The Spacelab Data Processing Facility (SLDPF) is an integral part of the Space Shuttle data network for missions that involve attached scientific payloads. Expert system prototypes were developed to aid in the performance of the quality assurance function of the Spacelab and/or Attached Shuttle Payloads processed telemetry data. The Spacelab Input Processing System (SIPS) and the Spacelab Output Processing System (SOPS), two expert systems, were developed to determine their feasibility and potential in the quality assurance of processed telemetry data. The capabilities and performance of these systems are discussed

Basile, Lisa R.

Kelly, Angelita C.

English

NASA Technical Reports Server

N88:16394
SPACEiAB DATA PROCESSING FACILITY (SLPDF)
QUALITY ASSS_ANCE EXPERt SYSTEMS
DEVELOPMENT
Lisa Basile (NASA/C_FC/Code 564)
Angelita C. Kelly (NASA/C_FCIOode 564)
Goddard Spaoe Flight Center
Greenbelt, MD 20771
ABSTRACT
The Spacelab Data Processing Facility (SLDPF) is an integral part
of the Space Shuttle data network for missions that involve
attached scientific payloads. The SLDPF has developed expert
system prototypes to aid in the performance of the quality
assurance (QA) function of Spacelab and/or Attad%ed Shuttle
Payloads (ASP) processed telemetry data. The SLDPF functions
include the capturing, quality monitoring, processing, aocount-
ing, and forwarding of data frum Spacelab and ASP missions to
various user facilities. The SLDPF consists of twD functional
elements: the S_o_ Input P=x_i_ System (SIPS) and the
S_c_ Outp_ _ing _ (SOre). The t_ _
prototypes were developed to determine their feasibility and
potential in the quality assurance of processed telemetry data.
The SIPS expert system, Knowledge System Prototype, (KSP), uses
an IBM PC/AT with the oummercial expert system shell OPS5+.
Expert knowledge (frum SIPS experts) emulating the duties of
quality assurance analysts was implemented. In an interactive
mode, a SIPS analyst responds to queries resulting in instruc-
tions and decisions governing the reprocessing, releasing or
further analysis/troubleshooting of data. Released data is
forwarded for further processing on the SOPS Sperry 1100/82. The
data are edited, time ordered with overlapping data removed,
d_ted, and quality checked before release to the user.
The SOPS QA analysts isolate problems and select the appropriate
action: either acoept the data or request the data to be reproc-
essed. The SOPS expert system emulates this prooess by utilizing
an expert system shell, CLIPS, and the Macintosh personal
cumputer. To date, these prototypes indicate potential benefi-
cial results; e,g., increase analyst productivity, decrease the
burden of tedious manual analysis, provide consistent evaluations
of data, provide concise historical records, provide training for
new analysts, and expedite the operational training of Spacelab
analysts. The logic implemented in the prototypes, the limita-
tions of the personal computers utilized, and the degree of
accessibility to input data have led to an operational configura-
tion to be implemented on a SUN 3/160 Workstation. This config-
uration is currently under development and on completion will
enhance the efficiency, both in time and quality, of releasing
Spacelab/ASP data.
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https://ntrs.nasa.gov/search.jsp?R=19880007012 2020-03-20T07:46:20+00:00Z
_ON:
The SI/)PFprocesses payload data from Spaoelab and ASP
missions. The SLDPFfunctions include the capture, quality
monitoring, processing, accountir_, and shipping of data to
users. The SLDPFis oomposedof two functional elements: the
SIPS and the SOPS. In SIPS, }_/_ d%annel 2 and/or channel 3
data are captured onto high-density tapes (HUEs). _he primary
functions of SIPS are the realtime capture, the monitoring of
data for quality and status ooordination with the Spaoelab
external interfaces suc_ as the Spaoelab Payload Operations
Occfcrol Center (POOC), the Mission Oontrol Center (MOC), and the
Network elements. See Figure below. _he data captured, _ud-
ing playback and direct access channel data, are processed to
produce Spacelab Experiment Data Tapes (SEDI_) and/or Space/ab
znput/oucputData Tapes (SIDe). To assurecompletenessand high
quality of SIPS prooessing, analysts currently perform quality
assurance and data a_ (QA/[_) analysis by the manual
evaluation of_ Spaoelab Quality and _ Records (SOARs)
aided with information from Spaoelab reports and logs. 9_e
results of the QA analysis determine the release of SEUgs, SIDI_
and Spacelab Quality and Accounting Tapes (SORTs) to the SOPS or
to other users. Additionaldata processingis performedby the
soPs. _e data are edited, time ordered with uverlap remm._,
_ted, quality_, and _ to users. _heQA/DA
analysis is a manual process of evaluating and correlating
information from various reports and logs to determine the
quality of the data and its status: release or rep_.
I Ksc
PREMISSIONINTEGRATION
TEST DATA
(HIGH - DENSITY TAPES)
r.. ....
INASCOM
I
PREMISSION
I o TIMELINE
I o HRDM
_FORMAT
t ........ .
SiPS
e DATA CAPTURE
e DEi,IULTIPLEXING
I DATA QUAUTY
MONITORING
e DATA ACCOUNTING
REAL-TME
TIMELINEIDATA l _
QUALITY STA'nJS 'p_
[PROJECTMANAGEMENTI_
............ t_uJ_E?2-l
SLOPF
MANAGEMENT
(CODE560} L....
--<D----
UNED_EO DI_AL
QU_ 1
ACCOUNTING
PREMISSION
I/0 DATA BASE
SOPS
e EDITINQ I FORMATI3NO
e TIME ORDERIHO &
OVERLAP REMOVAL
o I/0 DECOM
e ANCILLARY PROCESSING
• DATA QUALITY
MONITORINO
e DATA ACCOUNTING
,JSER TAPES
Io EXPERIMENT
!: COMPUTER I/0ANCILLARY
......................................... I
u.RTAPES _'_ POSTMI.,O.
o UHEDITED DIGITAL _.. /' o PO$TFUOHT ATTITUOE &
o QUALrI_' & ACCOUHT_IG "1[-- TRAJECTORY HISTORY
L--I o NOHDIGITAL | o ORBITER ANCILLARY
SLDPF INTERFACES
182
Expert system applications in the Information Processing
Division were first considered for their potential to expedite
the SLDPF operations, in particular, the QA/[I% analyst functions
of both the SIPS and the SOPS. The extremely large volume of
data from one mission and the short turnaround requirement for
delivery to users often makes the QA/[_ task demanding and
tediously repetitive. The objective of the c__rational expert
systems is to assist the analyst by making decisions and suggest-
ing logical analysis paths based on given data quality informa-
tion. The strategy formulated to accomplish the prototypes was
to use commercial expert system shells, code the QA/E_ knowledge
bases within the shells and implement them on persQnal cQmpu-
ters. The SIPS KSP uses the OPS5+ Develc_ System with a
C language interface installed on an IBM PC/AT. The SOPS Expert
System (ES) prototype was implemented with the expert system
building tool CLIPS and an in-house-written interface on an Apple
Macintosh.
SIPS KSP:
The SIPS KSP is designed to emulate the performance of
experienced SIPS QA/DA analysts in the evaluation of Spacelab
data quality and accounting information. This function is
currently performed through the examination of data quality and
aoo_mting report.
The first task was to gather the analysis expertise of the
QA/DA analysts to determine that this area was a practical
application for an expert system. The scope of the initial
effort was restricted due to the extensiveness of the application
and the limitations of the prototype hazrlware and software
configuration. Three stages of analysis were established: ini-
tial data evaluation, oumparison of initial and redo prooessing
run data, and data _. Ead_ can stand alone logically but
need aooess to the data and decisions of the _. The use of
a database to store data quality and accounting information as
well as the decisions of each stage allows the expert syste_ to
be divided into independent modules whiQh run with the available
memory of the prototype configuration. As each module runs,
pertinent data and decisions are written to report files from
whid_ database updates and printed sunmary reports are gener-
ated. The code for database oontrol, the Front End module,
grew to include database creation and loading, data validation,
data maintenance, data selection, expert system module selection,
and expert system report selection.
_he rule-based expert system tool OPS5+ was used to develop
the knowledge base for the KSP. The knowledge elements (rules)
are in the form "IF <oondition(s)> THEN <action(s)>." The KSP
Stage i: Initial Data Evaluation knowledge base oonsists of 201
rules; Stage 2: Cumparison of Initial and Redo Processing Runs,
130 rules. Completion of Stage 3: Data Trends has been deferred
to direct the use of _ to the operational system require-
ments definition.
183
The Front End interfaoes with the user in the form of
selection and input screens. Required responses are limited to
one-keystroke if default values are selected. Page forward and
backward options are provided. Data input/viewing screens are
provided to allow ir_ and data maintenance. Stage 1 interfaces
with the user in the form of a running dialog. It is initiated
by loading and initializing the evaluation program after entering
the OPS5+ environment. Data not directly downloaded is obtained
by %hser-query; responses are limited to one keystroke. Stage 1
generates a summary report printed on user request. The Stage 2
program, after being loaded and initialized, uperates without
intervention frum the user; both a summary report and a detailed
report are created and printed on user request.
SOPS ES _:
The knowledge base for the SOPS ES prototype was developed
using the nne-bas_ expert system language cLn_. All k_wledge
elements are represented in the form "IF <ocrdition(s)> THEN
<action(s)>." The knowledge base can be logically divided into
sets called knowledge islands consisting of rules to diagnose a
prablem, drive the user interface, and to retrieve data specific
to that knowledge island. A knowledge island can be modified or
replaced to reflect a p_ c_ange in SOPS without affecting
the other knowledge islands; this simplifies the modification
process. The prototype consists of four knowledge islands: Run
St_ Early, Data Gap Between Files, Data Coverage, and Data
Quality. Each was implemented only to the detail required to
realistically demonstrate the feasibility of an operational SOPS
ES. The knowledge islands will be expanded for future implemen-
tation to include particulars uncovered by this pro_.
The SOPS ES prot_ uses many of the standard features for
applications running on the Apple Macintosh. _%e features
include the use of multiple windows, pull-down menus, and dialog
boxes. Dialog boxes and windows may contain buttons, scroll
bars, or space for the analyst to type in additional information
called a text field. Whenever possible, the ES will set a
default value for the text fields; if the analyst changes the
value of a text field, the ES performs a consis_ check to
prevent the entering of unacceptable values. The primary windows
viewed by the analyst are the Transcript, Timeline, and Conclu-
sion windows. The Transcript window maintains a log of the ES
session containing all questions asked by the ES, the analyst's
responses, all reccmmendations frum the ES, and any analyst-added
cumments. The Timeline window displays the run in a graphical
format with the ES's current focus of attention flagged. The
Conclusion window displays the conclusions reached (rules fired)
by the ES. All windows can be printed upon oumpletion of the ES
session.
184
CONCLUSIONS:
The prototypes show that the expert systems offer many
benefits. _hey are fast. _%ey are cons_. _he expertise of
the most experi_ staff members is now made available to all.
_he prc_ can act as training tools when refined to a
detailed level. _uuu_ut develqm_nt, ways in which current
prooedures could be further autumated to increase accessibility
to information, to improve processing speed, and to decrease the
monotony of repetitious tasks were identified. Also, areas in
the expert systems' c_n uperation will be streamlined to make the
expert system concept not only workable but cperaticr_lly practi-
cal.
_%e goal of the expert system prototypes was to define the
design and oQnfiguration of expert syst_s in the mission
envY. These new operational systems will be larger, more
efficient, and more automatic, incorporating the capabilities
indicated by, but not present in the pzotot-ypes. Both the sIPS
and SOPS operational expert system cunfigurations will use the
same hardware, the SUN 3/160 workstation, and software, CLIPS
with C language interfaces, for ccnsis_ and maintainability.
NetwDrk interfaces will be established to autumatically transfer
necessary information frum the existing SIPS and SOPS mainframes
to the workstations for the expert systems' analysis. It is
planned that this configuration will be c_/ational by December
1988, in time to support ASTRO-I, the first of several scheduled
SLDPF missions in the post-(_mllenger period.
project could not have been successful Without the
ountributior_ of the follcwing persmm_l: Troy Ames (GSFC/Oode
522), Ellen Herring (formerly an SLDPF/Oode 564 mission manager),
Janice Watson, William Dallam, Michael Alvarez, Franz Berlin,
Warren Case, Michael Garner, James Pizzola, and Beth Pum_
(all of _). _he SLDPF personnel also wish to acknuwledge
Joe Bishop (NASA Head_/Oode TS) for his continuing support
in the enhancement of the SLDPF.
185


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