Results for “scheduling software” — Page 2

NASA NTRS1993

Video conferencing made easy

Network video conferencing is advancing rapidly throughout the nation, and the Idaho National Engineering Laboratory (INEL), a Department of Energy (DOE) facility, is at the forefront of the development. Engineers at INEL/EG&G designed and installed a very unique DOE videoconferencing system, offering many outstanding features, that include true multipoint conferencing, user-friendly design and operation with no full-time operators required, and the potential for cost effective expansion of the system. One area where INEL/EG&G engineers made a significant contribution to video conferencing was in the development of effective, user-friendly, end station driven scheduling software. A PC at each user site is used to schedule conferences via a windows package. This software interface provides information to the users concerning conference availability, scheduling, initiation, and termination. The menus are 'mouse' controlled. Once a conference is scheduled, a workstation at the hubs monitors the network to initiate all scheduled conferences. No active operator participation is required once a user schedules a conference through the local PC; the workstation automatically initiates and terminates the conference as scheduled. As each conference is scheduled, hard copy notification is also printed at each participating site. Video conferencing is the wave of the future. The use of these user-friendly systems will save millions in lost productivity and travel cost throughout the nation. The ease of operation and conference scheduling will play a key role on the extent industry uses this new technology. The INEL/EG&G has developed a prototype scheduling system for both commercial and federal government use.

Larsen, D. Gail↗

NASA NTRS1996

Explicit and Implicit Resources: A Simplified Approach to User Requirements Modeling

The International Space Station (ISS) program is dependent on the concept of distributed planning, which places a large responsibility in the hands of the science users. The users assume the responsibility in submitting the operations scheduling requirements in the format required by the scheduling software. The concept of explicit and implicit resources, developed to facilitate the operations scheduling of ISS by non-scheduling experts, is presented. The proposed concepts are defined and examples of scheduling requirements, implemented using explicit and implicit resources, are described together with the requirements modeling and scheduler formatting functions. The software developed to support the implicit and explicit resources concept is discussed.

Hagopian, Jeff↗

NASA NTRS2009

Hubble Systems Optimize Hospital Schedules

Don Rosenthal, a former Ames Research Center computer scientist who helped design the Hubble Space Telescope's scheduling software, co-founded Allocade Inc. of Menlo Park, California, in 2004. Allocade's OnCue software helps hospitals reclaim unused capacity and optimize constantly changing schedules for imaging procedures. After starting to use the software, one medical center soon reported noticeable improvements in efficiency, including a 12 percent increase in procedure volume, 35 percent reduction in staff overtime, and significant reductions in backlog and technician phone time. Allocade now offers versions for outpatient and inpatient magnetic resonance imaging (MRI), ultrasound, interventional radiology, nuclear medicine, Positron Emission Tomography (PET), radiography, radiography-fluoroscopy, and mammography.

Source record↗

NASA NTRS2010

Request-Driven Schedule Automation for the Deep Space Network

The DSN Scheduling Engine (DSE) has been developed to increase the level of automated scheduling support available to users of NASA s Deep Space Network (DSN). We have adopted a request-driven approach to DSN scheduling, in contrast to the activity-oriented approach used up to now. Scheduling requests allow users to declaratively specify patterns and conditions on their DSN service allocations, including timing, resource requirements, gaps, overlaps, time linkages among services, repetition, priorities, and a wide range of additional factors and preferences. The DSE incorporates a model of the key constraints and preferences of the DSN scheduling domain, along with algorithms to expand scheduling requests into valid resource allocations, to resolve schedule conflicts, and to repair unsatisfied requests. We use time-bounded systematic search with constraint relaxation to return nearby solutions if exact ones cannot be found, where the relaxation options and order are under user control. To explore the usability aspects of our approach we have developed a graphical user interface incorporating some crucial features to make it easier to work with complex scheduling requests. Among these are: progressive revelation of relevant detail, immediate propagation and visual feedback from a user s decisions, and a meeting calendar metaphor for repeated patterns of requests. Even as a prototype, the DSE has been deployed and adopted as the initial step in building the operational DSN schedule, thus representing an important initial validation of our overall approach. The DSE is a core element of the DSN Service Scheduling Software (S(sup 3)), a web-based collaborative scheduling system now under development for deployment to all DSN users.

Johnston, Mark D.↗

NASA NTRSDate not supplied

Crew Autonomy through Self-Scheduling: Scheduling Performance Pilot Study

Within the domain of human spaceflight, crew scheduling for International Space Station (ISS) remains a human-driven planning task. Large teams of flight controllers (called Ops Planners) spend weeks creating violation-free schedules for all crewmembers. As NASA considers long-duration exploration missions, the necessary shift of scheduling and planning management from Ops Planners to crew members requires significant research and investigation of crew performance to complete these scheduling tasks. This pilot study was conducted to evaluate non-expert human performance for the task of planning and scheduling, focusing on scheduling problems that increased in complexity based on the number of activities to be scheduled and the number of planning constraints. Nine non-expert planners were recruited to complete scheduling tasks using Playbook, a scheduling software. The results of this pilot study show that scheduling performance decreased as scheduling workload (i.e. number of activities and percent of activities with planning constraints) increased. This paper provides evidence towards developing a model for scheduling task difficulty and identifies potential implications for future automated aids for flight crew scheduling.

planning↗

NASA NTRSDate not supplied

Crew Autonomy Through Self-Scheduling: Scheduling Performance Pilot Study

Within the domain of human spaceflight, crew scheduling for International Space Station (ISS) remains a human-driven planning task. Large teams of flight controllers (called Ops Planners) spend weeks creating violation-free schedules for all crewmembers. As NASA considers long-duration exploration missions, the necessary shift of scheduling and planning management from Ops Planners to crew members requires significant research and investigation of crew performance to complete these scheduling tasks. This pilot study was conducted to evaluate non-expert human performance for the task of planning and scheduling, focusing on scheduling problems that increased in complexity based on the number of activities to be scheduled and the number of planning constraints. Nine non-expert planners were recruited to complete scheduling tasks using Playbook, a scheduling software. The results of this pilot study show that scheduling performance decreased as scheduling workload (i.e. number of activities and percent of activities with planning constraints) increased. This paper provides evidence towards developing a model for scheduling task difficulty and identifies potential implications for future automated aids for flight crew scheduling.

planning↗

NASA NTRS1988

A space station onboard scheduling assistant

One of the goals for the Space Station is to achieve greater autonomy, and have less reliance on ground commanding than previous space missions. This means that the crew will have to take an active role in scheduling and rescheduling their activities onboard, perhaps working from preliminary schedules generated on the ground. Scheduling is a time intensive task, whether performed manually or automatically, so the best approach to solving onboard scheduling problems may involve crew members working with an interactive software scheduling package. A project is described which investigates a system that uses knowledge based techniques for the rescheduling of experiments within the Materials Technology Laboratory of the Space Station. Particular attention is paid to: (1) methods for rapid response rescheduling to accommodate unplanned changes in resource availability, (2) the nature of the interface to the crew, (3) the representation of the many types of data within the knowledge base, and (4) the possibility of applying rule-based and constraint-based reasoning methods to onboard activity scheduling.

Brindle, A. F.↗

NASA NTRS2010

An Introduction to Sked

In this note I give an overview of the VLBI scheduling software sked. I describe some of the algorithms used in automatic scheduling and some sked commands which have been introduced at users requests. I also give a cookbook for generating some schedules.

Gipson, John↗

DOE OSTI2015

Development of Improved Graphical Displays for an Advanced Outage Control Center, Employing Human Factors Principles for Outage Schedule Management

The long-term viability of existing nuclear power plants in the United States (U.S.) is dependent upon a number of factors, including maintaining high capacity factors, maintaining nuclear safety, and reducing operating costs, particularly those associated with refueling outages. Refueling outages typically take 20-30 days, and for existing light water NPPs in the U.S., the reactor cannot be in operation during the outage. Furthermore, given that many NPPs generate between $1-1.5 million/day in revenue when in operation, there is considerable interest in shortening the length of refueling outages. Yet refueling outages are highly complex operations, involving multiple concurrent and dependent activities that are somewhat challenging to coordinate; therefore, finding ways to improve refueling outage performance, while maintaining nuclear safety has proven to be difficult. The Advanced Outage Control Center (AOCC) project is a research and development (R&D) demonstration activity under the LWRS Program. LWRS is an R&D program that works closely with industry R&D programs to establish technical foundations for the licensing and managing of long-term, safe, and economical operation of current fleet of NPPs. As such, the LWRS Advanced Outage Control Center project has the goal of improving the management of commercial NPP refueling outages. To accomplish this goal, INL is developing an advanced outage control center (OCC) that is specifically designed to maximize the usefulness of communication and collaboration technologies for outage coordination and problem resolution activities. The overall focus is on developing an AOCC with the following capabilities that enables plant and OCC staff to; Collaborate in real-time to address emergent issues; Effectively communicate outage status to all workers involved in the outage; Effectively communicate discovered conditions in the field to the OCC; Provide real-time work status; Provide automatic pending support notifications; Provide real-time requirements monitoring; Maximize their collective situational awareness to improve decision-making; and Leverage macro data to better support resource allocation. INL has partnered with several commercial NPP utilities to develop a number of advanced outage management technologies. These outage management technologies have focused on both collaborative technologies for control centers and developing mobile technologies for NPP field workers. This report describes recent efforts made in developing a suite of outage technologies to support more effective schedule management. Currently, a master outage schedule is created months in advance using the plant’s existing scheduling software (e.g., Primavera P6). Typically, during the outage, the latest version of the schedule is printed at the beginning of each shift. INL and its partners are developing technologies that will have capabilities such as Automatic Schedule Updating, Automatic Pending Support Notifications, and the ability to allocate and schedule outage support task resources on a sub-hour basis (e.g., outage Micro-Scheduling). The remaining sections of this report describe in more detail the scheduling challenges that occur during outages, how the outage scheduling technologies INL is developing helps address those challenges, and the latest developments on this task (e.g., work accomplished to date and the path forward)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

NASA NTRS2017

Increasing Crew Autonomy for Long Duration Exploration Missions: Self-Scheduling

Over the last three years, we have been investigating the operational concept of crew self-scheduling as a method of increasing crew autonomy for future exploration missions. Through Playbook, a planning and scheduling software tool, we have incrementally increased the ability for Earth analog mission crews to modify their schedules. Playbook allows the crew to add new activities from scratch, add new activities or groups of activities through a Task List, and reschedule or reassign flexible activities. The crew is also able to identify if plan modifications create violations, i.e., plan constraints not being met. This paper summarizes our observations with qualitative evidence from four NASA Extreme Environment Mission Operations (NEEMO) analog missions that supported self-scheduling as a feasible operational concept.

crew autonomy↗

NASA NTRS2017

Increasing Crew Autonomy for Long Duration Exploration Missions: Self-Scheduling

Over the last three years, we have been investigating the operational concept of crew self-scheduling as a method of increasing crew autonomy for future exploration missions. Through Playbook, a planning and scheduling software tool, we have incrementally increased the ability for Earth analog mission crews to modify their schedules. Playbook allows the crew to add new activities from scratch, add new activities or groups of activities through a Task List, and reschedule or reassign flexible activities. The crew is also able to identify if plan modifications create violations, i.e., plan constraints not being met. This paper summarizes our observations with qualitative evidence from four NASA Extreme Environment Mission Operations (NEEMO) analog missions that supported self-scheduling as a feasible operational concept.

planning and scheduling↗

NASA NTRS2012

Automating Mid- and Long-Range Scheduling for NASA's Deep Space Network

NASA has recently deployed a new mid-range scheduling system for the antennas of the Deep Space Network (DSN), called Service Scheduling Software, or S(sup 3). This system is architected as a modern web application containing a central scheduling database integrated with a collaborative environment, exploiting the same technologies as social web applications but applied to a space operations context. This is highly relevant to the DSN domain since the network schedule of operations is developed in a peer-to-peer negotiation process among all users who utilize the DSN (representing 37 projects including international partners and ground-based science and calibration users). The initial implementation of S(sup 3) is complete and the system has been operational since July 2011. S(sup 3) has been used for negotiating schedules since April 2011, including the baseline schedules for three launching missions in late 2011. S(sup 3) supports a distributed scheduling model, in which changes can potentially be made by multiple users based on multiple schedule "workspaces" or versions of the schedule. This has led to several challenges in the design of the scheduling database, and of a change proposal workflow that allows users to concur with or to reject proposed schedule changes, and then counter-propose with alternative or additional suggested changes. This paper describes some key aspects of the S(sup 3) system and lessons learned from its operational deployment to date, focusing on the challenges of multi-user collaborative scheduling in a practical and mission-critical setting. We will also describe the ongoing project to extend S(sup 3) to encompass long-range planning, downtime analysis, and forecasting, as the next step in developing a single integrated DSN scheduling tool suite to cover all time ranges.

scheduling↗

NASA NTRSDate not supplied

Evaluation of Self-Scheduling Exercises Completed by Analog Crewmembers in NASA's Human Exploration Research Analog (HERA)

NASA human spaceflight missions are inherently dynamic and require frequent scheduling changes in order to adapt to changing mission priorities and objectives. Tactical level changes to the mission plan are traditionally made by a team of expert planners and operations specialists on the ground. However, astronauts are expected to execute missions more autonomously during future long duration missions. Astronauts will need to take on some of the responsibility of managing their own schedule while still abiding by the numerous constraints required by human spaceflight operations. This paper summarizes salient elements of crew performance in NASA’s Human Exploration Research Analog Campaign 3. Analog crewmembers completed a series of self-scheduling exercises to evaluate Playbook’s usability towards enabling self-scheduling without support from ground control. Playbook is a self-scheduling software tool designed and developed by our team. We also investigated how to best communicate self-scheduling tasks and constraints to the crew in order to facilitate efficient self-scheduling during isolation in a realistic environment. Our analysis identified that 30 minutes was sufficient to complete complex self-scheduling tasks. Our evaluation also identified differences between individual and collaborative performance; analog crewmembers completed self-scheduling exercises more quickly as a team as opposed to individually and reported lower subjective difficulty ratings overall.

HERA↗

NASA NTRS2012

Automating Mid- and Long-Range Scheduling for the NASA Deep Space Network

NASA has recently deployed a new mid-range scheduling system for the antennas of the Deep Space Network (DSN), called Service Scheduling Software, or S(sup 3). This system was designed and deployed as a modern web application containing a central scheduling database integrated with a collaborative environment, exploiting the same technologies as social web applications but applied to a space operations context. This is highly relevant to the DSN domain since the network schedule of operations is developed in a peer-to-peer negotiation process among all users of the DSN. These users represent not only NASA's deep space missions, but also international partners and ground-based science and calibration users. The initial implementation of S(sup 3) is complete and the system has been operational since July 2011. This paper describes some key aspects of the S(sup 3) system and on the challenges of modeling complex scheduling requirements and the ongoing extension of S(sup 3) to encompass long-range planning, downtime analysis, and forecasting, as the next step in developing a single integrated DSN scheduling tool suite to cover all time ranges.

Deep Space Network↗

NASA NTRS2015

Integrating Human Performance Measures into Space Operations: Beyond Our Scheduling Capabilities?

Current planning and scheduling software tools for International Space Station (ISS) support different flight controller teams as they plan daily space operations. Planning and scheduling tools capabilities include integrating digitized ISS state inputs, evaluating their expected future states, and propagating them over time. Extensive, custom-made computational models of operations, of objectives, and of operational constraints help ISS flight controllers identify where scheduled events violate constraints. Based on the current capabilities of these tools, this paper proposes how human performance measures could be better integrated into planning and scheduling tools for space mission operations. Future integration of human performance measures could be applied to state inputs (in this case, the astronaut’s state) and to modeling human performance operational constraints & operational objectives (i.e., assigned activities) with parameters that are relevant to human performance measures. Gaps between the state-of-the-art for human performance modeling and planning tools for future exploration missions are identified.

space operations↗

NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗

NASA NTRSDate not supplied

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol(Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

activity planning↗

NASA NTRS2022

COCPIT: Collaborative Activity Planning Software for Mars Perseverance Rover

Since landing on the Martian surface, the Perseverance rover has relied on a distributed team to generate commands for exploring its new environment each sol (Martian day). The team uses a complex suite of software tools to accomplish this challenging task in time for the next window of opportunity to send commands to the rover. A key piece of this software ecosystem is COCPIT (Component-based Campaign Planning, Implementation, and Tactical). COCPIT is part of the next generation of planning and scheduling software tools developed by NASA's Jet Propulsion Laboratory in partnership with NASA's Ames Research Center. COCPIT is a web-based application that allows users to collaboratively view and update the Perseverance rover's activity plans, continuously verify that the plan satisfies constraints, assign targets for directing scientific instruments, document science intent, and model power and data resources. Mars Surface Operations requires diverse expertise from team members within the Engineering, Science, Robotic, and Instrument Operations groups, distributed across North America and Europe. In order to improve efficiency and reduce risk, all teams are able to review and edit their activities simultaneously and see the effects on the plan in its entirety. As part of the Ground Data System (GDS) tool suite, COCPIT is responsible for the activity plan. It provides specialized views that allow operators to understand where there may be room for additional observations, see whether any planning constraints are being violated, and confirm that energy usage and data generation are within the defined limits. It contains details such as which filters a camera will use for a given observation, what the resolution of the images should be, where to store the data onboard, and how long the observation is expected to take. It predicts when specific data will be downlinked from the rover to a passing orbiter, so that the team knows when to expect that data on Earth for evaluation in future planning. Ultimately the information from the COCPIT plan is translated to sequences that will be bundled and radiated to Perseverance for execution. The COCPIT tool is used throughout all planning phases.

Kanefsky, Bob↗