System safety - A management system for safety used in manned space flight.
Management system for safety in NASA Manned Space Flight Program, discussing hazard analyses and reduction precedence sequence
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Management system for safety in NASA Manned Space Flight Program, discussing hazard analyses and reduction precedence sequence
As emerging flight operations become more prevalent and increasingly automated and distributed, the capabilities for managing safety of vehicles and operations will also need to evolve. To address this challenge, the National Academies has envisioned an In-Time Aviation Safety Management System (IASMS) capability for a wide range of aviation operations including current commercial operations as well as new entrants envisioned with advanced air mobility (AAM). The suite of IASMS services, functions, and capabilities (SFCs) would be implemented in a federated approach and would address trends as well as individual operations. Through predictive modeling and data analysis, IASMS is envisioned to identify arising risks so that they can be mitigated, in-time, before a safety incident occurs. IASMS and its requisite set of SFCs must leverage a wide range of information to perform. To better understand these new needs, FSF worked with the aviation and humanitarian communities to develop and validate scenarios that include traditional aviation operations and UAS operations intermingled as they are deployed for disaster management and first responder (DMFR) situations. The three scenarios developed include: • Post Natural disaster response, such as a hurricane, involving multiple parties utilizing traditional aviation and UAS to support rescue operations, surveil damage, and locate survivors needing assistance. • Wildfire fighting in remote locations with traditional aircraft for transport and fire-retardant delivery combined with UAS for surveillance of fire locations as well as to track individual firefighter locations. • Medical Operations and AAM in Urban Environments including passenger-carrying helicopters and AAM vehicles, medical missions (such as transport of radio-pharmaceuticals), and other UAS delivery operations (such as the delivery of defibrillators). Each scenario was developed and validated by representatives with expertise in humanitarian operations, urban and rural emergency response, air traffic management, UAS operations, and traditional flight operations. The scenario definitions address roles and responsibilities of individual actors, the appropriate utilization of UAS, and the actions taken by those actors to appropriately manage risks associated with the mission and environment. The risks to aviation traffic and to people on the ground explored included potential risks arising from incompatibilities in calculating reference altitudes (eg, differing uses of AGL, MSL, barometric, or GPS-derived values), loss of command and control (C2) communications, rapid changes in weather and winds, and physical interference. For each risk, IASMS SFCs were postulated in the context of monitoring services, risk assessment capabilities, and identifying appropriate mitigation strategies. The identified SFC capabilities were envisioned from known services postulated for IASMS and for UTM. For these unique environments, IASMS SFCs are needed to address conditions such as hazardous payloads, micro-climates and urban canyons, and the need to keep uninvolved air traffic out of the area where DMFR operations are being conducted. The second phase of analysis focused on inferring the specific information needs and the SFCs for IASMS, utilizing a structure of 16 information classes to organize requirements. For each of the risks identified in the workshops, it was postulated what data sources would be necessary to monitor critical aspects of the risk (eg, surrounding air traffic, ground population, terrain, etc). to be directly measured as well as data that would be derived, which implies additional SFCs for different actors to understand what information would likely be exchanged between parties. For an IASMS to be effective, additional research is needed to develop the advanced algorithms that can address the increasingly autonomous and complex operations in differing environments and to develop means of identifying unknown risks. Looking at these scenarios highlighted a number of research issues. These include the ability to quickly "cordon off" airspace thru temporary flight restrictions (TFRs) or other means, developing clear definitions to enable automation-based algorithms for prioritizing operations, defining airspace density metrics, standardization of altitude reporting, and establishing a basis for safety data metrics definition and collection. This paper seeks to outline the development of an IASMS in the context of the DMFR scenarios and resulting demonstrations. Utilizing this contextual approach, NASA will generate recommendations for an assured safety framework for AAM operations that enables AAM operations to safely access the NAS.
In-time integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System (NAS). The path for realizing the vision includes addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers. The paper describes safety management systems and its’ challenges, and how the concept of In-time Aviation Safety Management Systems addresses the need to ensure an adaptable and resilient future safety system in the envisioned transformed NAS. Finally, it discusses potential human factors challenges, including new human roles and responsibilities, new information and cognitive requirements, new intelligent technologies that change human-system interaction and coordination, and new design paradigms for human system integration and teaming.
In-time integrated safety management will be paramount for safely enabling the envisioned transformations of the future National Airspace System (NAS). The path for realizing the vision includes addressing the increasing need for advanced data analytics and fusion of aviation safety data, managed by human decision-makers. The paper describes safety management systems and its’ challenges, and how the concept of In-time Aviation Safety Management Systems addresses the need to ensure an adaptable and resilient future safety system in the envisioned transformed NAS. Finally, it discusses potential human factors challenges, including new human roles and responsibilities, new information and cognitive requirements, new intelligent technologies that change human-system interaction and coordination, and new design paradigms for human system integration and teaming.
Tools from several different disciplines can improve system safety management. This paper relates the Art World with our system safety world, showing useful art schools of thought applied to system safety management, developing an art theory-system safety bridge. This bridge is then used to demonstrate relations with risk management, the legal system, personnel management and basic management (establishing priorities). One goal of this presentation/paper is simply to be a fun diversion from the many technical topics presented during the conference.
The envisioned transformation of the National Airspace System to integrate an In-time Aviation Safety Management System(IASMS)to assure safety in Advanced Air Mobility(AAM)brings unprecedented challenges to the design of human interfaces and management of safety information. Safety in design and operational safety assurance are critical factors for how humans will interact with increasingly autonomous systems. The IASMS Concept of Operations builds from traditional commercial operator safety management and scales in complexity to AAM. The transformative changes in future aviation systems pose potential new critical safety risks with novel types of aircraft and other vehicles having different performance capabilities, flying in increasingly complex airspace, and using adaptive contingencies to manage normal and non-normal operations. These changes compel development of new and emerging capabilities that enable innovative ways for humans to interact with data and manage information. In-creasing complexity of AAM corresponds with use of predictive modeling, data analytics, machine learning, and artificial intelligence to effectively address known hazards and emergent risks. The roles of humans will dynamically evolve in increments with this technological and operational evolution. The interfaces for how humans will interact with increasingly complex and assured systems designed to operate autonomously and how information will need to be presented are important challenges to be resolved.
In 2018, as result of a recommendation from the National Academies, NASA began to prototype an In-Time Aviation Safety Management System(IASMS). The purpose of the IASMS is to enable innovative aviation operations and greater heterogeneity of the overall National Airspace (NAS) by automating much of the safety monitoring, assessment, and risk and hazard mitigation functionspresent in today’s Safety Management Systems (SMS). NASA has worked together with early industry collaborators to understand how such a system might work and has published several early Concepts of Operation (ConOps) and other technical memoranda that illustrate the primary considerations for selected aviation domains. The shift from an SMS to an IASMS is predicated on several assumptions, including: 1.) automating safety functions will decrease the amount of time necessary for risk and hazard identification and analysis, making it more likely that safety concerns are understood ‘in-time’ to mitigate them, and 2.) an IASMS will allow easier tailoring of safety management processes to the particular risks and hazards inherent to that aviation operation. In this paper, we begin to validate these assumptions through the use of Model-Based Systems Engineering (MBSE).
In 2018, as result of a recommendation from the National Academies, NASA began to prototype an In-Time Aviation Safety Management System (IASMS). The purpose of the IASMS is to enable innovative aviation operations and greater heterogeneity of the overall National Airspace (NAS) by automating much of the safety monitoring, assessment, and risk and hazard mitigation function present in today’s Safety Management Systems (SMS). NASA has worked together with early industry collaborators to understand how such a system might work and has published several early Concepts of Operation (ConOps) and other technical memoranda that illustrate the primary considerations for selected aviation domains. The shift from an SMS to an IASMS is predicated on several assumptions, including: 1.) automating safety functions will decrease the amount of time necessary for risk and hazard identification and analysis, making it more likely that safety concerns are understood ‘in-time’ to mitigate them, and 2.) an IASMS will allow easier tailoring of safety management processes to the particular risks and hazards inherent to that aviation operation. In this paper, we begin to validate these assumptions through the use of Model-Based Systems Engineering (MBSE).
The systems theory is discussed in relation to safety management. It is suggested that systems safety management, as a new discipline, holds great promise for reducing operating errors, conserving labor resources, avoiding operating costs due to mistakes, and for improving managerial techniques. It is pointed out that managerial failures or system breakdowns are the basic reasons for human errors and condition defects. In this respect, a recommendation is made that safety engineers stop visualizing the problem only with the individual (supervisor or employee) and see the problem from the systems point of view.
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The National Airspace System (NAS) is growing in complexity of aircraft, missions, and operations. In response, many organizations have published papers and concepts of operations (ConOps) for new and enhanced safety systems. The National Academies’ vision for an In-time Aviation Safety Management System (IASMS) is integral to Federal Aviation Administration (FAA) modernization efforts. The National Aeronautics and Space Administration (NASA) System-Wide Safety (SWS) project is conducting safety research, exploring solutions, and defining the safety needs of future missions, such as Advanced Air Mobility (AAM) and autonomous aircraft operating in a more connected, flexible, and dynamic airspace. IASMS enables and provides a path for bringing FAA’s operational vision to fruition through increasingly automated safety systems that integrate services, functions, and capabilities (SFCs). These SFCs provide the necessary responsiveness to monitor, assess, and mitigate known hazards and emergent risks. This paper describes how safety in today’s air transportation system will need to evolve, identifies key points regarding in-time safety, and explores the criticality of IASMS in the future NAS.
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The growth of new emerging operations involving Advanced Air Mobility (AAM) necessitates developing a perspective for an In-time Aviation Safety Management System (IASMS). This perspective advances from the National Academies report on IASMS and its recommendation for developing a Concept of Operations (ConOps) for IASMS. A ConOps has been developed for In-time System-Wide Safety Assurance (ISSA) from which the IASMS ConOps pivots to provide a robust scope commensurate with the broad vision defined by the National Academies. The IASMS ConOps focuses on emerging operations and spans innovations in Unmanned Aircraft System (UAS) and an increasingly complex ecosystem comprised of a widening mix of vehicles and technologies, Urban Air Mobility (UAM) with industry-federated services, traditional operations, as well as new supersonic aircraft and space launch systems.The challenge for the IASMS ConOps is to be broad to encompass innovations in the coming years and decades while agile to ensure levels of safety compatible with operational and certification requirements of the National Airspace System (NAS). The IASMS ConOps interweaves increasing complexity of operational safety capabilities and unlocking UAS Maturity Levels (UMLs). The relationships between increased complexity of automation and automated systems, fewer operators who are not as traditionally higher skilled, more complex operational environments, and aviation operations management with mixed aircraft and equipage pose a multi-dimensional space for IASMS capabilities essential for safety assurance and risk management. Instantiating IASMS capabilities and how they would be integral to AAM operations and increasing maturity of UAM could be accomplished through a series of Safety Demonstrators. These Safety Demonstrators could provide increased understanding and insight into use of controls for risk mitigation, means of compliance for certification, and operational experience with safety services such as in relation to contingency management. The IASMS capabilities can be viewed as initially residing with the vehicle, airspace, and Supplemental Data Service Provider (SDSP). For example, vehicle capabilities include communications including the command and control link, Remote Identification (ID), conflict advisory/alerting, and UAS system monitoring. These capabilities monitor and assess data such as battery health, aircraft state, and human performance. Complexity of ISAMS capabilities depends on a number of factors. These factors are intendedonly as a notional categorization with the purpose being to reflect the complexity of the AAM ecosystem that would drive up the complexity of ISSA capabilities including systems, sensors, models, standards, and controls. Factors could include the Vehicle Flight Management, Environment, Airspace, and Contingency Management. Each of these factors can be comprised of multiple sub-factors that contribute to increasing complexity. For example, Airspace at a lower level of complexity could be dedicated to UTM operations that are unmonitored, and at a higher level of complexity could involve mixed UTM and ATM operations. The IASMS concept includes safety services that provide data and information to different participants in AAM. The roles and responsibilities of participants can be defined using the Responsible-Accountable-Consulted-Informed (RACI) analysis. For example, for the safety service involving the Remote ID, the Operator would be accountable for providing the data, the Vehicle would be responsible for transmitting it, and the USS, SDSP, Vertiports, FIMS (FAA), and Public Entities such as safety services would be informed by receiving the data. The IASMS ConOps identifies the capabilities needed for risk mitigation and safety assurance in the increasingly complex national airspace. The ConOps serves as a pathway for engaging with industry to gain operational experience including through the Safety Demonstrator series, the RACI analysis, and operational complexity factors. The ConOps serves to integrate these different perspectives to build a cohesive and cogent approach to an AAM safety management system.
Our current air transportation system has underserved markets, including local, regional, intraregional, and urban transportation of both people and cargo. Recent advances in aviation technology such as small highly-automated vehicles, electric aircraft, and automated air traffic are enabling business opportunities in these markets. Advanced Air Mobility, or AAM, refers to a community effort to overcome the gaps in operational rules, safety analysis, and overall acceptance, so that these new operations will be possible. For full details, please see: https://www.nasa.gov/aam As we think about how we can safely introduce these new operations, fundamental questions about how the structure of Safety Management Systems can be applied to AAM, and how that structure can be used to help us overcome the necessary technical and societal obstacles arise. Two of these questions are: • How do we tailor the requirements and desired level of monitoring and assessment to achieve safety given the breadth of possible operations and the associated risk of those operations? • How do we aid innovation by rapidly evaluating the safety of novel operations without losing associated rigor? We assume that a Safety Management System that enables these future systems will incorporate knowledge of the acceptable level of risk, and will utilize data science to automate the core monitor, assess and mitigate functions that will allow us to respond to risks and hazards in time to prevent safety incidents. In 2018, the National Academies proposed an In-Time Aviation Safety Management System (IASMS) that would advance these goals. (https://www.nap.edu/catalog/24962/in-time-aviation-safety-management-challenges-and-research-for-an) The National Academies made a clear distinction between in-time systems, in which hazards could be identified and risks mitigated in time to prevent incidents, and real-time systems, since many hazards and risks do not need real-time data and analysis to detect and mitigate.
Enabling new and novel concepts of operations for Advanced Air Mobility poses an important need to evolve current safety management systems (SMS) and is posited to be realized through advances in Machine Learning (ML) Data Sciences and Artificial Intelligence. The “In-time Aviation Safety Management System” (IASMS) concept of operations supports the need to evolve today’s SMS to become more tailorable, scalable, and interoperable in response to forecasted changes expected for the future airspace system. Key to IASMS is integration of proactive and predictive ML algorithms trained to provide “in time” detection and mitigation of hazards and emergent risks through new methods and novel data types. IASMS research and technology development includes human factors design considerations for these systems to include human-system teaming, innovations in human interfaces and management of complex digital data information, human-system interaction/model-based system engineering, and verification and validation for data assurance and trust.
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NASA’s vision for Advanced Air Mobility (AAM) Mission is to help emerging aviation markets to safely develop an air transportation system that moves people and cargo between places previously not served or underserved by aviation. The integration of new operational paradigms and vehicle classes in this system requires a transformation of the National Airspace System (NAS) that includes substantive changes critical for assuring safety. These changes are compelled by unique challenges posed by AAM to the safety management system (SMS). These challenges were assessed by committees of the National Academies in their reports on a vision for an In-time Aviation Safety Management System (IASMS) and a blueprint for AAM [1,2]. In their description of an IASMS, the top recommendation was development of a concept of operations (ConOps) for IASMS. This paper describes the high-priority recommendations from the National Academies for its IASMS vision and how they are addressed through a distributed system-of-systems architecture. The IASMS architecture is structured on the services, functions, and capabilities (SFCs) necessary for In-time System-wide Safety Assurance (ISSA)initially developed for urban air mobility (UAM). The paper then posits where these SFCs would reside across vehicles, airspace, or service suppliers such as Supplemental Data Service Providers (SDSPs), and how SFCs scale with increasing complexity in design and operations of AAM. SFCs are foundational building blocks for a system that targets an individual or family of risks using a Monitor-Assess-Mitigate risk paradigm for anomalies, precursors and trends. An IASMS could be conceived that uses a portfolio of SFCs for AAM in general or prioritizes SFCs for a specific domain or operation.
Today’s airports are complex multi-faceted ecosystems. Currently, of the 517certificatedairports, 270arerequired to use safety management systems (SMSs) to identify and mitigate known hazards and emergent risks and to voluntarily share safety data with commercial operators and tenants. Airports manage a wide variety of hazards. These traffic hubs have direct responsibilities, such as removing foreign object debris from runways and taxiways and configuring runways to help prevent against incursions and tail strikes during takeoff. To ensure safety in the future NAS, the National Academies recommended an In-time Aviation Safety Management System (IASMS). An IASMS will employ services, functions, and capabilities (SFCs) to identify and mitigate hazards that are proactively and predictively managed based on data analytics of detected anomalies, precursors, and trends. SFCs would scale with airport complexity and environmental conditions using increasingly automated systems to respond proactively to hazards and, by using integrated data sources and predictive safety analytical methods, discover new, never before seen risks.