NASA's Kennedy Space Center (KSC) is working with Stottler Henke to improve KSC's Ground Processing (GP) scheduling. The solution called, Aurora-KSC, has been designed, developed and deployed at KSC to automate a large amount of Kennedy Space Center's planning, scheduling, and execution decision-making. Aurora-KSC leverages Aurora, the world's most intelligent scheduling framework; Aurora itself originated in part from many earlier NASA-funded efforts and has been utilized by NASA for some of its most complex scheduling challenges, including the scheduling of the maintenance, repair & overhaul (MRO) of the Space Shuttle during its tenure. Aurora-KSC expands on this foundation, enhancing and extending Aurora for improved generalization and adaptability. This includes an interface with Primavera P6 and Microsoft Project so project information already available in these formats can benefit from Aurora-KSC. This allows KSC to realize significant efficiency improvements in several different areas. Aurora-KSC also includes adaptive execution, that is, executing the scheduled activities/procedures intelligently as actual execution actually deviates from the original schedule. Aurora-KSC is available to the wider NASA community to provide its many benefits to the rest of NASA. Aurora-KSC is being applied to several problems at KSC relating to Ground Processing (GP). The delivered application improves the scheduling of Space Launch System (SLS) Processing and verification & validation (V&V) activity, including reduced turnaround time in response to changes and what-ifs, and more optimal schedules. This paper reviews the goals that lead to the development of Aurora-KSC, including background on the pre-existing proven technologies that were leveraged. The application to NASA challenges will be discussed with benefits to date. Finally, the benefits of leveraging Aurora-KSC for other NASA applications will be discussed.


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    Titel :

    Intelligent scheduling at NASA: Application to ground operations at Kennedy Space Center


    Beteiligte:
    Xu, Steven (Autor:in) / Stottler, Richard (Autor:in) / Richards, Robert (Autor:in)

    Erschienen in:

    Erscheinungsdatum :

    2017-03-01


    Format / Umfang :

    2991096 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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