Space Station Program Plans
Project and contract management in NASA orbital space station program
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Project and contract management in NASA orbital space station program
To learn how ground-based personnel of a space project plan and organize their work and how such planning and organizing relate to work outcomes, longitudinal study of the management and execution of the Space Lab Mission Development Test 3 (SMD 3) was performed at NASA Ames Research Center. A view of the problems likely to arise in organizations and some methods of coping with these problems are presented as well as the conclusions and recommendations that pertain strictly to SMD 3 management. Emphasis is placed on the broader context of future space facility projects and additional problems that may be anticipated. A model of management that may be used to facilitate problem solving and communication - management by objectives (MBO) is presented. Some problems of communication and emotion management that MBO does not address directly are considered. Models for promoting mature, constructive and satisfying emotional relationships among group members are discussed.
The Space Station Furnace Facility (SSFF) is an advanced facility for materials research in the microgravity environment of the Space Station Freedom and will consist of Core equipment and various sets of Furnace Module (FM) equipment in a three-rack configuration. This Project Implementation Plan (PIP) document was developed to satisfy the requirements of Data Requirement Number 4 for the SSFF study (Phase B). This PIP shall address the planning of the activities required to perform the detailed design and development of the SSFF for the Phase C/D portion of this contract.
Automated Manifest Planner (AMP) computer program applies combination of artificial-intelligence techniques to assist both expert and novice planners, reducing planning time by orders of magnitude. Gives planners flexibility to modify plans and constraints easily, without need for programming expertise. Developed specifically for planning space shuttle missions 5 to 10 years ahead, with modifications, applicable in general to planning other complex projects requiring scheduling of activities depending on other activities and/or timely allocation of resources. Adaptable to variety of complex scheduling problems in manufacturing, transportation, business, architecture, and construction.
The Applied Meteorology Unit (AMU) provides technology transition and technique development to improve operational weather support to the Space Shuttle and the entire American space program. The AMU is funded and managed by NASA and operated by a contractor that provides five meteorologists with a diverse mix of advanced degrees, operational experience, and associated skills including data processing, statistics, and the development of graphical user interfaces. The AMU's primary customers are the U.S. Air Force 45th Weather Squadron at Patrick Air Force Base, the National Weather Service Spaceflight Meteorology Group at NASA Johnson Space Center, and the National Weather Service Melbourne FL Forecast Office. The AMU has transitioned research into operations for nineteen years and worked on a wide range of topics, including new forecasting techniques for lightning probability, synoptic peak winds,.convective winds, and summer severe weather; satellite tools to predict anvil cloud trajectories and evaluate camera line of sight for Space Shuttle launch; optimized radar scan strategies; evaluated and implemented local numerical models; evaluated weather sensors; and many more. The AMU has completed 113 projects with 5 more scheduled to be completed by the end of 2010. During this rich history, the AMU and its customers have learned many lessons on how to effectively transition research into operations. Some of these lessons learned include collocating with the operational customer and periodically visiting geographically separated customers, operator submitted projects, consensus tasking process, use of operator primary advocates for each project, customer AMU liaisons with experience in both operations and research, flexibility in adapting the project plan based on lessons learned during the project, and incorporating training and other transition assistance into the project plans. Operator involvement has been critical to the AMU's remarkable success and many awards from NASA, the National Weather Association, and two citations from the Navy's Center of Excellence for Best Manufacturing Practices. This paper will present the AMU's proven methods and explain how they may be applied by other organizations to effectively transition research into operations.
This report contains instructional guidelines for the resources planning and control of research and development (R&D) projects managed by NASA's Langley Research Center (LaRC). Although written to serve primarily as a practical guide and reference for those LaRC personnel who perform resources planning, analysis, control, and reporting functions, it should also be meaningful to other NASA personnel who are directly or indirectly involved in or affected by these functions, especially project technical managers whose responsibilities include resources management. Certain sections should help Contractor personnel to better understand what resources information must usually be submitted on LaRC projects and what use is made of such information. The Project Manager of a large R&D project typicaly receives support from an Analyst in the area of resources management. The Analyst provides assistance in four functional areas: Planning, Analysis/Control, Administration, and Reporting. Each of these functions are discussed in detail. Examples of techniques used effectively on LaRC projects have been included where applicable. A considerable amount of information has been included on the use of Performance Measurement (Earned Value) Systems for contract cost control and reporting as little information is currently available on this subject in NASA publications.
The Machine Translation Project consists of several components, two of which, the Project Plan and the Requirements Analysis, have already been delivered. The Project Plan details the overall rationale, objectives and time-table for the project as a whole. The Requirements Analysis compares a number of available machine translation systems, their capabilities, possible configurations, and costs. The Alternatives Analysis has resulted in a number of conclusions and recommendations to the NASA STI program concerning the acquisition of specific MT systems and related hardware and software.
Tasks remaining to be completed are summarized for the following major project elements: (1) evaluation of crop yield models; (2) crop yield model research and development; (3) data acquisition processing, and storage; (4) related yield research: defining spectral and/or remote sensing data requirements; developing input for driving and testing crop growth/yield models; real time testing of wheat plant process models) and (5) project management and support.
The applicability of integrated parametric models for the budgeting and management of complex projects is investigated. Methods for building a very flexible, interactive prototype for a project planning system, and software resources available for this purpose, are discussed and evaluated. The prototype is required to be sensitive to changing objectives, changing target dates, changing costs relationships, and changing budget constraints. To achieve the integration of costs and project and task durations, parametric cost functions are defined by a process of trapezoidal segmentation, where the total cost for the project is the sum of the various project cost segments, and each project cost segment is the integral of a linearly segmented cost loading function over a specific interval. The cost can thus be expressed algebraically. The prototype was designed using Lotus-123 as the primary software tool. This prototype implements a methodology for interactive project scheduling that provides a model of a system that meets most of the goals for the first phase of the study and some of the goals for the second phase.
Large projects almost always exceed their budgets. Estimating cost is difficult and estimated costs are usually too low. Three different reasons are suggested: bad luck, overoptimism, and deliberate underestimation. Project management can usually point to project difficulty and complexity, technical uncertainty, stakeholder conflicts, scope changes, unforeseen events, and other not really unpredictable bad luck. Project planning is usually over-optimistic, so the likelihood and impact of bad luck is systematically underestimated. Project plans reflect optimism and hope for success in a supposedly unique new effort rather than rational expectations based on historical data. Past project problems are claimed to be irrelevant because "This time it's different." Some bad luck is inevitable and reasonable optimism is understandable, but deliberate deception must be condemned. In a competitive environment, project planners and advocates often deliberately underestimate costs to help gain project approval and funding. Project benefits, cost savings, and probability of success are exaggerated and key risks ignored. Project advocates have incentives to distort information and conceal difficulties from project approvers. One naively suggested cure is more openness, honesty, and group adherence to shared overall goals. A more realistic alternative is threatening overrun projects with cancellation. Neither approach seems to solve the problem. A better method to avoid the delusions of over-optimism and the deceptions of biased advocacy is to base the project cost estimate on the actual costs of a large group of similar projects. Over optimism and deception can continue beyond the planning phase and into project execution. Hard milestones based on verified tests and demonstrations can provide a reality check.
Orbiting primate spacecraft project planning and documentation on systems design and engineering, experiment design, tests programs, and manufacturing
Contractural requirements, project planning, equipment specifications, and technical data for space shuttle biological experiment payloads are presented. Topics discussed are: (1) urine collection and processing on the space shuttle, (2) space processing of biochemical and biomedical materials, (3) mission simulations, and (4) biomedical equipment.
This paper delves into the details of the Joint Confidence Level (JCL) process performed for the Ice, Cloud, and Land Elevation Satellite (ICESat)-2 mission and how past performance was incorporated into subsequent JCL models to enable the project to continuously analyze potential slips to their launch readiness date (LRD). One year prior to the mission Preliminary Review (mPDR), the JCL model development process began. The first model was well received at the mPDR, held on October 10, 2012, and the input received by the Standing Review Board was incorporated into the model for the official data drop for key decision point (KDP)-C. The 70% JCL results of the October 2012 mPDR model forecast an LRD of February 2017 and associated cost of $830M. This result in 2012 immediately highlighted potential challenges with the project-planned LRD of July 2016. The year following the mPDR, the project had sustained a oneyear slip in the LRD due to problematic systems engineering requirement issues which impacted all project subsystems. This slip moved the project planned LRD from July 2016 to July 2017, an additional 5 months beyond the 2012 model’s 70% JCL result for the LRD of February 2017. As the project was quickly approaching the mission Critical Design Review (mCDR), the need for reliable JCL results increased significantly. The project held discussions on the JCL modeling process and focused on the input uncertainty distributions. Specifically, to identify the uncertainty distributions that the 2012 mPDR model would have needed to produce a 70% LRD result of July 2017. This led the project to compare multiple uncertainty distributions, and ultimately spurred the project to utilize uncertainty distributions that incorporated project past performance and historical data to forecast potential LRD slips. The revised results, created in 2014 and utilizing the new uncertainty distributions, showed that with 70% confidence, the ICESat-2 mission would launch in August 2018 with a cost of $1,044M. Today, ICESat-2 is scheduled to launch on September 15, 2018 with a project management (PM) agreement value of $1,056M. This illustrates how a JCL model can be continuously improved to produce valuable results for a project, even in cases of LRD delays. The primary reason for the ICESat-2 LRD delay is due to a laser failure on the primary instrument. Laser failure was one of the highest risk and uncertainty drivers within the JCL model. The project placed the most risk in this area of the model, and the model further identified the laser as the top risk driver and contributor to the LRD result. This further illustrates how a JCL can be used to predict and quantify possible issues on new technology missions.
In June of 1985 the Project Initiation Agreement was signed by the Jet Propulsion Laboratory and the NASA Office of Space Science and Applications for the Spaceborne Imaging Radar Project (SIR). The thrust of the Spaceborne Imaging Radar Project is to continue the evolution of synthetic aperture radar (SAR) science and technology developed during SEASAT, SIR-A and SIR-B missions to meet the needs of the Earth Observing System (EOS) in the mid 1990's. As originally formulated, the Project plans were for a reflight of the SIR-B in 1987, the development of a new SAR, SIR-C, for missions in mid 1989 and early 1990, and the upgrade of SIR-C to EOS configuration with a qualification flight aboard the shuttle in the 1993 time frame (SIR-D). However, the loss of the shuttle Challenger has delayed the first manifest for SIR to early 1990. This delay prompted the decision to drop SIR-B reflight plans and move ahead with SIR-C to more effectively utilize this first mission opportunity. The planning for this project is discussed.
The considered project is part of the DOE Photovoltaic Technology and Market Development Program. This program is concerned with the development and the utilization of cost-competitive photovoltaic systems. The project has the objective to develop, by 1986, the national capability to manufacture low-cost, long-life photovoltaic arrays at production rates that will realize economies of scale, and at a price of less than $0.70/watt. The array performance objectives include an efficiency greater than 10% and an operating lifetime longer than 20 years. The objective of the silicon material task is to establish the practicality of processes for producing silicon suitable for terrestrial photovoltaic applications at a price of $14/kg. The large-area sheet task is concerned with the development of process technology for sheet formation. Low-cost encapsulation material systems are being developed in connection with the encapsulation task. Another project goal is related to the development of economical process sequences.
NASA uses a structured process for managing projects that develop advanced space technologies and transition them into the designs of flight systems. The four-part process consists of formulation, approval, implementation, and transition. In the formulation phase, technology needs are derived from mission concept studies, various technical approaches for meeting the technology needs are identified, technical performance goals called Key Performance Parameters (KPPs) are established, and a project plan is developed. Prior to project approval, an Independent Formulation Review is conducted to ensure that the project objectives are aligned with the mission needs, and that the project is well planned to meet the objectives. In the implementation phase, the technology development project matures the technology, and progress towards the KPPs is evaluated in periodic status reviews. Technology Readiness Levels (TRLs) are used throughout the project lifecycle to assess the progress of technology maturation. In the transition phase, technologies that are successful in achieving the required level of maturity are transitioned to a customer for further development, are used in system designs, or are thoroughly documented for resumption of development at a later date. The customer or end-user of the technology is involved in all phases of the technology development process.
The removal and installation of sting-mounted wind tunnel models in the National Transonic Facility (NTF) is a multi-task process having a large impact on the annual throughput of the facility. Approximately ten model removal and installation cycles occur annually at the NTF with each cycle requiring slightly over five days to complete. The various tasks of the model changeover process were modeled in Microsoft Project as a template to provide a planning, tracking, and management tool. The template can also be used as a tool to evaluate improvements to this process. This document describes the development of the template and provides step-by-step instructions on its use and as a planning and tracking tool. A secondary role of this document is to provide an overview of the model changeover process and briefly describe the tasks associated with it.
This report summaries the project team's activity during the period 1 January - 31 March 2004. It consists of a project plan, which was completed during this period and an indication of the completion status of each phase of the project. The intention of the investigative team is to closely follow the statement of work documented in our proposal. For this reason, the proposal may be referenced in this and upcoming status reports. This project got underway in this quarter. Our activity was to formulate a project plan and to engage in planning meetings with collaborators.