The large number of government and industry activities supporting the Unit of Action (UA), with attendant documents, reports and briefings, can overwhelm decision-makers with an overabundance of information that hampers the ability to make quick decisions often resulting in a form of gridlock. In particular, the large and rapidly increasing amounts of data and data formats stored on UA Advanced Collaborative Environment (ACE) servers has led to the realization that it has become impractical and even impossible to perform manual analysis leading to timely decisions. UA Program Management (PM UA) has recognized the need to implement a Decision Support System (DSS) on UA ACE. The objective of this document is to research the commercial Knowledge Discovery and Data Mining (KDDM) market and publish the results in a survey. Furthermore, a ranking mechanism based on UA ACE-specific criteria has been developed and applied to a representative set of commercially available KDDM solutions. In addition, an overview of four R&D areas identified as critical to the implementation of DSS on ACE is provided. Finally, a comprehensive database containing detailed information on surveyed KDDM tools has been developed and is available upon customer request.
At the direction of the Department of Defense Explosives Safety Board (DDESB), a Peer Review Team was established to review the status of development of the risk-based explosives safety siting process and criteria as currently implemented in the software 'Safety Assessment for Explosive Risk (SAFER)' Version 2.1. The objective of the Peer Review Team was to provide an independent evaluation of the components of the SAFER model, the ongoing development of the model and the risk assessment process and criteria. This peer review report addressed procedures; protocols; physical and statistical science algorithms; related documents; and software quality assurance, validation and verification. Overall, the risk-based method in SAFER represents a major improvement in the Department of Defense (DoD) approach to explosives safety management. The DDESB and Risk Based Explosives Safety Criteria Team (RBESCT) have made major strides in developing a methodology, which over time may become a worldwide model. The current status of all key areas of the SAFER code has been logically developed and is defensible. Continued improvement and refinement can be expected as implementation proceeds. A consistent approach to addressing and refining uncertainty in each of the primary areas (probability of event, consequences of event and exposure) will be a very beneficial future activity.
The US Department of Energy (DOE) created the Nuclear Energy Research Initiative (NERI) in 1999 to conduct research and development with the objectives of: (1) overcoming the principal technical obstacles to expanded nuclear energy use, (2) advancing the state of nuclear technology to maintain its competitive position in domestic and world markets, and (3) improving the performance, efficiency, reliability, and economics of nuclear energy. The NERI program is now beginning its second year with increased funding and an emphasis on international participation. Among the programs selected for funding was the ``Smart Equipment and Systems to Improve Reliability and Safety in Future Nuclear Power Plant Operations''. This program is a 36 month collaborative effort bringing together the technical capabilities of Westinghouse Nuclear Automation, Sandia National Laboratories, Duke Engineering and Services (DE and S), Massachusetts Institute of Technology (MIT) and Pennsylvania State University (PSU). The goal of the program is to design, develop, and evaluate an integrated set of tools and methodologies that can improve the reliability and safety of advanced nuclear power plants through the introduction of smart equipment and predictive maintenance technology. The results have implications for reduced construction costs. This paper discusses: (1) the goals and significance of the program, (2) the significant achievements of the program's first year and the current direction for its continuing efforts and (3) potential cooperation with the domestic nuclear and component manufacturing industries, and with international organizations.
The United States Department of Energy initiated the Nuclear Energy Research Initiative (NERI) to conduct research and development with the objectives of: (1) overcoming the principal technical obstacles to expanded nuclear energy use, (2) advancing the state of nuclear technology to maintain its competitive position in domestic and world markets, and (3) improving the performance, efficiency, reliability, and economics of nuclear energy. Fiscal Year 1999 program funding is $19 Million, with increased finding expected for subsequent years, emphasizing international cooperation. Among the programs selected for funding is the ``Smart Equipment and Systems to Improve Reliability and Safety in Future Nuclear Power Plant Operations''. This program is a 30 month collaborative effort bringing together the technical capabilities of ABB C-E Nuclear Power, Inc. (ABB CENP), Sandia National Laboratories, Duke Engineering and Services (DE and S), Massachusetts Institute of Technology (MIT) and Pennsylvania State University (PSU). The program's goal is to design, develop and evaluate an integrated set of smart equipment and predictive maintenance tools and methodologies that will significantly reduce nuclear plant construction, operation and maintenance costs. To accomplish this goal the Smart Equipment program will: (1) Identify and prioritize nuclear plant equipment that would most likely benefit from adding smart features; (2) Develop a methodology for systematically monitoring the health of individual pieces of equipment implemented with smart features (i.e. smart equipment); (3) Develop a methodology to provide plant operators with real-time information through smart equipment Man-Machine Interfaces (MMI) to support their decision making; (4) Demonstrate the methodology on a targeted component and/or system; (5) Expand the concept to system and plant levels that allow communication and integration of data among smart equipment. This paper will discuss (1) detailed subtask plans for the entire program, including expected achievements, (2) preliminary results from the early program phases and (3) the program's relationship to other NERI programs being conducted by the same team.
The Demand Activated Manufacturing Architecture (DAMA) project during the last five years of work with the U.S. Integrated Textile Complex (retail, apparel, textile, and fiber sectors) has developed an inter-enterprise supply chain collaboration development methodology. The goal of this methodology is to enable a supply chain to work more efficiently and competitively. The outcomes of this methodology include: (1) A definitive description and evaluation of the role of business cultures and supporting business organizational structures in either inhibiting or fostering change to a more competitive supply chain; (2) ``As-Is'' and proposed ``To-Be'' supply chain business process models focusing on information flows and decision-making; and (3) Software tools that enable and support a transition to a more competitive supply chain, which results form a business driven rather than technologically driven approach to software design. This methodology development will continue in FY00 as DAMA engages companies in the soft goods industry in supply chain research and implementation of supply chain collaboration.
The Demand Activated Manufacturing Architecture (DAMA) project during the last five years of work with the U.S. Integrated Textile Complex (retail, apparel, textile, and fiber sectors) has developed an inter-enterprise architecture and collaborative model for supply chains. This model will enable improved collaborative business across any supply chain. The DAMA Model for Supply Chain Collaboration is a high-level model for collaboration to achieve Demand Activated Manufacturing. The five major elements of the architecture to support collaboration are (1) activity or process, (2) information, (3) application, (4) data, and (5) infrastructure. These five elements are tied to the application of the DAMA architecture to three phases of collaboration - prepare, pilot, and scale. There are six collaborative activities that may be employed in this model: (1) Develop Business Planning Agreements, (2) Define Products, (3) Forecast and Plan Capacity Commitments, (4) Schedule Product and Product Delivery, (5) Expedite Production and Delivery Exceptions, and (6) Populate Supply Chain Utility. The Supply Chain Utility is a set of applications implemented to support collaborative product definition, forecast visibility, planning, scheduling, and execution. The DAMA architecture and model will be presented along with the process for implementing this DAMA model.