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Formal Information-Based Standards for Test and Diagnosis John W. Sheppard, Co-Chair Mark Kaufman, Co-Chair Diagnostic & Maintenance Control IEEE SCC20.

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Presentation on theme: "Formal Information-Based Standards for Test and Diagnosis John W. Sheppard, Co-Chair Mark Kaufman, Co-Chair Diagnostic & Maintenance Control IEEE SCC20."— Presentation transcript:

1 Formal Information-Based Standards for Test and Diagnosis John W. Sheppard, Co-Chair Mark Kaufman, Co-Chair Diagnostic & Maintenance Control IEEE SCC20

2 System Complexity Modern systems and products are complex. Test systems required to support products are equally complex. Managing complexity involves: –Controlling risk and cost. –Intelligent distribution of resources. –Management and integration of information from these distributed sources. –Definition of unambiguous information requirements through a common language.

3 Requirement Interdependence Testability requirements are based on system specifications. –Testability metrics not precisely defined or have multiple definitions. –Existing tools/methods calculate metrics differently. –Metric ambiguity is driven by existing guidelines (e.g., MIL HDBK 2165): Test requirements are established to satisfy testability goals. –Often tied to ATS architecture. No standard way to specify test requirements. Therefore …

4 DMC Scope Effective management of test and maintenance information is critical. –The test and maintenance engineering process is, by nature, highly distributed. –The information requirements to support test and maintenance engineering are highly diverse. DMC standards focus on reducing the cost and risk of managing the information required for test and maintenance.

5 The Focus Communication!!! Communication requires prior agreement on the characteristics of the message. –Structure –Content In test and diagnosis, this equals information exchange among and between test assets and maintenance organizations.

6 Information-Based Architecture Communications Backbone Diagnostic System Test System Historical Data System Under Test Application Executive

7 An Information-Based Approach Information Framework IDEF0 (Activity Models) IDEF1x (Data Models) EXPRESS (Information Models) diagnose repair fault BIT Codes TOs Define Test & Diagnostic Process Capture Required Information Implement Information System

8 Information Model Definition: An information model is a formal description of types (classes) of ideas, facts, and processes that together represent of a portion of interest of the real world. Purpose: To identify clearly the objects in a domain of interest to enable precise communication about that domain. Components: objects or entities, relationships, constraints. Outcome: Unambiguous exchange of information between systems.

9 Integrating Test & Diagnostic Information Test & Diagnostic Information Framework Test & Diagnostic Data Diagnostic Data Test Data Product Data History Data P1598 TeRM P1232 AI-ESTATE P1522 Testability Pxxxx SIMICA

10 The Standards IEEE P1232Standard for Artificial Intelligence Exchange and Service Tie to All Test Environments (AI-ESTATE). IEEE P1522Standard Testability and Diagnosability Characteristics and Metrics. IEEE PxxxxStandard Interface for Maintenance Information Collection and Analysis (SIMICA). IEEE P1598Standard for the Test Requirements Model (TeRM)

11 IEEE P1232AI-ESTATE P1232 Define information for system test and diagnosis. Exchange diagnostic information between applications. Support modular diagnostic architectures. Support interoperability with other test assets. Define information for system test and diagnosis. Exchange diagnostic information between applications. Support modular diagnostic architectures. Support interoperability with other test assets.

12 IEEE P1522Testability/Diagnosability P1232 P1522 Define fundamental information for testability analysis. Tie definitions to standard modelseliminate ambiguity. Derive metrics and characteristics based on fundamentals. Provide foundation for extension and expansion. Define fundamental information for testability analysis. Tie definitions to standard modelseliminate ambiguity. Derive metrics and characteristics based on fundamentals. Provide foundation for extension and expansion.

13 IEEE PxxxxSIMICA P1232 P1522Pxxxx Define information domain of system maintenance. Support capture of historical maintenance/diagnostic data. Facilitate discovery/extraction of maintenance knowledge. Provide foundation for diagnostic and product maturation. Define information domain of system maintenance. Support capture of historical maintenance/diagnostic data. Facilitate discovery/extraction of maintenance knowledge. Provide foundation for diagnostic and product maturation.

14 IEEE P1598TeRM P1232 P1522Pxxxx P1598 Provide formal description of product behavior under test. Define formal semantics for test requirements. Feed entire product lifecycle (concept to field) Emphasize what to test, not how to test. Provide formal description of product behavior under test. Define formal semantics for test requirements. Feed entire product lifecycle (concept to field) Emphasize what to test, not how to test.

15 Risk Reduction Optimizes use of test equipment/ resources and maintenance information to maximize availability. Promotes test effectiveness through requirements-driven test engineering. Provides means to develop strategy for test and diagnostic effectiveness assessment (testability and diagnosability). Facilitates unambiguous testability prediction and validation to ensure weapon system support specification compliance. Promotes cost-effective development and integration of state-of-the-art COTS products into ATS. Promotes flexibility in diagnostic architectures through separation of data and process.

16 Life Cycle Cost Reduction Supports advanced diagnostic technologies to improve product maintenance. –Helps to find bad actors and target maintenance problems. Provides a foundation for integrating test assets with other RMT analysis tools and methods. –Supports trade-off and competition among COTS tools to reduce ATS development cost. –Facilitates integration with related standards efforts (e.g., PLCS) to broaden resource base. Provides foundation for closed-loop corrective action analysis. –Supports diagnostic process improvement/maturation to reduce field test and maintenance cost and maximize availability.

17 Industry Interest/Involvement Committee Membership –Industry (ARINC, Boeing, Honeywell) –Tool Developers (DSI, QSI, HSI) –US DoD (All services) –Academia (Vanderbilt, NPG, U Conn) Industry Interest –OSA-CBM –PLCS/STEP –NASA –NxTest

18 Call for Participation We are looking for help: –Provide technical support and participation in the committees work. –Promote objectives of the standards in service organizations. –Promote objectives of the standards with contractors. –Incorporate DMC standards in AMB initiatives (e.g., NxTest).

19 Contact Information Dr. John Sheppard, ARINC – Mark Kaufman, NSWC, Corona Division –


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