CONFIG 3 is a prototype software tool that supports integrated conceptual design evaluation from early in the product life cycle, by supporting isolated or integrated modeling, simulation, and analysis of the function, structure, behavior, failures and operation of system designs. Integration and reuse of models is supported in an object-oriented environment providing capabilities for graph analysis and discrete event simulation. Integration is supported among diverse modeling approaches (component view, configuration or flow path view, and procedure view) and diverse simulation and analysis approaches. Support is provided for integrated engineering in diverse design domains, including mechanical and electro-mechanical systems, distributed computer systems, and chemical processing and transport systems. CONFIG supports abstracted qualitative and symbolic modeling, for early conceptual design. System models are component structure models with operating modes, with embedded time-related behavior models. CONFIG supports failure modeling and modeling of state or configuration changes that result in dynamic changes in dependencies among components. Operations and procedure models are activity structure models that interact with system models. CONFIG is designed to support evaluation of system operability, diagnosability and fault tolerance, and analysis of the development of system effects of problems over time, including faults, failures, and procedural or environmental difficulties

Fleming, Land

Malin, Jane T.

Ryan, Dan

English

NASA Technical Reports Server

COMPUTER-AIDED OPERATIONS ENGINEERING 
WITH INTEGRATED MODELS OF SYSTEMS AND OPERATIONS 
Jane T. Malin 
NASA 
Automation and Robotics Division 
Johnson Space Center, ER2 
Houston, TX 77058 
S*c. - e;. 
Dan Ryan 
MITRE 
Johnson Space Center, ER2 
Houston, TX 77058 
Land Fleming 
Lockheed Engineering C Sciences Co. 
Houston, TX 77058 
ABSTRACT 
CONFIG 3 is a prototype software tool that supports integrated conceptual design evaluation 
from early in the product life cycle, by supporting isolated or integrated modeling, simulation, 
and analysis of the function, structure, behavior, failures and operation of system designs. 
Integration and reuse of models is supported in an object-oriented environment providing 
capabilities for graph analysis and discrete event simulation. Integration is supported among 
diverse modeling approaches (component view, configuration or flow path view, and 
procedure view) and diverse simulation and analysis approaches. Support is provided for 
integrated engineering in diverse design domains, including mechanical and electro-mechanical 
systems, distributed computer systems, and chemical processing and transport systems. 
CONFIG supports abstracted qualitative and symbolic modeling, for early conceptual design. 
System models are component structure models with operating modes, with embedded time- 
related behavior models. CONFIG supports failure modeling and modeling of state or 
configuration changes that result in dynamic changes in dependencies among components. 
Operations and procedure models are activity structure models that interact with system 
models. CONFIG is designed to support evaluation of system operability, diagnosability and 
fault tolerance, and analysis of the development of system effects of problems over time, 
including faults, failures, and procedural or environmental difficulties. 
INTRODUCTION 
The core of engineering design and evaluation focuses on analysis of physical design. Thus, 
today’s computer-aided engineering software packages often do not provide enough support 
for conceptual design early in the life cycle or for engineering for operahon, fault management, 
or supportability (reliability and maintainability). Benefits of engineering for operations and 
supportability include more robust systems that meet customer needs better and that are easier 
to operate, maintain and repair. Benefits of concurrent engineering include reduced costs and 
shortened time for system development. Integrated modeling and analysis of system function, 
structure, behavior, failures and operation is needed, early in the life cycle. 
Conventional system modeling approaches are not well suited for evaluating conceptual 
designs early in the system life cycle. These modeling approaches require more knowledge of 
geometric or performance parameters than is usually available early in design. More abstracted 
models can support early conceptual design definition and evaluation, and also remain useful 
for some later analyses. Component-connection models provide one such useful abstraction, 
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and discrete events are another. Discrete event simulation technology combines both 
abstractions, for evaluation of conceptual designs of equipment configurations in operations 
research (3). COPFIG uses these abstractions, with some enhancements, to define and 
evaluate conceptual designs for several types of systems. 
The initial CONFIG project goal was to support simulation studies for design of automated 
diagnostic software for new life-support systems (9). The problem was to design an "expert 
system" on-line troubleshooter before there was an expert. The design engineer could use a 
model of the system to support what-if analyses of failure propagation, interaction, 
observability and testability. This activity is similar to Failure Modes and Effects Analysis (3, 
but uses comparative simulations of failure effects to develop diagnostic software. 
Conventional simulation software was not up to this challenge, but discrete event simulation 
software has been. CONFIG supports the use of qualitative models for applying discrete event 
simulation to continuous systems. 
A major design goal for CONFIG is to support conceptual design for operations and safety 
engineering. Major tasks in conceptual design are design definition, evaluation (by simulation 
and analysis) and documentation. Operations engineering focuses on the design of systems 
and procedures for operating, controlling and managing the system in normal or faulty 
conditions. Safety engineering focuses on prevention of hazardous effects and conditions in 
the physical system or its operation, In these types of engineering, complex interactions and 
interfaces among system components and operations must be a focus. 
Another design goal of COPFIG is to bridge the gaps between physical design engineering and 
other types of engineering. Component-connection representations are well suited for 
modeling and defining physical system designs (as structures of interacting components) and 
operations designs (as structures of interacting actions), as well as interactions between system 
components and operational actions. Discrete event models have been used for this type of 
modeling for queueing and scheduling problems, but can be extended to support conceptual 
modeling in operations and safety engineering. This type of modeling is also compatible with 
systems engineering function diagrams (1). 
CONFIG 3 
The project approach has been to incrementally integrate advanced modeling and analysis 
technology with more conventional technology. The prototype integrates qualitative modeling, 
discrete event simulation and directed graph analysis technologies for use in analyzing normal 
and faulty behaviors of dynamic systems and their operations. The prototype has been 
designed for modularity, portability and extensibility. A generic directed graph element design 
has been used to standardize model element designs and to promote extensibility. This directed 
graph framework supports integration of levels of modeling abstraction and integration of 
alternative types of model elements. 
Enhanced Discrete Event Simulation Capabilities 
In traditional discrete event modeling and simulation, state changes in a system's entities, 
"events", occur discretely rather than continuously, at nonuniform intervals of time. 
Throughout simulation, new events are added to an event list that contains records of events 
and the times they are scheduled to occur. Simulation processing jumps from one event to the 
next, rather than occurring at a regular time interval. Computation that results in creation of 
new events is localized in components, which are connected in a network. Any simulation run 
produces a particular history of the states of the system. Statistical simulation experiments, 
using random variables in repeated simulation runs, are used to compare design alternatives. 
456 
To enhance this discrete event simulation approach to accommodate continuous systems, a 
number of new concepts and methods were developed. These include component models with 
operating modes, types of links connecting components ("relations" and "variable clusters"), 
state transition structures ("processes"), methods for representing qualitative and quantitative 
functions ("process language"), and a new simulation control approach. 
Digraph Analysis Capabilities 
The CONFIG Digraph Analyzer (DGA) makes graph analysis techniques available for 
evaluating conceptual designs of systems and their operations. The DGA is based on 
reachability search, and is implemented generically for application to the many types of graph 
data structures in CONFIG. DGA can support analyses of completeness, consistency and 
modularity. Analysis of failure sources and impacts can be done by tracing the paths fiom a 
given failure. 
System Modeling 
Devices are the basic components of a CONFIG system model. Relations are basic connectors 
for building topological model structures with devices. Device behavior is defined within 
operating and failure Modes, which contain mode dependent and mode transition Processes. 
Modes are connected together in a mode transition digraph which delineates the transition 
dependencies among the individual modes. A Thermal Bus System model, shown in the 
Figure, illustrates a CONFlG model of a system of connected devices (heat exchangers, 
valves, sensors, accumulator, etc.) for removing heat. The behavior of each device depends 
on its current mode and on changes in its input received from other devices via relations or via 
the global flow path manager. 
Device Processes define changes in device variables as events with time delays, which are 
conditionally invoked and executed during a simulation. Processes define time-related 
behavioral effects of changes in device input variables, both direction of change and the new 
discrete value that will be reached, possibly after a delay. Faults and failures can be modeled in 
two distinctly diffmnt ways. Failure modes can be used to model device faults. Mode- 
transition processes can be used to model latent failures or triggering failures that prevent or 
cause mode changes. Relations connect devices via their variables, so that state changes can 
propagate along these relations during simulations. Related variables are organized into 
variable clusters, to separate types of relations by domain (e.g., electrical vs. fluid 
connections). Relations can also be used to make connections between system Devices and 
Activities in operations models. 
Flow Path Modeling 
Flow is a property of many systems, whether the substance flowing is a liquid or information. 
There are two difficulties in modeling flows with local device processes. First, flow is a global 
property of the topology of the modeled system and the substances flowing within it. Second, 
while dynamic changes in system structure and flow can occur during operations, process 
descriptions involving flow must often rely on assumptions of static system topology. These 
factors would limit the reusability of device descriptions to a limited set of system structures. 
A flow-path management module (FPMM) has been implemented to address these problems. 
The FPMM is separate from the module implementing local device behavior, but the two 
modules are interfaced via flow-related state variables in the devices. When FPMM is notified 
during simulation of a local change in device state, it recomputes the global effects on flows 
produced by the local state change. The FPMM then updates the state of flow in all affected 
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devices. This design permits the user to write reusable local device process descriptions that 
do not depend on any assumptions concerning the system topology. 
FPMM uses a simplified representation of the system, as a collection of aggregate objects, or 
"circuits." Further abstraction is achieved by identifying serial and parallel clusters in the 
cireuit (6). In many cases, configuration determination alone is sufficient to verify flow/effm' 
path designs, or to establish flow paths for a continuous simulation, for reconfiguration 
planning, and for troubleshooting analysis (see Ref. [2] on cluster-based design of procedures 
for diagnosis, test, repair and work-around in a system). 
Operations modeling 
Activities are the basic components of a CONFIG operations model, and are connected together 
in action structures with Relations. They represent procedures or protocols that interact with 
the system, to control and use it to achieve goals or functions. Each activity model can include 
specifications for what it is intended to achieve or maintain. Activity behavior is controlled in a 
sequence of phases, ending in an evaluation of results. Activity behavior is defined by 
processes that model direct effects of actions, or that control device operation and mode 
transitions to achieve activity goals. Relations define sequencing and control between activities 
and connect Devices with device-controlling Activities. 
Operations models are designed to support operation analysis with procedure models. These 
models are designed to support analysis of plans and procedures for nominal or off-nominal 
operation. The procedure modeling elements are designed for reuse by intelligent replanning 
software, and for compatibility with functional modeling in systems engineering. 
Model Development and Integration Capabilities and Approach 
CONFIG provides intelligent automation to support nonprogrammer and nonspecialist use and 
understanding. CONFIG embeds object-oriented model libraries in an easy-to-use toolkit with 
interactive graphics and automatic programming. 
CONF'IG provides extensive support for three separable yet tightly integrated phases of user 
operation during a modeling session: Library Design, Model Building, and Simulation and 
Analysis. This includes a graphical user interface for automated support of modeling during 
each of the phases including the development of object-oriented library element classes or 
templates, the construction of models from these library items, model inspection and 
verification, and running simulations and analyses. 
The integration between the phases enables an incremental approach to the modeling process. 
analyses can be repeatedly and rapidly incoprated by the user into an . Support for these phases as separate user activities fosters the 
achievement of concurrent engineering goals. Different users can define library elements, build 
models, and analyze models at different times depending on area of expertise and availability of 
resources. Support for the model building phases spans all types of modeling that can be 
performed in CONFIG including component structure, behavior and flow, and activity goals 
and structure. 
Hosting 
CONFIG is implemented in software that is portable to most Unix work stations. The 
Common LISP Object System (CLOS) is a highly standardized language, with compilers for 
most of the commonly available work stations. The user interface was implemented using the 
Common LISP Interface Manager (CLIM), another standardized tool built on CLOS. 
459 
CONCLUSIONS 
CONFIG is designed to model many types of systems in which discrete and continuous 
processes occur. The CONFIG 2 prototype was used to model and analyze: 1) a simple two- 
phase thermal control system based on a Space Station prototype thermal bus, 2) a 
reconfigurable computer network with alternate communications protocols, and 3) Space 
Shuttle Remote Manipulator System latching and deployment subsystems (7). The core ideas 
of CONFIG have been patented (8). CONFIG 3 has added capabilities for graph analysis and 
for modeling operations and procedures. 
The CONmG prototype demonstrates advanced integrated modeling, simulation and analysis 
to support integrated and coordinated engineering. CONFIG supports qualitative and symbolic 
modeling, for early conceptual design. System models are component structure models with 
operating modes, with embedded time-related behavior models. CONFIG supports failure 
modeling and modeling of state or configuration changes that result in dynamic changes in 
dependencies among components. Operations and procedure models are activity structure 
models that interact with system models. The models support simulation and analysis both of 
monitoring and diagnosis systems and of operation itself. CONFIG is designed to support 
evaluation of system operability, diagnosability and fault tolerance, and analysis of the 
development of system effects of problems over time, including faults, failures, and procedural 
or environmental difficulties. 
ACKNOWLEDGEMENTS 
The authors wish to thank Bryan Basham, Leslie Ambrose, Ralph Krog, Debra 
Schreckenghost, Brian Cox, Daniel Leifker and Sherry Land for their contributions to 
CONFIG design and implementation. 
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Computer-aided operations engineering with integrated models of systems and operations

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