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RASSP Integrated System Tools Appnote

3.0 Technical Description

3.1 RASSP Systems Engineering Process

3.1.1 Overview

The RASSP design process consists of the signal processing system-level design, architecture selection and detailed hardware/software design as shown in Figure 3-1. The inputs to the RASSP design process are the physical, functional and performance requirements for the signal processing system. These requirements typically are passed down from the platform system level design which is performed prior to the signal processor design. During the signal processing system design, the requirements are captured and analyzed, the functional behavior of the system is defined and the requirements and functions are allocated to the major subsystems of the signal processor. Hardware/software co-design activities are performed during the architecture selection process and a virtual prototype of the system is developed. Once the processing architectures are determined, the hardware and software are developed and integrated during the detailed design process. Note that these processes are iterative in nature and that feedback between the processes is used whenever required. The focus of this section of the application note is to describe the RASSP systems engineering process.

Figure 3 - 1: RASSP Design Methodology

It is recommended that Section 3.1.2 be read to understand what is accomplished during the signal processing system design. Section 3.2.1 entitled "RASSP Integrated System Tool Description Overview" should then be read next to understand the capabilities of these integrated tools. One can then read Section 3.2.2 for more details about the individual tools and Section 3.2.3 for details on their integration. However, both of these sections may be skipped and the reader can move directly to Section 3.3 to learn the benefits of using the integrated toolset. The reader can then progress to Section 4 to see an example how the integrated tools are used on a typical program.

3.1.2 RASSP System Process Description

The RASSP system definition process is a front-end engineering task in which signal processing concepts that meet customer requirements are developed and top-level trade-offs are performed to determine the processing subsystem requirements. Although the same type of functional decomposition and allocation is performed as in the traditional design process, several significant RASSP extensions have been developed which lead to shorter design cycles. Emphasis is placed on understanding the life cycle impact of early design decisions in the RASSP process. Each member of the integrated product development team participates in the system-level tradeoffs to ensure that the complete life cycle is considered during the design process. Model year architecture concepts are used in RASSP designs to ensure that the signal processor can easily be upgraded to support its entire life cycle. Emphasis is placed on making early design decisions so prototyping activities can begin early in the program to reduce high-risk elements. The output of the system definition process is a set of executable specifications that have the requirements for each processing subsystem in an executable form. The executable specifications support the RASSP concept of reuse and minimize errors due to human interpretation. Traceable system requirements are passed via executable specifications from the system definition process to the architecture design process. As the design progresses, the ability to meet requirements is passed back to the system-level simulations so the impact of lower-level trade-offs are analyzed.

The system definition process is shown in Figure 3-2. The inputs to the system definition process include all the customer documentation detailing the processing system specification. Typical signal processing requirements include system mode functional descriptions (search, track, waveforms and algorithms), performance requirements (processing gain, timeline and precision requirements), physical constraints (size, weight, power, cost, reliability, maintainability, testability, etc.), and interface requirements. Top-level tradeoffs are performed by the multidiscipline product development team to determine how the system will operate and what set of subsystems are required. System level functional and timeline simulations are developed to characterize system behavior. The system definition process is iterative, requiring constant interaction with the customer and product development team. The outputs of the system definition process include the functional, performance and physical requirements for each signal processing subsystem.

Figure 3 - 2: System Definition Process

As the subsystem designs progress, key system-level simulations are re-run to ensure that performance is maintained. The subsystem requirements are periodically monitored to make sure that the development risks are appropriately balanced among the subsystems. There is a feedback path back to the system-level from each subsystem design which is used whenever cost-effective subsystem designs cannot be obtained. When subsystem requirements can not be met, analyses are performed to determine a refined partitioning of the system requirements.

3.1.2.1 Requirements Analysis

During requirements analysis a user need is converted into a set of system requirements that satisfies that need. Customer documentation is reviewed and discussions are held with the customer and user to refine the purpose and manner in which users will operate the system. The focus of system requirements analysis is to determine what the system is to do and how the system is to be used. External interfaces to the system are identified. Methods to verify each requirement statement are determined. This process iterates with the functional analysis and system partitioning efforts to assess feasibility and to structure the requirements cost-effectively. This iteration also makes the verification process more accurate and cost effective by eliminating ambiguity in the requirement statements.

The tasks performed during requirements analysis are summarized in Table 3-1. A complete set of customer documents must be used to determine the requirements since the contractor must understand how users intend to use the system. The system is defined in terms of its modes and states, functions and interfaces. Trade-offs establish alternative performance and functional requirements to meet customer needs. Any potential conflicts between the trade-off analysis results and the system requirements are resolved. A work-off plan for all TBD/TBR items that identify the responsible individual, schedule for resolution, risk analysis and key trade-offs to be performed is developed. Traceability of system requirements and decisions ensures that the trade-off decisions made in generating requirements can be tracked and that these requirements are completely and accurately reflected in the final design. Traceability is also used to assess the impact of changes at any level of the system. System requirements are examined to ensure completeness and consistency.

Obtain Relevant Information

 

System Requirements Assessment

 

System Definition


  • Obtain all relevant customer documentation
  • Discuss system requirements with customer
  • Obtain data on applicable technology
  •  
  • Assess functional & performance requirements, operational environment, system constraints & measures of effectiveness
  •  
  • Define system modes & states
  • Define system functions
  • Define system configuration items
  • Define system interfaces
  •          

    TBD/TBR Work-off Planning

     

    Requirements Traceability

     

    System Specification Generation


  • Identify responsible individual
  • Perform risk analysis
  • Develop schedule for resolution
  • Identify potential trade-offs
  • Determine resolution criteria
  • Assemble work-off plan
  • Conduct internal review
  •  
  • Capture customer requirements
  • Trace system requirements to source documents
  • Prepare traceability matrix
  • Conduct internal review
  •  
  • Analyze inputs
  • Prepare specification outline
  • Incorporate applicable documents & standards
  • Prepare preliminary specification
  • Conduct review
  • Incorporate comments
  • Place under configuration control
  • Submit for authentication
  • Table 3 - 1: Requirements Analysis Tasks

    The output of the requirements analysis task is the system specification. This specification includes the technical requirements for the system, allocates the requirements to functional areas, documents the design constraints and defines interfaces between functional areas. This specification also contains the necessary performance requirements. Essential physical constraints and requirements for application of any known specific equipment which must be included in the system are included in the specification. The specification can be in either a written format, an executable format or a combination of both formats.

    3.1.2.2 Functional Analysis

    During functional analysis, the system is decomposed into its functional elements. This analysis is performed by determining what functions are required to implement each system requirement. Functions are described by defining the inputs to the function, the algorithm performed by the function and the outputs of the function. Constraints and timing requirements are established for each function. The top-level functional behavior is modeled to ensure that the functional requirements are met.

    The tasks performed during functional analysis are summarized in Table 3-2. The functional identification task translates system requirements, customer heritage and customer rationale into functional block diagrams that are used by subsequent processes to create and evaluate system configurations. This task refines and decomposes the functions identified from the requirements analysis task. Design constraints for each functions are defined. Functional elements within the RASSP reuse library are examined to determine whether existing functional library elements can be used.

    Functional Identification

     

    Functional Decomposition


  • Analyze system requirements
  • Identify system functions
  • Develop functional block diagrams
  • Identify constraints
  • Establish performance timelines
  • Evaluate baseline for consistency and completeness
  • Perform traceability to requirements
  • Provide rationale for functional identification
  • Develop alternative functional configurations
  •  
  • Perform trade-offs to eliminate poor system configurations
  • Develop next tier functions
  • Develop next tier functional block diagrams
  • Identify next tier constraints
  • Establish next tier performance timelines
  • Perform traceability to upper tier functions and requirements
  • Provide rationale for decomposition
  • Identify new library primitive elements
  • Table 3 - 2: Functional Analysis Tasks

    Lower level functions, constraints and performance are generated during functional decomposition. This decomposition continues until the functionality can be allocated to a specific subsystem. This more detailed information is used in the subsequent partitioning and architectural trade processes. This functional analysis is performed iteratively to eliminate poor allocation decisions as soon as possible. Functional elements within the RASSP reuse library are examined to determine whether existing library elements can be used at this lower level decomposition. If any of the system functions can not be represented by existing library elements, new primitives are identified for development.

    Traceability is established between each functional block and the system requirements.

    3.1.2.3 System Partitioning

    During system partitioning, candidate system configurations are defined and evaluated to determine which configurations most effectively meet the functional and system requirements. As many configurations as feasibly possible should be evaluated in enough detail to rank the alternatives. A structured method must be followed to quickly identify the feasibility of a specific configuration. The output of the system partitioning process is the set of functional, performance and physical requirements for each subsystem in the baseline configuration.

    The tasks performed during system partitioning are summarized in Table 3-3. Functions and constraints are allocated to entities in a specific candidate design during the functional allocation task. This task is completed when all functions are allocated to subsystems and all requirements and constraints are mapped through functions to subsystems. Trade-off analyses assess the risk and life cycle cost for each alternative system configuration. Design decisions and rationale must be documented as the functions are allocated. This task iterates until an allocated baseline is established. Many iterations may be needed to refine the system configuration.

    Functional Allocation

     

    Performance Verification


  • Create candidate system configurations
  • Allocate functions to configuration
  • Allocate constraints to configuration
  • Identify interfaces
  • Perform traceability to functions and requirements
  • Provide rationale for allocation
  • Identify and quantify risks
  • Identify candidate prototyping activities
  •  
  • Develop metrics
  • Develop and configure models
  • Estimate unknown parameters
  • Execute models
  • Evaluate results
  • Perform life cycle cost analysis
  • Perform reliability and maintainability assessment
  • Evaluate trade-offs to eliminate poor configurations
  • Reiterate process if completion criteria not met
  • Perform traceability
  • Develop subsystem requirements
  • Support make/buy decision for each subsystem
  • Table 3 - 3: System Partitioning Tasks

    The performance verification task supports system partitioning by providing evaluation criteria to determine which candidate configuration provides the most effective performance. This effort must consider all factors of interest to the product development team: technical performance, risk, life cycle cost, producability, supportability, testability, etc. The performance evaluation must reflect objective, demonstrable evaluation metrics and must assure the customer that sufficient candidates were considered. The behavior of candidate configurations is determined through simulation to ensure all performance requirements are met at the system level. The system partitioning process iterates with the functional allocation process until the performance of a candidate configuration meets the completion criteria established during the requirements analysis process.

    The output of the system partitioning process includes the set of functional, performance and physical requirements for each subsystem. This requirements are in the form of an executable requirement and represent the first virtual prototype for the subsystem.

    The RASSP architecture selection process transforms the processing requirements for each processing subsystem into a candidate architecture of hardware and software elements. The architecture selection process overlaps with the system definition process during the system partitioning activity. A hierarchical set of simulations is performed at each design level, and the results of these simulations are back annotated in the higher-level simulations to verify that overall performance is maintained.

    3.2 RASSP Integrated System Tools Description

    3.2.1 Overview

    The ATL RASSP team has developed a concurrent engineering environment based upon COTS tools which supports the RASSP systems engineering process. This concurrent engineering environment, which is shown in Figure 3-3, consists of Ascent Logic Corporation's (ALC)RDD-100 system engineering tool, Lockheed Martin PRICE Systems cost estimation tools and Management Sciences' (MSI) RAM-ILS toolset. RDD-100 is used to capture and analyze the requirements, to define the functional behavior of the system, to allocate the requirements and functions to the subsystems, and to provide requirements traceability. PRICE cost estimating tools are used to estimate the development, production and support costs for the processing system. The RAM-ILS tool is used to perform reliability and maintainability analyses.

    Figure 3 - 3: RASSP Integrated System Tools

    Each tool passes data to another tool through an ASCI file with the appropriate format. The types of data which are passed from one tool to another consist of the data that typically resides in that tool and can be used by the other tool. For example, system engineering data is passed from RDD-100 to the PRICE cost estimating tool. This approach eliminated the need for implementing a GUI interface for PRICE and RAM-ILS in the RDD-100 tool. The types of parameters which are passed from RDD-100 to PRICE include the equipment configuration, size, weight, power, technology and complexity factors. The development, production and support costs are calculated within the PRICE tool and these costs are back annotated into the RDD-100 data base. On the other side of the interface, the equipment configuration, allocated reliability and maintainability budgets, and cost data are passed from RDD-100 to the RAM-ILS toolset. The reliability and maintainability assessment is performed within the MSI toolset and the results of these analyses are back annotated into the RDD-100 data base. In addition, optimizations can be performed within the RAM-ILS toolset when the reliability requirements are not met and the tool can make a recommendation on how redundancy can be added in the system in the most cost effective way to meet the requirements.

    Now that you have a basic understanding of the integrated toolset, you may read Sections 3.2.2 and 3.2.3 for more detailed information on the individual tools and their integration. For a shortened version you can skip directly to Section 3.3 to read about the benefits of using these tools in a cooperative manner.

    3.2.2 Individual Tool Description

    3.2.2.1 RDD-100

    Ascent Logic Corporation's (ALC) RDD-100 is a system engineering tool used for capturing requirements, relating the requirements to a behavior model, and allocating the functionality to a physical architecture. The tool supports object-oriented analysis, stimulus response threads, and other analysis techniques. RDD-100 can be used to produce specifications at the system, segment and/or component level. Traceability of all system level parameters from both requirements to functions and from functions to components is maintained within RDD-100,

    RDD-100 is based upon an entity, relationship and attribute (ERA) database. Entities within the database are the nouns or objects within the system such as requirements, functions and components. The interrelationship between different entity types are defined by an extendible schema within RDD-100. It is through these relationships that traceability is maintained within RDD-100. The base RDD-100 schema has been extended for RASSP to support the integrated costing and reliability analysis and these extensions are described in Section 3.2.3.1.

    The typical use of RDD-100 is illustrated in Figure 3-4. Requirements are initially captured, examined and decomposed into lower level requirements during the requirements analysis step. The functionality of the system is then defined using behavior diagrams within RDD-100 during the functional analysis step. Both control and data flow are shown within the same behavior diagram. Every function within the behavior diagram must be traceable to a requirement. The physical architecture consisting of hardware and software components is established during the system partitioning step. Each function in the behavior diagram must be allocated to one component in the system architecture. A traceable path between each function and the component that function is allocated to is maintained within RDD-100.

    Figure 3 - 4: Typical Use for RDD-100

    3.2.2.2 PRICE Cost Estimating Tools

    Lockheed Martin's PRICE Systems cost estimating models are advanced Computer Aided Parametric Estimating (CAPE) tools used for calculating cost estimates and schedules for both hardware and software components. Computer-aided parametric estimating tools are parametric cost models that relate physical and empirical system characteristics to the costs and schedules required to develop, produce and maintain the system. These cost estimating relationships (CERs) are embodied within the computer model. PRICE Systems formalizes these relationships by applying regression techniques to hardware and software systems across various industries. In addition, these estimating relationships can be calibrated for a specific organization so the outputs obtained from the PRICE tools reflect that organization's costs.

    The PRICE cost estimating tools consist of the hardware, microcircuit, hardware life cycle and software models and each of these models are described below.

    PRICE H - Hardware Cost Model : The hardware model is used to estimate the cost and schedule for electronic, electro-mechanical, and structural assemblies. This model incorporates input data concerning weight, size, quantity, process and design sensitivity, and complexity parameters. The hardware model provides cost and schedule outputs for the development and production phases of a program.

    PRICE M - Microcircuit/Module Cost Model : The microcircuit model is used to estimate the cost and schedule for custom microcircuits, printed circuit boards, and electronic modules. The model uses functional relationships based upon parameters such as the number of transistors, percentage of new circuit cells, number of pins, board types and size.

    PRICE HL - Hardware Life Cycle Model : The hardware life-cycle model is used to estimate the cost of operating and maintaining hardware systems throughout their deployment. Inputs to the life cycle model include deployment parameters, maintenance concepts, cost, and escalation factors. The life cycle model is a supplement to and works in conjunction with the hardware model.

    PRICE S - Software/Software Life Cycle Model : This software model is used to estimate the cost and schedule for the design, development, integration, testing, and support of software. This model uses functional relationships based upon parameters such as function, lines of code, complexity, platform, application, and design reuse to estimate costs.

    PRICE Systems refine and update their cost estimating models based upon actual costs being incurred on current products of their users. While the cost models are designed to provide estimates for a typical organization, the models provide the flexibility for the user to tailor and calibrate the models for their specific organization. As a result of calibration, the costs and schedule outputs of the models reflect how a particular organization develops their product.

    The PRICE model requires that the system be described as a set of hardware and software components in an equipment breakdown structure (EBS) which is shown in Figure 3-5. Parameters which characterize each component are entered into the model. Global parameters which define labor rates, financial factors and deployment concepts are also required. The PRICE models determines the development, production and support costs for each component in the EBS and these costs are accumulated up the equipment tree to determine the overall system costs.

    Figure 3 - 5: PRICE EBS and Output Report

    3.2.2.3 RAM-ILS

    Management Sciences Incorporated's (MSI) RAM-ILS toolset provides design assurance management for an overall system design environment. The RAM-ILS toolset consists of synergistic tools within the design framework which measure the quality related aspects of a design. This toolset is used to assess the functional robustness, functional reliability, functional diagnosability, manufacturing process reliability, and deployment reliability issues. The features of the RAM-ILS toolset are summarized in Table 3-4.

    Design Assurance Tool

    Value Added

    Functional Reliability Risk Allocation

    Reliability goals for hardware and software

    Circuit Based Design Reliability Simulation

    Stress derating for component selection

    Functional Reliability and Longevity Analysis

    Improved performance in operational life cycle

    Deployment Life Cycle Cost Tradeoffs

    Economic and warranty analysis

    Failure Modes and Effects Criticality Analysis

    Safety and degraded performance analysis

    Diagnosability and Repairability

    Maintenance requirements analysis

    Mission and Deployment Reliability

    Durability, capability and performance analysis

    Maintainability and Supportability

    Support staff/equipment requirements analysis

    Worst Case Analysis (Aging and Degradation)

    Parametric degradation analysis

    Thermal Damage Analysis

    Thermal derating analysis

    Table 3 - 4: Features of the RAM-ILS Toolset s

    The RAM-ILS toolset can be used for reliability predictions, maintenance analysis, failure modes and effects criticality analysis (FMECA), and success tree analysis. Each of these capabilities are described below.

    Reliability Predictions - Reliability predictions are made within the RAM-ILS tool using reliability block diagrams. Failure models for each component in the system can be based upon relevant historical data, specialty computational methods, probability distributions and "similar to" designs. These predictions facilitate trade-off studies when allocating failure rate budgets to system components.

    Maintainability Predictions - The RAM-ILS tool can be used to determine the impact of various maintenance concepts on life cycle cost. The tool models various maintenance strategies such as level of repair and fault isolation characteristics. Maintenance diagrams are constructed within the toolset.

    Failure Modes and Effects Criticality Analysis (FMECA) - The FMECA portion of the RAM-ILS toolset provides the user with an understanding how the system will perform when it is operating in either a degraded or failed state.

    Success Trees - Success trees are modeled within the RAM-ILS toolset to illustrate how a system successfully operates with respect to the interaction of system functions and components. Inverted success trees identify unacceptable critical combinational failures. Success trees can be used to confirm redundancy decisions and identify false redundancy conditions.

    The RAM-ILS toolset is integrated with Mentor Graphics Falcon Framework and is illustrated in Figure 3-6. This integration provides a consistent, well-defined, known user interface. As a result, the user does not need to learn another specialized interface to use the RAM-ILS tool. In addition, the Mentor interface provides convenient access to detailed design data.

    Figure 3 - 6: RAM-ILS User Interface

    3.2.3 Integrated Tools Description

    3.2.3.1 RASSP Schema Extension Overview

    The schema within RDD-100 has been extended on the RASSP program to support both cost estimating and specialty engineering. An overview of the RASSP schema extensions is presented in this section to give the reader a basic understanding of these modifications. For more detailed information on the schema extensions see the RDD-100 User's Manual for the Integrated System Engineering RASSP Schema and the "Specification for Ascent Logic Corporation, RDD-100 Schema Extensions (for the RASSP program)". The baseline RDD-100 schema has been extended in six basic areas to support cost estimating and specialty engineering. Each of these schema extensions is described below.

    3.2.3.1.1 Additional Component Attributes

    Additional attributes have been added to the component entity in the RASSP schema to characterize the component for cost and reliability assessment. A summary of these additional attributes is given in Table 3-6. Some of these attributes are not applicable to all component types. For example, the attributes which characterize software are not applicable to purely hardware components.

    Type of Attribute

    Attribute

    Comment

    Component Characterization Parameters

  • Component Type

  • Component Subtype

  • Design Source

  • Percent New Design

  • Technology Maturity

  • Duplicate Used in Other Assemblies
  • User input parameters

  • Component type indicates whether component is system, subsystem, hardware, software or firmware

  • Component subtype indicates whether component is an assembly, board, module, power supply, etc.

  • Design source indicates whether component will be a new design, COTS or furnished
  • Quantity Parameters

  • Quantity in Next Higher Assembly

  • Quantity Requested by RMA

  • Quantity Required for Operation

  • Redundancy Mode

     

  • RAM-ILS tool back annotated quantity requested for RMA which indicates optimizations within the RAM-ILS tool on how system configuration can be changed for a more cost effective system

  • Parameters accommodate redundancy in the system
  • Physical Parameters

  • Budgeted Length

  • Budgeted Width

  • Budgeted Depth

  • Budgeted Weight

  • Predicted Length

  • Predicted Width

  • Predicted Depth

  • Predicted Weight
  • User enters in the budgeted values

  • Other tools or user enter in predicted values as design progresses

  • Parameters indicate margin between current design and requirement
  • Power Parameters

  • Budgeted Average Power

  • Budgeted Maximum Power

  • Predicted Average Power

  • Predicted Maximum Power
  • User enters in the budgeted values

  • Other tools or user enter in predicted values as design progresses

  • Parameters indicate margin between current design and requirement

  • RAM-ILS tool uses power metrics within sensitivity calculations
  • Sensitivity Parameters

  • Volume Sensitivity

  • Weight Sensitivity

  • Power Sensitivity
  • User input parameters

  • RAM-ILS uses parameters in sensitivity calculations when trying to optimize system configuration to meet requirements

  • Parameters are used to specify relative importance among these sensitivities
  • Hardware Technology Parameters

  • Technology Type 1

  • Equipment Type 1

  • Percentage of Type 1 Technology

  • Technology Type 2

  • Equipment Type 2

  • Percentage of Type 2 Technology

  • Technology Type 3

  • Equipment Type 3

  • Percentage of Type 3 Technology

  • Technology Type 4

  • Equipment Type 4

  • Percentage of Type 4 Technology

  • Technology Type 5

  • Equipment Type 5

  • Percentage of Type 5 Technology
  • User input parameters

  • Up to five different technology/equipment types can be used to characterize component

  • Technology type defines the digital technology used to construct component, i.e. VLSI

  • Equipment type specifies the application where technology is used, i.e. analog, rf, digital, display, structure, etc.

  • Percentages of all technology types should add up to 100 percent
  • Software Parameters

  • Source Lines of Code

  • Percent of Memory Utilization

  • Percent of Processor Utilization

  • Language

  • Percent of New Code
  • User input parameters

  • Parameters indicate the size, language and efficiency of the software component
  • Software Characterization Parameters

  • Percent of Mathematic Code

  • Percent of String Manipulation Code

  • Percent of Store and Retrieve Code

  • Percent of On-line Communication Code

  • Percent of Operating System & Interactive Code

  • Percent of User Defined Code

  • Difficulty of User Defined Code
  • User input parameters

  • Parameters indicate the type of software being developed

  • Percentage of all code types should add up to 100 percent

  • Difficulty factor must be defined if user defined code is used
  • Table 3 - 6: Added RASSP Attributes for Component Entity

    3.2.3.1.2 Cost Entity

    The attributes in the cost entity primarily contain the development, production and support costs, which are back annotated from the PRICE tool into the RDD-100 database. There must be one cost entity for each component in the equipment tree, which is related to the component by the "costs" relationship. A summary of the cost entity attributes is given in Table 3-7. The budgeted costs in this table are entered by the user and represent the cost requirement. The predicted costs are calculated by the PRICE tool and are back annotated into RDD-100.

    Type of Attribute

    Attribute

    Comment

    Development Cost Parameters

  • Purchased Item Cost

  • Budgeted Development Costs

  • Predicted Development Costs
  • Purchased item cost is unit cost of COTS item entered by user

  • User enters budgeted cost

  • PRICE calculates predicted development cost
  • Production Cost Parameters

  • Budgeted Amortized Unit Production Cost

  • Budgeted Unit Production Cost

  • Budgeted Production Costs

  • Predicted Amortized Unit Production Cost

  • Predicted Unit Production Cost

  • Total Production Quantity

  • Predicted Production Costs
  • User enters budgeted costs

  • PRICE calculates predicted costs

  • Total production quantity includes initial spares
  • Operational Cost Parameters

  • Budgeted Operational Costs

  • Predicted Operational Costs
  • User enters budgeted costs

  • Predicted operational costs are entered by user from either PRICE, RAM-ILS or other source
  • Support Cost Parameters

  • Budgeted Support Costs

  • Predicted Support Costs
  • User enters budgeted costs

  • PRICE calculates predicted costs
  • Sensitivity Cost Parameters

  • Production Cost Sensitivity

  • Operational Cost Sensitivity

  • Support Cost Sensitivity
  • User input parameters

  • RAM-ILS uses parameters in sensitivity calculations when trying to optimize system configuration to meet requirements

  • Parameters are used to specify relative importance among these sensitivities
  • Table 3 - 7: Cost Attributes

    3.2.3.1.3 RMA Entity

    The attributes in the RMA entity primarily contain reliability and maintainability metrics which are back annotated from the RAM-ILS tool into the RDD-100 database. There must be one RMA entity for each component in the equipment tree which is related to the component by the "has rma" relationship. A summary of the RMA entity attributes is given in Table 3-8. The budgeted RMA attributes in this table are entered by the user and represent the allocated requirement. The predicted RMA attributes are calculated by the RAM-ILS tool and are back annotated into RDD-100

    Type of Attribute

    Attribute

    Comment

    Reliability Parameters

  • Allow RMA Quantity Request

  • Predicted Availability

  • Predicted Reliability

  • Budgeted MTBCF

  • Predicted MTBCF

  • Budgeted MTBF

  • Predicted MTBF

  • Method used for MTBF Prediction

  • Optimized MTBF

  • MTBF Optimization Criteria
  • User enters budgeted metrics

  • Allow RMA Quantity Request is a user entered parameter to indicate to the RAM-ILS tool whether redundancy can be considered for this component when optimizing the system

  • RAM-ILS tool calculates predicted metrics

  • RAM-ILS can use various methods for MTBF prediction and this method is back annotated into RDD-100 database

  • RAM-ILS tools is used for sensitivity and optimization studies and the results and criteria used for these studies are back annotated into the optimization metrics

  • Predicted MTBF is used within PRICE life cycle model
  • Maintainability Parameters

  • Line Replaceable Unit (LRU)

  • Maintenance Procedure

  • Budgeted Line MTTR

  • Predicted Line MTTR

  • Predicted LRU MTTR at Organization Supply Location

  • Predicted Module MTTR at Organization Supply Location

  • Predicted LRU MTTR at Intermediate Supply Location

  • Predicted Module MTTR at Intermediate Supply Location

  • Predicted LRU MTTR at Depot Supply Location

  • Predicted Module MTTR at Depot Supply Location
  • User enters budgeted metric

  • Line Replaceable Unit (LRU) is a user entered parameter to indicate to the RAM-ILS tool whether the component is an LRU

  • RAM-ILS tool calculates the predicted metrics

  • Predicted metrics are used as inputs to the PRICE life cycle model
  • Maintenance Concept Parameters

  • Maintenance Concept Requested for Cost Estimating Tool

  • Maintenance Concept Used in Cost Estimating Tool
  • User enters requested maintenance concept to direct PRICE which concept to use within the life cycle model

  • PRICE selects most cost effective maintenance concept if requested concept field is empty

  • PRICE back annotates the maintenance concept used within life cycle model into RDD-100 database
  • Table 3 - 8: RMA Attributes

    3.2.3.1.4 Life Cycle Parameter

    The attributes in the life cycle parameter entity characterizes the operational environment and deployment scenario for the product under development. There must be one life cycle parameter entity defined for the system which is related to the system component through the "satisfies" relationship. A summary of the life cycle parameter attributes is given in Table 3-9.

    Type of Attribute

    Attribute

    Comment

    Operational Parameters

  • Operating Environment

  • Environmental Maximum Temperature

  • Environmental Minimum Temperature
  • User input parameters

  • PRICE uses operating environment in cost calculations

  • RAM-ILS uses parameters for reliability assessment
  • System ‘ility Parameters

  • Operational Availability

  • Inherent Availability

  • Reliability
  • User input parameters

  • System level requirements

  • RAM-ILS uses these parameters to determine whether calculated ilities meet the system requirements
  • Deployment Parameters

  • Deployment Quantity

  • Prototype Quantity

  • Mission Period

  • Life Cycle Duration

  • On Time Factor
  • User input parameters

  • PRICE uses parameters for life cycle cost calculations

  • RAM-ILS uses parameters for reliability and maintainability assessments
  • Sensitivity Parameters

  • Volume Sensitivity

  • Weight Sensitivity

  • Power Sensitivity

  • Production Cost Sensitivity

  • Operational Cost Sensitivity

  • Support Cost Sensitivity
  • User input parameters

  • RAM-ILS uses parameters in sensitivity calculations when trying to optimize system configuration to meet requirements

  • Parameters are used to specify relative importance among these sensitivities
  • Table 3 - 9: Life Cycle Parameter Attributes

    3.2.3.1.5 Duplicate Component

    A component may be replicated in multiple places within the system equipment tree. Since each instance of a component entity must have a unique name in RDD-100, a means of identifying which components are identical is needed to ensure that the appropriate development, production and support costs are calculated within the PRICE toolset. The duplicate component entity is used to identify families of components that are identical and are built from different parent components. The relationship "includes duplicate" is made from the duplicate component entity to all identical components within a family. Note that when identical components have the same parent within the equipment tree, the attribute entitled "Quantity in Next High Assembly" is used to reflect the number of identical components used in the parent and the use of the duplicate component is not needed for this case.

    The attributes for the duplicate component entity are essentially identical to the additional attributes added to the component entity in the RASSP extended schema. The major difference between the attributes is that the various quantity attributes in the component entity have been replaced by the total system quantity attribute in the duplicate component entity. The total system quantity attribute contains the total number of identical components used within one system and this number is calculated and back annotated into the RDD-100 database by running the "Calculate Total System Quantity Report" within RDD-100.

    3.2.3.1.6 External Tool File Entity

    The attributes in the external tool file entity contains information about file location for both the PRICE and RAM-ILS tool. A summary of the external tool file attributes is given in Table 3-10.

    Type of Attribute

    Attribute

    Comment

    PRICE File Parameters

  • Cost Analyst File Requested

  • Sync File Requested

  • Lock File Requested

  • Cost File Used

  • Sync File Used

  • Lock File Used
  • User inputs the requested file names

  • Specific use of files described in integrated design to cost section

  • Cost analyst can specify which file to use in lieu of the requested file

  • Names of actual files used are back annotated into RDD-100 from PRICE

     

  • RAM-ILS File Parameter

  • RAM-ILS Directory Used
  • RAM-ILS tool back annotates this parameter which defines the path name of directory which the RAM-ILS tools uses for RAM analyses
  • Table 3 - 10: External Tool File Attributes

    3.2.3.2 Integrated Design To Cost

    3.2.3.2.1 Overview

    Traditional cost estimating processes have relied upon estimators and engineers to work within a functionally-oriented organizational process, as shown in Figure 3-7. As a result, the traditional process is slow, inconsistent and generally not repeatable. From the cost estimator's perspective, the costing process is a top-down process that requires the translation of engineering specifications into cost model inputs and an estimating breakdown structure (EBS), and the execution of the model to obtain preliminary results. These results are then iterated back to engineering several times to resolve any questions that arise. From the engineer's perspective, the traditional costing process is a bottoms-up process that requires the creation of an engineering estimate based upon labor hours and a bill of materials supported by vendor quotes. Generally, these two estimates are compared and a resolution is reached via a process that varies from company to company. Although this process may be valuable in providing cost perspectives from two different approaches, this process has proven to be much too slow and costly to be responsive in using cost as a design trade-off parameter in a Design To Cost (DTC) environment.

    Figure 3 - 7: Traditional Cost Estimating Process

    An automated Integrated Design To Cost (IDTC) environment has been developed which enables engineers and cost estimators to work efficiently together using their native tools so many design alternatives can be examined during system concept trade-off studies. As shown in Figure 3-8, the engineer works within his system engineering tool (RDD-100) to enter a physical description of a potential design. This information is then exported out of the system engineering tool and read into the cost estimating tool(PRICE). The data is then translated into cost estimating parameters and merged with information from the cost analyst to produce a complete set of data for the parametric estimating engine. The parametric engine produces a cost and schedule estimate and exports this data back to the system engineering tool. The engineer can then access this cost data within the system engineering tool.

    Figure 3 - 8: Integrated Cost Estimating Process

    This IDTC estimating process is an improvement to the traditional method in many ways. It is faster, enabling more alternatives to be explored. It is more accurate and repeatable because the estimating relationships are controlled by the estimator, codified into a language script and executed by a computer. Since the relationships are codified, the engineer does not need to meet with the estimator every time a cost estimate is needed. This IDTC process allows the engineer and estimator to work effectively together. A cost estimate can be turned around in minutes instead of days or weeks with this IDTC environment.

    The organization of this section is as follows. The physical elements of the IDTC environment are initially described. Then the process to use the IDTC environment is explained.

    3.2.3.2.2 IDTC Environment

    The RASSP IDTC environment consists of the RDD-100 and PRICE extensions as shown in Figure 3-9. The schema, consistency checks and output reports have been developed for RDD-100 which support the IDTC environment. A cost analyst file, synchronization file, PRICE Rule Language (PRL) import template, and PRL export template have been developed within the PRICE Enterprise toolset to support the automated IDTC environment. The use of each of these elements within the IDTC environment is described below. Note that the parameters calculated by the RAM-ILS tool which are used within PRICE to support cost estimating are not explicitly shown in Figure 3-9, since these parameters are back annotated into the RDD-100 database prior to using them in PRICE.

    Figure 3 - 9: IDTC Environment

    The schema within RDD-100 has been extended on the RASSP program to support both cost estimating and reliability analysis as previously described in section 3.2.3.1. The engineer populates the RDD-100 data base with the system engineering parameters that define the physical configuration of the hardware and software. A consistency report is then executed within RDD-100 to make sure that the database has been sufficiently populated to obtain a cost estimate. An export report is then run within RDD-100 which outputs the system configuration with all the required attributes in the appropriate format (format needed by the PRICE tool is defined in the interface specification) to import into the PRICE cost estimating tools. The cost for each system component is then estimated within the PRICE tool based upon the system engineering parameters and data provided by the cost analyst. The PRICE tool generates an output file in the standard RDD-100 rdt format which contains the development, production and support costs for each system component. This cost data is populated within the RDD-100 data base using the standard RDD-100 import facility.

    Cost Analysis File - The cost analyst file is used in conjunction with the RDD-100 output file, PRL import template and the synchronization file to establish all of the parameters the PRICE tool needs to perform a cost estimate. The cost analyst file contains default parameters for each component in the system which are missing from translation of the RDD-100 file. The parameters typically defined within the cost analyst file are prototype and production schedule, labor rates, escalation rates and other financial factors that the PRICE tool needs. The information is entered within the cost analyst file on an element type basis. Each component within the PRICE estimating breakdown structure has a particular element type such as electro-mechanical, software and design integration. All components of the same mode type receive the same default parameters contained within the cost analyst file if the parameter is missing from the RDD-100 file and synchronization file.

    Synchronization File - The synchronization file is used in conjunction with the RDD-100 output file, PRL import template and the cost analyst file to establish all of the parameters the PRICE tool needs to perform a cost estimate. The synchronization file contains parameters for each component which override any parameter from either the translation of the RDD-100 file or cost analyst file. It is through the use of the synchronization file that the cost analyst can control the cost estimate since any parameter within this file will supersede the same parameter from any other source. The information is entered within the synchronization file on a component name basis which enables each component to have its own parameters within the synchronization file. Since the PRICE interface has been designed to interface with multiple tools, a lock file name is used within the PRICE tool to identify which parameters are active for overriding parameters for each tool interface. It is through the use of the lock file name that the same synchronization file can be used for interfacing PRICE to multiple tools.

    PRL Import Template - System engineering parameters within RDD-100 are used to populate attributes within the PRICE toolset. However, there is not a direct one-to-one mapping of the system engineering parameters within RDD-100 to PRICE attributes. A simple illustration of this is that the length, depth and width of a component are entered in RDD-100 for a hardware component, while the PRICE tool only uses volume. As a result, the system engineering parameters must be translated into attributes understood by the PRICE tool. A proprietary interpreted language called PRICE Rule Language (PRL) was developed to translate parameters from other tools into PRICE attributes. As a part of the RASSP program, a PRL import template was written which translates approximately 65 system engineering parameters for each component into about the same number of PRICE attributes. This import template was developed for the signal processing domain, although it may be applicable to digital hardware and software systems. To support other domains, additional translations are required that are unique to that particular domain.

    PRL Export Template - Development, production and support costs for each component are back annotated from the PRICE tool into the RDD-100 database. A PRL export template is used to write the cost data out of the PRICE tool into a file with the appropriate format. In this case, the standard RDD-100 rdt format is used so that the data can be imported into RDD-100 with the standard import mechanism.

    3.2.3.2.3 IDTC Process

    The process in which the IDTC team can effectively implement IDTC is shown in an IDEF3 representation in Figure 3-10. This process diagram is an adaptation of the process used by one of the beta site companies evaluating the RASSP integrated system tools. Each box in this figure represents a process step. The inputs to the process are shown on the left side of the box, the control parameters on the top, the resources needed for the process on the bottom and the output of the process on the right side. The IDTC process consists of six steps which are listed below:
    1. Create the parametric estimating relationships;
    2. Analyze the programmatic requirements of the project;
    3. Create the cost analysis file;
    4. Develop and verify system architectures which meet the requirements;
    5. Obtain the cost estimate; and
    6. Create and maintain the synchronization file.

    Each of these process steps is described below. Note that this process is iterative in nature and is repeated as the system design matures, resulting in more accurate cost estimates.

    Figure 3 - 10: IDTC Process

    Create Parametric Estimating Relationships - The parametric estimating relationships (PER) which are used to convert system engineering data into PRICE cost estimating attributes are established and codified into the PRICE Rule Language (PRL) during this process step. This process step is performed once and should address all product lines and application domains which IDTC is intended to be used. The generation of the PRL import template should be done once for a company and is not typically part of a specific project. The PER's and PRL import template are updated to reflect changes in a company's product line. The cost estimating department is responsible for developing the PER's. The process used to generate these relationships are contained within a company's work instructions. These relationships are developed from legacy data from previous projects. The output of this process step is the PRL import template which codifies the rules to translate RDD-100 system engineering parameters into PRICE attributes. The RDD-100 schema, consistency checks and export reports may need to be modified if additional system engineering parameters are needed to characterize a company's product.

    Analyze Project's Programmatic Requirements - The customer requirements are analyzed in this process step to determine whether a company is going to proceed in bidding the program. The program management and proposal response teams perform this process step using the company's legacy data and conceptual baseline architecture for the project. The outputs of this process step include the job instructions for conducting the project and the set of allocated budgets for the program.

    Create the Cost Analyst File - The cost analyst file used to supply default parameters while importing system engineering parameters into the PRICE tool is created during this process step. The cost estimating department is responsible for the generation of this file using the PRICE tool. This file contains default parameters which are used to supplement the attributes obtained from the translation of the RDD-100 parameters. This file typically contains prototype and production schedules, labor rates, escalation rates and other financial factors.

    Develop and Verify System Architectures - Architecture tradeoffs are performed during this process step to determine the hardware and software elements of the system. This process step is performed by the IPDT team which must consider all aspects of the system life cycle. The IPDT performs this process step using the allocated budgets, project technical information and cost data in determining the composition of the system. The requirements are analyzed, the system functions are decomposed and system architectures are analyzed using RDD-100. This process step is iterative in nature and is repeated for each candidate system design. The output of this process is the system configuration with costing data. The fidelity of the cost data can either be comparative in nature, rough order of magnitude or basis of estimate depending upon the rigor used in developing the parametric estimating relationships.

    Obtain the Cost Estimate - The development, production and support costs for a system architecture are determined during this process step. This process step is performed by importing the RDD-100 generated file containing the system engineering parameters using the PRL import template, cost analyst file and synchronization file into the PRICE Enterprise toolset. The outputs of this process step are the cost reports from the PRICE tool and the ASCI file containing the development, production and support costs. This file is used to import the cost data into the RDD-100 database.

    Create and Maintain the Synchronization File - The synchronization file used to supply overriding parameters while importing system engineering parameters into the PRICE tool is created during this process step. The cost estimating department is responsible for generating this file using the PRICE tool. This file contains overriding parameters which supersede the values obtained from either the translation of the system engineering data or cost analyst file. This file provides the mechanism that the cost analyst can use to control the cost estimate.

    3.2.3.3 RAM (Reliability, Availability and Maintainability) Assessment

    3.2.3.3.1 Overview

    Traditional RAM engineering processes are disjoint with respect to the product development cycle as shown in Figure 3-11. Reliability engineering has typically been viewed as a necessary evil; a very time consuming effort to be left to specialty engineers. While most engineers have a basic understanding of quality goals and issues, much of the focus in implementing quality has been on the statistical aspects of quality rather than applying reliability knowledge in the engineering design effort. Problems associated with this traditional approach are listed below:

    Figure 3 - 11: Traditional RAM Process

    Management Sciences, Inc. (MSI) RAM tools provide a new approach to applying traditional "ilities" design techniques early in the design process. The goal of using RAM tools early in the system engineering effort is to reduce the number of nasty surprises encountered later in the product life cycle. It is in this early design phase that the most reliability improvements can be recognized and incorporated cost effectively. Through the early use of the integrated systems tools, reliability requirements and issues are identified and documented cooperatively and concurrently with other design requirements and issues as shown in Figure 3-12. Thus, quality related issues can be applied to the architecture selection process, and issues and requirements can be documented, tracked, and monitored through the product design life cycle.

    Figure 3 - 12: Integrated RAM Process

    The remainder of this section provides a short discussion of the software integration with Ascent Logic's (ALC) RDD-100 tool. This discussion is followed with a description of how the MSI tools support the RASSP systems engineering process. The MSI tools that are discussed include: Quality Function Deployment (QFD), Failure Modes and Effects Analysis (FMEA), and Integrated RAM Analysis. Through reading this section, you will obtain an understanding of the benefits of using these capabilities early in the design process.

    3.2.3.3.2 Software Integration

    The RMA entity type has been added to the RDD100 schema (as described previously in Section 3.2.3.1) to support a combination of reliability analysis, documentation, and statistical analysis. This entity type contains statistical values such as MTBF, Reliability, MTTR, and Availability which are used in performing integrated cost estimating and detailed statistical reliability analysis.

    The systems engineer populates the RDD-100 data base with the equipment configurations, functional descriptions, interface items and allocated RAM budgets. An export report is run within RDD-100 which outputs the system configuration and its associated attributes in the appropriate format for the MSI RAM toolset. The specialty engineer uses this data within the MSI toolset with detailed CAD data from existing designs to support a variety of RAM analyses such as Quality Function Deployment (QFD), Failure Modes and Effects Analysis (FMEA) and RAM assessment. The predicted RAM attributes calculated by the MSI toolset are back populated within the RDD-100 data base.

    3.2.3.3.3 Quality Function Deployment (QFD)

    The relationship among the requirements, architecture candidates and customer expectations can be depicted in Quality Function Deployment models. These QFD charts (typically referred to as "House of Quality") show a correlation between what must be done, how to do it, and the relative benefits of each candidate architecture as shown in Figure 3-13. Functions, components and interface items within the RDD-100 data base can be used to populate various elements within the QFD spreadsheet template in the MSI toolset at the indenture level desired. A different chart is created for each function or component within the system. The specialty engineer can then populate the remaining items of this spreadsheet when performing the QFD analysis.

    Figure 3 - 13: Quality Function Deployment Template

    3.2.3.3.4 Failure Modes Effects Analysis (FMEA)

    FMEA models define the relationship between components, functions and failures in meeting mission performance requirements. FMEA spreadsheets depict a correlation matrix between how things fail, how the failures will be detected, and what is likely to happen in the event of a failure. The engineer uses this analysis to understand these relationships early in the design and to make changes to the architecture candidate that facilitate a safer, more maintainable, and more reliable system.

    Components, functions and interface items defined within the RDD-100 data base are used to initially populate a FMEA data base within the MSI toolset. The specialty engineer can then use this FMEA data base to perform the following tasks:

    An example of a FMEA spreadsheet populated automatically from the RDD-100 data base is shown in Figure 3-14. Data items that are missing from the worksheet must be manually populated by the engineer.

    Figure 3 - 14: Automated FMEA Worksheet

    3.2.3.3.5 Integrated RAM Analysis

    RAM models define the relationship between architecture candidates, failure probabilities, availability, and repair times. The components hierarchy and allocated RAM defined within the RDD-100 data base are used to populate the MSI RAM toolset. This toolset can be then used for the following tasks: The RAM predictions within the MSI toolset are based upon the data populated from RDD-100 and data the user adds within the RAM tools. Typical sources for MTBF and MTTR values used for the system engineering activities are estimates of acceptable loss rate, "similar to" designs, historical data and vendor data. The results of the RAM assessments within the MSI toolset are back annotated in the RDD-100 data base.

    3.3 Benefits of Using the RASSP Integrated System Tools

    The integrated system tools provide a concurrent engineering environment where tradeoffs considering a product's complete life cycle are performed. Multi-disciplinary design data is stored in one location that the entire IPDT team can assess. As a result, the entire design team uses the same data within their analyses which eliminates the confusion when parameters are maintained in multiple locations. Cost performance tradeoffs are performed using the integrated tools to optimize the system design over multiple disciplines. The integrated tools provide a quick impact analysis capability, as detailed design data can be used to update the reliability and cost predictions.

    The integrated system tools provide an efficient process for the engineer to access cost data. Engineers can obtain complete life cycle costs using the system tools without becoming an expert cost analyst. The integrated system tools provide an environment which can be effectively used to implement either Design To Cost (DTC) or Cost as an Independent Variable (CAIV) programs which are being emphasized within DoD. The cost estimation process has been established so the cost analyst is able to control the estimate.

    The integrated system tools provide a reliability and maintainability analysis capability throughout the design process. These tools provide the mechanism that allows specialty engineers to be involved early in the design process. The RAM-ILS tool provides capabilities to perform reliability, maintainability, success tree and FMECA analyses. In addition, the system architecture can be optimized to meet reliability requirements in a cost effective fashion with the integrated system tools.


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