation state includes location, parent, resource contents, and operational state properties. Second, a functional behavioral framework captures the temporal dimension of infrastructure operations at a level suitable for strategic analysis. Resource behaviors determine the flow of resources into or out of nodes and element behaviors modify other state including the network structure. Two application use cases illustrate the usefulness of the modeling framework in varying contexts. The first case applies the framework to future space exploration infrastructure with an emphasis on mobile system elements and discrete resource flows. The second case applies the framework to infrastructure investment in Saudi Arabia with an emphasis on immobile system elements aggregated at the city level and continuous resource flows. Finally, conclusions present future work planned for implementing the framework in a simulation software tool.American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi