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1 Introduction Advances in the capabilities of technologies applicable to distributed networking, telecommunications, multi-user computer applications, and interactive virtual reality are creating opportunities for users in the same or separate locations to engage in interdependent, cooperative activities using a common computer-based environment. These capabilities have given rise to relatively new interdisciplinary efforts to unite the interests of mission-oriented communities with those of the computer and social science communities to create integrated, tool-oriented computation and communication systems. Whether they are called "collaboratories," "computer-supported cooperative work" (CSCW) technologies, "coordination technologies," "groupware,'' and "advanced engineering environments" (AEEs), all of these technologies and systems facilitate the sharing of data, software, instruments, and communication devices with remote colleagues. They attempt to create an environment in which all resources are virtually local regardless of the user's physical location. Thus, research and development (R&D) on these technologies must pay explicit attention to the participants' organizational and social contexts by taking into account situations, roles, social interactions, and task interdependencies among participants, as well as functional requirements in system design, development, implementation, and evaluation. For most engineering tasks, collaborations currently rely heavily on face-to-face interactions, group meetings, individual actions, and hands-on experimentation—with groups ranging from gatherings of a few people to several hundred members of large project teams. Through a shared electronic infrastructure, computer and telecommunication systems enable teams in widespread locations to collaborate using the newest instruments and computing resources. The benefits of such collaborations and systems are many. For example, a new paradigm for intimate collaboration between scientists and engineers is emerging that could accelerate the development and dissemination of knowledge and optimize the use of instruments and facilities, while minimizing the time between the discovery and application of knowledge. Defining an Advanced Engineering Environment Discussions about AEEs often focus on their potential for eliminating barriers to innovation; for providing seamless design, engineering, and manufacturing capabilities; and for assessing product reliability, life-cycle costs, and supportability quickly and accurately. To understand the long-term potential of AEEs, they must first be defined. As treated in this report, AEEs (i.e., AEE systems) are defined as particular implementations of computational and communications systems that create integrated virtual and/or distributed environments1 linking researchers, technologists, designers, manufacturers, suppliers, and customers involved in mission-oriented, leading-edge engineering teams in industry, government, and academia. AEE systems will incorporate a variety of software tools and other technologies for modeling, simulation, analysis, and communications. Some of the tools and other technologies needed to create AEE systems are already being used in operational engineering environments and processes. The current challenge is to develop new and improved technologies and to integrate them effectively with currently available technologies to create comprehensive, interoperable AEE systems, as described in the vision that appears below. The committee's definition of an AEE is discussed in the following sections, which describe the committee's long-term vision for AEEs; a vignette of an ideal AEE; and the objectives, components, and characteristics of AEEs. These 1 Virtual environments are defined as "an appropriately programmed computer that generates or synthesizes virtual worlds with which the operator can interact" (NRC, 1995). "Distributed environments" refer to nonvirtual, collaborative computing systems.
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topics are discussed in more detail in the remainder of the report. Vision The committee collected information about the current state and future utility of AEEs from governmental, industrial, and academic organizations involved in AEEs either as developers, providers, or users of technologies or services (see Appendix C). Based on that information, the committee defined the following vision: AEEs should create an environment that allows organizations to introduce innovation and manage complexity with unprecedented effectiveness in terms of time, cost, and labor throughout the life cycle of products and missions. Vignette: The Ideal AEE One way to explain the ultimate goals and benefits of developing AEEs is through a top-level description of an ideal AEE, which would encompass concept definition, design, manufacturing, production, and analyses of reliability, performance, and cost over the entire life cycle in a seamless blend of disciplinary functions and activities. The ideal AEE would ease the implementation of innovative concepts and solutions while readily drawing on legacy data, tools, and capabilities. Interoperability between data sets and tools would be routine and would not require burdensome software development. The ideal AEE would accommodate diverse user groups and facilitate their collaboration in a manner that eliminates cultural barriers. It would be marked by functional flexibility that would allow rapid reorientation and reorganization of its capabilities at little or no cost. The AEE would include a high-speed communications network to enable rapid, high-fidelity evaluations of concepts and approaches across engineering, manufacturing, production, reliability, and cost parameters. It would be amenable to hardware and software enhancements in a transparent way. Unfortunately, an ideal AEE is not presently achievable at the enterprise level. Integrating "all" of an enterprise's data and analysis capabilities is impossible because no widely accepted standards have been established. Other, more subtle issues, such as cultural resistance and the difficulty of credibly demonstrating benefits, must also be addressed. An ideal AEE would span all of an enterprise's operations, and in a traditional organization rarely is anyone with sufficient authority and responsibility designated to implement an AEE. Despite these difficulties, the committee believes that useful elements of AEE systems can be developed in the near term to demonstrate some of the capabilities of the ideal system. This would require an organizational "center of gravity" empowered to identify analyses and data sets where interoperability is most important, designate specific tools as enterprise standards without having to achieve internal consensus, and support the ongoing process as needs and available technologies and software change. With this kind of leadership, a good deal of the promise of AEEs could be realized. Objectives To determine the requirements for realizing the vision, the committee defined two key objectives that AEEs should satisfy: Enable complex new systems, products, and missions. Greatly reduce product development cycle time and costs. In addition, AEE technology and system developers should devise a comprehensive, multifaceted implementation process that meets the following objectives: Lower technical, cultural, and educational barriers. Apply AEEs broadly across U.S. government, industry, and academia.2 Components After defining the AEE vision and objectives, the committee identified three key components of an AEE: computation, modeling, and software; human-centered computing; and hardware and networks. These elements will interact dynamically to reflect the current state of engineering practice, available technology, and cultural developments. Effective AEEs must be oriented toward users who will have a wide range of needs and abilities. Therefore AEEs must be modular in nature, dynamic in an evolutionary sense, and open to users with broad cultural and social differences. A critical, yet sometimes under-appreciated, aspect of AEEs is the social and psychosocial dynamics of organizations. Characteristics The committee identified specific characteristics that represent users' needs for each component of an AEE that meets the objectives described above. The most important characteristics for each component are listed in Table 1-1. The committee strongly believes that AEEs should fulfill both operational and research functions. Although these functions are often very different, most technology industries require high-fidelity tools for both types of activities, and addressing both functions concurrently will help reduce cycle time from research to development. 2 The objectives are discussed in more detail in Chapter 3.
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Table 1-1 AEE System Components and Characteristics Computation, Modeling, and Software • multidisciplinary analysis and optimization • interoperability of tools, data, and models • system analysis and synthesis • collaborative, distributed systems • software structures that can be easily reconfigured • deterministic and nondeterministic simulation methods Human-Centered Computing • human-adaptive interfaces • virtual environments • immersive systems • telepresence • intelligence augmentation Hardware and Networks • ultrafast computing systems • large high-speed storage devices • high-speed and intelligent networks Study Overview The Statement of Task for this study requires the committee to conduct a two-phase assessment of existing and planned methods, architectures, tools, and capabilities associated with the development of AEE technologies and systems and their transition into practice by the current and future workforce. This report documents the results of Phase 1. Focusing on the near term (the next 5 years), Phase 1 examined potential applications of AEEs; explored the potential payoffs of AEEs on a national scale; evaluated how AEEs relate to the development of relevant technical standards and analyses of cost and risk; identified technical, cultural, and educational barriers to the implementation of AEEs, opportunities that could be created by AEEs, and needs for education and training; and recommended an approach for the National Aeronautics and Space Administration (NASA) to enhance the development of AEE technologies and systems with broad application in industry, government, and academia. Expanding on the results of Phase 1, Phase 2 will focus on the potential and feasibility of developing AEE technologies and systems over the long term (the next 5 to 15 years). Specific tasks will include evaluating the potential for AEEs to contribute to NASA's long-term goal of revolutionizing the engineering culture; assessing potential long-term payoffs of AEEs on a national scale; examining broad issues, such as infrastructure changes, interdisciplinary communications, and technology transfer; describing approaches for achieving the AEE vision, including the potential roles of government, industry, academic, and professional organizations in resolving key issues; and identifying key elements of a long-term educational and training strategy to encourage the acceptance and application of AEEs by existing and future workforces. (The complete Statement of Task for this two-phase study appears in Appendix A.) Organization of the Report Subsequent chapters illustrate the current state of the art in AEE technologies and systems (Chapter 2), describe AEE requirements and alternatives for meeting those requirements (Chapter 3), discuss barriers to the implementation of AEEs (Chapter 4), and summarize near-term actions that should be taken to pursue the AEE vision (Chapter 5). In keeping with the Statement of Task, many sections of the report place special emphasis on aerospace engineering and NASA. However, many of the challenges associated with AEEs are shared by other organizations within the federal government, private industry, and academia. Therefore, many of the findings and recommendations are applicable to all organizations engaged in developing and applying AEE technologies. Reference NRC (National Research Council). 1995. Virtual Reality: Scientific and Technical Challenges. Committee on Virtual Reality Research and Development. Washington, D.C.: National Academy Press.
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