Engineering topics
Meshkat, Leila
Publications and source records attributed to Meshkat, Leila.
Managing the Risk of Command File Errors
Command File Error (CFE), as defined by the Jet Propulsion Laboratory's (JPL) Mission Operations Assurance (MOA) is, regardless of the consequence on the spacecraft, either: an error in a command file sent to the spacecraft, an error in the process for developing and delivering a command file to the spacecraft, or the omission of a command file that should have been sent to the spacecraft. The risk consequence of a CFE can be mission ending and thus a concern to space exploration projects during their mission operations. A CFE during space mission operations is often the symptom of some kind of imbalance or inadequacy within the system that comprises the hardware & software used for command generation and the human experts involved in this endeavour. As we move into an era of enhanced collaboration with other NASA centers and commercial partners, these systems become more and more complex and hence it is all the more important to formally model and analyze CFEs in order to manage the risk of CFEs. Here we will provide a summary of the ongoing efforts at JPL in this area and also explain some more recent developments in the area of developing quantitative models for the purpose of managing CFE's.
A Systems Modeling Approach for Risk Management of Command File Errors
The main cause of commanding errors is often (but not always) due to procedures. Either lack of maturity in the processes, incompleteness of requirements or lack of compliance to these procedures. Other causes of commanding errors include lack of understanding of system states, inadequate communication, and making hasty changes in standard procedures in response to an unexpected event. In general, it's important to look at the big picture prior to making corrective actions. In the case of errors traced back to procedures, considering the reliability of the process as a metric during its' design may help to reduce risk. This metric is obtained by using data from Nuclear Industry regarding human reliability. A structured method for the collection of anomaly data will help the operator think systematically about the anomaly and facilitate risk management. Formal models can be used for risk based design and risk management. A generic set of models can be customized for a broad range of missions.
Reliability Analysis and Standardization of Spacecraft Command Generation Processes
center dot In order to reduce commanding errors that are caused by humans, we create an approach and corresponding artifacts for standardizing the command generation process and conducting risk management during the design and assurance of such processes. center dot The literature review conducted during the standardization process revealed that very few atomic level human activities are associated with even a broad set of missions. center dot Applicable human reliability metrics for performing these atomic level tasks are available. center dot The process for building a "Periodic Table" of Command and Control Functions as well as Probabilistic Risk Assessment (PRA) models is demonstrated. center dot The PRA models are executed using data from human reliability data banks. center dot The Periodic Table is related to the PRA models via Fault Links.
TAMU: a new space mission operations paradigm
The Transferable, Adaptable, Modular and Upgradeable (TAMU) Flight Production Process (FPP) is a model-centric System of System (SoS) framework which cuts across multiple organizations and their associated facilities, that are, in the most general case, in geographically diverse locations, to develop the architecture and associated workflow processes for a broad range of mission operations. Further, TAMU FPP envisions the simulation, automatic execution and re-planning of orchestrated workflow processes as they become operational. This paper provides the vision for the TAMU FPP paradigm. This includes a complete, coherent technique, process and tool set that result in an infrastructure that can be used for full lifecycle design and decision making during any flight production process. A flight production process is the process of developing all products that are necessary for flight.
TAMU: A New Space Mission Operations Paradigm
The Transferable, Adaptable, Modular and Upgradeable (TAMU) Flight Production Process (FPP) is a model-centric System of System (SoS) framework which cuts across multiple organizations and their associated facilities, that are, in the most general case, in geographically diverse locations, to develop the architecture and associated workflow processes for a broad range of mission operations. Further, TAMU FPP envisions the simulation, automatic execution and re-planning of orchestrated workflow processes as they become operational. This paper provides the vision for the TAMU FPP paradigm. This includes a complete, coherent technique, process and tool set that result in an infrastructure that can be used for full lifecycle design and decision making during any flight production process. A flight production process is the process of developing all products that are necessary for flight.
Command Process Modeling & Risk Analysis
Commanding Errors may be caused by a variety of root causes. It's important to understand the relative significance of each of these causes for making institutional investment decisions. One of these causes is the lack of standardized processes and procedures for command and control. We mitigate this problem by building periodic tables and models corresponding to key functions within it. These models include simulation analysis and probabilistic risk assessment models.
Software Development Standard Processes (SDSP)
A JPL-created set of standard processes is to be used throughout the lifecycle of software development. These SDSPs cover a range of activities, from management and engineering activities, to assurance and support activities. These processes must be applied to software tasks per a prescribed set of procedures. JPL s Software Quality Improvement Project is currently working at the behest of the JPL Software Process Owner to ensure that all applicable software tasks follow these procedures. The SDSPs are captured as a set of 22 standards in JPL s software process domain. They were developed in-house at JPL by a number of Subject Matter Experts (SMEs) residing primarily within the Engineering and Science Directorate, but also from the Business Operations Directorate and Safety and Mission Success Directorate. These practices include not only currently performed best practices, but also JPL-desired future practices in key thrust areas like software architecting and software reuse analysis. Additionally, these SDSPs conform to many standards and requirements to which JPL projects are beholden.
TAMU: Blueprint for A New Space Mission Operations System Paradigm
The Transferable, Adaptable, Modular and Upgradeable (TAMU) Flight Production Process (FPP) is a System of System (SOS) framework which cuts across multiple organizations and their associated facilities, that are, in the most general case, in geographically disperse locations, to develop the architecture and associated workflow processes of products for a broad range of flight projects. Further, TAMU FPP provides for the automatic execution and re-planning of the workflow processes as they become operational. This paper provides the blueprint for the TAMU FPP paradigm. This blueprint presents a complete, coherent technique, process and tool set that results in an infrastructure that can be used for full lifecycle design and decision making during the flight production process. Based on the many years of experience with the Space Shuttle Program (SSP) and the International Space Station (ISS), the currently cancelled Constellation Program which aimed on returning humans to the moon as a starting point, has been building a modern model-based Systems Engineering infrastructure to Re-engineer the FPP. This infrastructure uses a structured modeling and architecture development approach to optimize the system design thereby reducing the sustaining costs and increasing system efficiency, reliability, robustness and maintainability metrics. With the advent of the new vision for human space exploration, it is now necessary to further generalize this framework to take into consideration a broad range of missions and the participation of multiple organizations outside of the MOD; hence the Transferable, Adaptable, Modular and Upgradeable (TAMU) concept.
Re-Engineering Complex Legacy Systems at NASA
The Flight Production Process (FPP) Re-engineering project has established a Model-Based Systems Engineering (MBSE) methodology and the technological infrastructure for the design and development of a reference, product-line architecture as well as an integrated workflow model for the Mission Operations System (MOS) for human space exploration missions at NASA Johnson Space Center. The design and architectural artifacts have been developed based on the expertise and knowledge of numerous Subject Matter Experts (SMEs). The technological infrastructure developed by the FPP Re-engineering project has enabled the structured collection and integration of this knowledge and further provides simulation and analysis capabilities for optimization purposes. A key strength of this strategy has been the judicious combination of COTS products with custom coding. The lean management approach that has led to the success of this project is based on having a strong vision for the whole lifecycle of the project and its progress over time, a goal-based design and development approach, a small team of highly specialized people in areas that are critical to the project, and an interactive approach for infusing new technologies into existing processes. This project, which has had a relatively small amount of funding, is on the cutting edge with respect to the utilization of model-based design and systems engineering. An overarching challenge that was overcome by this project was to convince upper management of the needs and merits of giving up more conventional design methodologies (such as paper-based documents and unwieldy and unstructured flow diagrams and schedules) in favor of advanced model-based systems engineering approaches.
Probabilistic Risk Assessment for Decision Making During Spacecraft Operations
Decisions made during the operational phase of a space mission often have significant and immediate consequences. Without the explicit consideration of the risks involved and their representation in a solid model, it is very likely that these risks are not considered systematically in trade studies. Wrong decisions during the operational phase of a space mission can lead to immediate system failure whereas correct decisions can help recover the system even from faulty conditions. A problem of special interest is the determination of the system fault protection strategies upon the occurrence of faults within the system. Decisions regarding the fault protection strategy also heavily rely on a correct understanding of the state of the system and an integrated risk model that represents the various possible scenarios and their respective likelihoods. Probabilistic Risk Assessment (PRA) modeling is applicable to the full lifecycle of a space mission project, from concept development to preliminary design, detailed design, development and operations. The benefits and utilities of the model, however, depend on the phase of the mission for which it is used. This is because of the difference in the key strategic decisions that support each mission phase. The focus of this paper is on describing the particular methods used for PRA modeling during the operational phase of a spacecraft by gleaning insight from recently conducted case studies on two operational Mars orbiters. During operations, the key decisions relate to the commands sent to the spacecraft for any kind of diagnostics, anomaly resolution, trajectory changes, or planning. Often, faults and failures occur in the parts of the spacecraft but are contained or mitigated before they can cause serious damage. The failure behavior of the system during operations provides valuable data for updating and adjusting the related PRA models that are built primarily based on historical failure data. The PRA models, in turn, provide insight into the effect of various faults or failures on the risk and failure drivers of the system and the likelihood of possible end case scenarios, thereby facilitating the decision making process during operations. This paper describes the process of adjusting PRA models based on observed spacecraft data, on one hand, and utilizing the models for insight into the future system behavior on the other hand. While PRA models are typically used as a decision aid during the design phase of a space mission, we advocate adjusting them based on the observed behavior of the spacecraft and utilizing them for decision support during the operations phase.
A dynamic fault tree model of a propulsion system
We present a dynamic fault tree model of the benchmark propulsion system, and solve it using Galileo. Dynamic fault trees (DFT) extend traditional static fault trees with special gates to model spares and other sequence dependencies. Galileo solves DFT models using a judicious combination of automatically generated Markov and Binary Decision Diagram models. Galileo easily handles the complexities exhibited by the benchmark problem. In particular, Galileo is designed to model phased mission systems.
An Efficient Approach for the Reliability Analysis of Phased-Mission Systems with Dependent Failures
We consider the reliability analysis of phased-mission systems with common-cause failures in this paper. Phased-mission systems (PMS) are systems supporting missions characterized by multiple, consecutive, and nonoverlapping phases of operation. System components may be subject to different stresses as well as different reliability requirements throughout the course of the mission. As a result, component behavior and relationships may need to be modeled differently from phase to phase when performing a system-level reliability analysis. This consideration poses unique challenges to existing analysis methods. The challenges increase when common-cause failures (CCF) are incorporated in the model. CCF are multiple dependent component failures within a system that are a direct result of a shared root cause, such as sabotage, flood, earthquake, power outage, or human errors. It has been shown by many reliability studies that CCF tend to increase a system's joint failure probabilities and thus contribute significantly to the overall unreliability of systems subject to CCF.We propose a separable phase-modular approach to the reliability analysis of phased-mission systems with dependent common-cause failures as one way to meet the above challenges in an efficient and elegant manner. Our methodology is twofold: first, we separate the effects of CCF from the PMS analysis using the total probability theorem and the common-cause event space developed based on the elementary common-causes; next, we apply an efficient phase-modular approach to analyze the reliability of the PMS. The phase-modular approach employs both combinatorial binary decision diagram and Markov-chain solution methods as appropriate. We provide an example of a reliability analysis of a PMS with both static and dynamic phases as well as CCF as an illustration of our proposed approach. The example is based on information extracted from a Mars orbiter project. The reliability model for this orbiter considers the various phases of Launch, Cruise, Mars Orbit Insertion, and Orbit. Some of the CCF for the orbiter in this mission include environmental effects, such as micrometeoroids, human operator errors, and software errors.
A Holistic Approach for Risk Management During Design
In this paper, an approach for the identification, assessment, mitigation and continuous management of risks during the process of designing a space mission is presented. This approach has been developed by observing the risk patterns that occur at the Project Design Center of the Jet Propulsion Laboratory (TeamX) which develops conceptual, concurrent design of Space Missions. TeamX develops an end-to-end conceptual design of a Space Mission in a matter of one or two weeks. As the risk chair in TeamX, the author has had the opportunity to observe the risk patterns that occur during design over the course of many design sessions. This paper introduces an abstraction and generalization of those patterns. Risk is defined as anything that can go wrong, along with its approximate likelihood and consequence. The indicators, and causes, and effects of these risks are cross cutting across the multiple levels of people and processes involved in the design, and the actual design product itself.
Risk management during design
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