Development of reliability methodology for systems engineering. Volume I - Methodology - Analysis techniques and procedures Final report
Reliability analyses for equipment in design stage
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Reliability analyses for equipment in design stage
The project requirements, approach, system description, design requirements, design, analysis, system tests, installation safety considerations, failure modes and effects analysis, data acquisition, and initial performance for the MOD-OA 200 kw wind turbine generator are discussed. The components, the rotor, driven train, nacelle equipment, yaw drive mechanism and brake, tower, foundation, electrical system, and control systems are presented. The rotor includes the blades, hub and pitch change mechanism. The drive train includes the low speed shaft, speed increaser, high speed shaft, and rotor brake. The electrical system includes the generator, switchgear, transformer, and utility connection. The control systems are the blade pitch, yaw, and generator control, and the safety system. Manual, automatic, and remote control and Dynamic loads and fatigue are analyzed.
A study was conducted to establish the guidelines to be applied to the selection of equipment for manned spacecraft systems. Recommendations for expansion of the original study are submitted. The subjects considered are: (1) designing to severe dynamic requirements; (2) analysis of in-space failures due to life limitations; (3) accelerated testing of semiconductors; (4) fan life verification; (5) testing of solid tantalum capacitors; (6) testing of teflon valve seats; and (7) electromigration model verification.
The structures and mechanical subsystem of a space station are considered. The subsystem includes basic structure (pressurization, equipment support, meteoroid protection, radiators, insulation, and docking interfaces), the docking mechanisms, spacecraft access (hatches, airlocks, and view ports), and antenna deployment mechanisms. Checkout is discussed in terms of reliability, failure analysis, and maintenance.
The preprototype water quality monitor (WQM) subsystem was designed based on a breadboard monitor for pH, specific conductance, and total organic carbon (TOC). The breadboard equipment demonstrated the feasibility of continuous on-line analysis of potable water for a spacecraft. The WQM subsystem incorporated these breadboard features and, in addition, measures ammonia and includes a failure detection system. The sample, reagent, and standard solutions are delivered to the WQM sensing manifold where chemical operations and measurements are performed using flow through sensors for conductance, pH, TOC, and NH3. Fault monitoring flow detection is also accomplished in this manifold assembly. The WQM is designed to operate automatically using a hardwired electronic controller. In addition, automatic shutdown is incorporated which is keyed to four flow sensors strategically located within the fluid system.
NASA missions are extremely complex and prone to sudden, catastrophic failure if equipment falters or if an unforeseen event occurs. For these reasons, NASA trains to expect the unexpected. It tests its equipment and systems in extreme conditions, and it develops risk-analysis tests to foresee any possible problems. The Space Agency recently worked with an industry partner to develop reliability analysis software capable of modeling complex, highly dynamic systems, taking into account variations in input parameters and the evolution of the system over the course of a mission. The goal of this research was multifold. It included performance and risk analyses of complex, multiphase missions, like the insertion of the Mars Reconnaissance Orbiter; reliability analyses of systems with redundant and/or repairable components; optimization analyses of system configurations with respect to cost and reliability; and sensitivity analyses to identify optimal areas for uncertainty reduction or performance enhancement.
The results of the Independent Orbiter Assessment (IOA) of the Failure Modes and Effects Analysis (FMEA) and Critical Items List (CIL) are presented. The IOA approach features a top-down analysis of the hardware to determine failure modes, criticality, and potential critical items. To preserve independence, this analysis was accomplished without reliance upon the results contained within the NASA FMEA/CIL documentation. The independent analysis results for the Instrumentation Subsystem are documented. The Instrumentation Subsystem (SS) consists of transducers, signal conditioning equipment, pulse code modulation (PCM) encoding equipment, tape recorders, frequency division multiplexers, and timing equipment. For this analysis, the SS is broken into two major groupings: Operational Instrumentation (OI) equipment and Modular Auxiliary Data System (MADS) equipment. The OI equipment is required to acquire, condition, scale, digitize, interleave/multiplex, format, and distribute operational Orbiter and payload data and voice for display, recording, telemetry, and checkout. It also must provide accurate timing for time critical functions for crew and payload specialist use. The MADS provides additional instrumentation to measure and record selected pressure, temperature, strain, vibration, and event data for post-flight playback and analysis. MADS data is used to assess vehicle responses to the flight environment and to permit correlation of such data from flight to flight. The IOA analysis utilized available SS hardware drawings and schematics for identifying hardware assemblies and components and their interfaces. Criticality for each item was assigned on the basis of the worst-case effect of the failure modes identified.
History has shown that failures occur in every engineering endeavor, and what we learn from those failures contributes to the knowledge base to safely complete future missions. The necessity of failure analysis is at its apex at the end of one aged program and at the beginning of a new and untested program. The information that we gain through failure analysis corrects the deficiencies in the current vehicle to make the next generation of vehicles more efficient and safe. The Failure Analysis and Materials Evaluation Branch in the Materials Science Division at the Kennedy Space Center performs metallurgical, mechanical, electrical, and non-metallic materials failure analyses and accident investigations on both flight hardware and ground support equipment for the Space Shuttle, International Space Station, Constellation, and Launch Services Programs. This paper will explore a variety of failure case studies at the Kennedy Space Center and the lessons learned that can be applied in future programs.
The purpose of dynamic modeling and simulation of Advanced Life Support (ALS) systems is to help design them. Static steady state systems analysis provides basic information and is necessary to guide dynamic modeling, but static analysis is not sufficient to design and compare systems. ALS systems must respond to external input variations and internal off-nominal behavior. Buffer sizing, resupply scheduling, failure response, and control system design are aspects of dynamic system design. We develop two dynamic mass flow models and use them in simulations to evaluate systems issues, optimize designs, and make system design trades. One model is of nitrogen leakage in the space station, the other is of a waste processor failure in a regenerative life support system. Most systems analyses are concerned with optimizing the cost/benefit of a system at its nominal steady-state operating point. ALS analysis must go beyond the static steady state to include dynamic system design. All life support systems exhibit behavior that varies over time. ALS systems must respond to equipment operating cycles, repair schedules, and occasional off-nominal behavior or malfunctions. Biological components, such as bioreactors, composters, and food plant growth chambers, usually have operating cycles or other complex time behavior. Buffer sizes, material stocks, and resupply rates determine dynamic system behavior and directly affect system mass and cost. Dynamic simulation is needed to avoid the extremes of costly over-design of buffers and material reserves or system failure due to insufficient buffers and lack of stored material.
The scope and status of the effort to assess the risks associated with the accidental release of carbon/graphite fibers from civil aircraft is presented. Vulnerability of electrical and electronic equipment to carbon fibers, dispersal of carbon fibers, effectiveness of filtering systems, impact of fiber induced failures, and risk methodology are among the topics covered.
NASA has initiated a significant thrust of research and development focused on providing the flight crew and air traffic managers automation aids to increase capacity in en route and terminal area operations through the use of flexible, more fuel-efficient routing, while improving the level of safety in commercial carrier operations. In that system development, definition of cognitive requirements for integrated multi-operator dynamic aiding systems is fundamental. In order to support that cognitive function definition, we have extended the Man Machine Integrated Design and Analysis System (MIDAS) to include representation of multiple cognitive agents (both human operators and intelligent aiding systems) operating aircraft, airline operations centers and air traffic control centers in the evolving airspace. The demands of this application require representation of many intelligent agents sharing world-models, and coordinating action/intention with cooperative scheduling of goals and actions in a potentially unpredictable world of operations. The MIDAS operator models have undergone significant development in order to understand the requirements for operator aiding and the impact of that aiding in the complex nondeterminate system of national airspace operations. The operator model's structure has been modified to include attention functions, action priority, and situation assessment. The cognitive function model has been expanded to include working memory operations including retrieval from long-term store, interference, visual-motor and verbal articulatory loop functions, and time-based losses. The operator's activity structures have been developed to include prioritization and interruption of multiple parallel activities among multiple operators, to provide for anticipation (knowledge of the intention and action of remote operators), and to respond to failures of the system and other operators in the system in situation-specific paradigms. The model's internal representation has been be modified so that multiple, autonomous sets of equipment will function in a scenario as the single equipment sets do now. In order to support the analysis requirements with multiple items of equipment, it is necessary for equipment to access the state of other equipment objects at initialization time (a radar object may need to access the position and speed of aircraft in its area, for example), and as a function of perception and sensor system interaction. The model has been improved to include multiple world-states as a function of equipment am operator interaction. The model has been used -1o predict the impact of warning and alert zones in aircraft operation, and, more critic-ally, the interaction of flight-deck based warning mechanisms and air traffic controller action in response to ground-based conflict prediction and alerting systems. In this operation, two operating systems provide alerting to two autonomous, but linked sets of operators, whose view of the system and whose dynamics in response are radically different. System stability and operator action was predicted using the MIDAS model.
The precision power monitor (PPM) is a precision radiometric instrument used to improve the efficiency of signal reception by the Deep Space Network. Real time estimates of the system operating temperature, the present (signal + noise)-to-noise ratio, and the signal power are utilized to increase the accuracy and resolution of the received spacecraft signal. Due to the critical nature of radio science data returning from Voyager 2 at Saturn Encounter, PPM support was required. The task was undertaken to validate the performance of equipment technically under research and development in time to meet the encounter deadline. Initial studies revealed PPM performance to be out of tolerance. Action was immediately taken to identify the system problems. Using data analysis as feedback, the system failures were identified and corrected in time to contribute to the encounter support efforts. As a result, the radio science data were collected successfully.
National Aeronautics and Space Administration (NASA) subcontractor Wiltech contacted the NASA Electrical Lab (NE-L) and requested a failure analysis of a Solvent Purity Meter; model SP-IOOO produced by the VerTis Instrument Company. The meter, used to measure the contaminate in a solvent to determine the relative contamination on spacecraft flight hardware and ground servicing equipment, had been inoperable and in storage for an unknown amount of time. NE-L was asked to troubleshoot the unit and make a determination on what may be required to make the unit operational. Through the use of general troubleshooting processes and the review of a unit in service at the time of analysis, the unit was found to be repairable but would need the replacement of multiple components.
Plume spectrometry provides a means to monitor the health of a burning rocket engine, and optical matrix processors provide a means to analyze the plume spectra in real time. By observing the spectrum of the exhaust plume of a rocket engine, researchers have detected anomalous behavior of the engine and have even determined the failure of some equipment before it would normally have been noticed. The spectrum of the plume is analyzed by isolating information in the spectrum about the various materials present to estimate what materials are being burned in the engine. Scientists at the Marshall Space Flight Center (MSFC) have implemented a high resolution spectrometer to discriminate the spectral peaks of the many species present in the plume. Researchers at the Stennis Space Center Demonstration Testbed Facility (DTF) have implemented a high resolution spectrometer observing a 1200-lb. thrust engine. At this facility, known concentrations of contaminants can be introduced into the burn, allowing for the confirmation of diagnostic algorithms. While the high resolution of the measured spectra has allowed greatly increased insight into the functioning of the engine, the large data flows generated limit the ability to perform real-time processing. The use of an optical matrix processor and the linear analysis technique described below may allow for the detailed real-time analysis of the engine's health. A small optical matrix processor can perform the required mathematical analysis both quicker and with less energy than a large electronic computer dedicated to the same spectral analysis routine.
The baseline data management subsystem for a space station is discussed. The subsystem consists of equipment necessary to transfer, store, and process data to and from users and subsystems. It acquires and conditions a wide variety of input data from experiments, vehicle subsystems sensors, uplinked ground communications, and astronaut-activated controls. Computer techniques for failure analysis, reliability, and maintenance checkout onboard the space station are considered.
The reliability and quality assurance system and procedures used in developing test equipment for the Lunar Experiment projects are described. The subjects discussed include the following: (1) documentation control, (2) design review, (3) parts and materials selection, (4) material procurement, (5) inspection procedures, (6) qualification and special testing, and failure modes and effects analysis.
A new noise measuring method is outlined that is based on electronic analysis of the radiated noise. Non-relevant components are suppressed, while the differential phonogram displayed on the oscilloscope screen discloses the information carrying components. It allows low skilled operators to perform: (1) correct alignment of equipment; (2) detection of incipient failure; and (3) checking of prototypes.
Cranes and hoists are widely used in many areas. Crane accidents and handling mishaps are responsible for injuries, costly equipment damage, and program delays. Most crane accidents are caused by preventable factors. Understanding these factors is critical when designing cranes and preparing lift plans. Analysis of previous accidents provides insight into current recommendations for crane safety. Cranes and hoists are used throughout Kennedy Space Center to lift everything from machine components to critical flight hardware. Unless they are trained crane operators, most NASA employees and contractors do not need to undergo specialized crane training and may not understand the safety issues surrounding the use of cranes and hoists. A single accident with a crane or hoist can injure or kill people, cause severe equipment damage, and delay or terminate a program. Handling mishaps can also have a significant impact on the program. Simple mistakes like bouncing or jarring a load, or moving the crane down when it should go up, can damage fragile flight hardware and cause major delays in processing. Hazardous commodities (high pressure gas, hypergolic propellants, and solid rocket motors) can cause life safety concerns for the workers performing the lifting operations. Most crane accidents are preventable with the correct training and understanding of potential hazards. Designing the crane with human factors taken into account can prevent many accidents. Engineers are also responsible for preparing lift plans where understanding the safety issues can prevent or mitigate potential accidents. Cranes are widely used across many areas of KSC. Failure of these cranes often leads to injury, high damage costs, and significant delays in program objectives. Following a basic set of principles and procedures during design, fabrication, testing, regular use, and maintenance can significantly minimize many of these failures. As the accident analysis shows, load drops are often caused or influenced by human factors. Therefore, proper training and understanding of crane safety throughout the workforce is critical. It is important that the engineers designing the cranes, lift planners preparing the lift plans, operators performing the lifts, and training officers conducting the operator training all understand the problems that can happen with cranes and how to ensure the safety of the workforce and equipment being lifted.