Skip to main content
SpringerLink
Log in

ROM: a reliability knowledge representation for collaborative system design

  • Original Article
  • Published:
Engineering with Computers Aims and scope Submit manuscript

Abstract

Designing systems that satisfy target reliability is a challenge because of complex assembly structures and logical connections, numerous components and associated failure modes, and multi-disciplinary considerations. To overcome these difficulties and to design reliable systems in a systematic way, we have developed a knowledge representation for system design-for-reliability (SDfR). It is called reliability object model (ROM). ROM includes (1) a new reliability analysis structure, (2) reliability metrics that consider both random failures and wear-out failures, (3) algorithms that allocate, predict, and assess reliability, and (4) rules for reliability-oriented design change recommendations. These capabilities of ROM are demonstrated by prototype SDfR tools and three electronic system case studies. The results show that ROM is an effective unified method for SDfR, providing richer semantics and increasing the chances of developing reliable designs.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20
Fig. 21
Fig. 22
Fig. 23
Fig. 24
Fig. 25

Similar content being viewed by others

Notes

  1. Fault tree analysis (FTA) is an event-based logic diagram method that displays the relationship between a potential event affecting system performance and an underlying cause for this event [11–13].

  2. Reliability block diagram (RBD) is a component-based logic diagram method that represents complex series and parallel connections of components together [14].

  3. Failure mode and effects analysis (FMEA) is a method for analyzing potential failure modes early in the development cycle [1].

  4. Assembly structure is a set of organized relations among systems, subsystems, and components.

  5. Logical structure is a set of organized relations among series and parallel connections of physical items in terms of possible failures.

  6. Failure mode structure is a set of organized relations among failure modes and mechanisms.

  7. Failure interactions and dependencies are relations in terms of failures between two items.

  8. Random failures are represented by the exponential function (R(t) = e −λ·t, where λ is random failure rate).

  9. Wearout failures are represented by the Weibull function (\( R(t) = e^{{ - \left( {{\frac{t}{\alpha }}} \right)\beta }} \), where α is the characteristic lifetime, and β is the shape parameter).

  10. Constant random failure rate is a value that measures reliability during the random failure stage.

  11. Percentile wearout failure reliability is a probability value that measures wearout failure reliability of items at a given time.

  12. Substituting the exponential function (R(t) = e −λ·t) and RTRWi.j into Eq. (6) (\( R_{i.j} (t) = R_{i} (t)^{{w_{i.j} }} \)) leads to the equation (\( e^{{ - \lambda_{i,j} \times t}} = e^{{ - \lambda_{i} \times t \times {\text{RTRW}}_{i,j} }} \)) for allocating target random failure rates. Taking the relation between the exponents of the both sides leads to the resultant equation (λ i,j = λ i × RTRWi.j).

  13. The structure used here for USB Hub 514 is based on an actual product (GE UH 514 model). However the reliability numbers we use are not actual values and are intended for method demonstration purposes only.

References

  1. Crowe D, Feinberg A (2001) Design for reliability. CRC Press, New York

    Google Scholar 

  2. Tummala RR (2001) Fundamentals of microsystems packaging. McGraw-Hill, New York

    Google Scholar 

  3. Jensen F (1995) Electronic component reliability. Wiley, New York

    Google Scholar 

  4. Denson W (1998) The history of reliability prediction. IEEE Trans Reliab 47:321–328

    Google Scholar 

  5. Foucher B, Boullie J, Meslet B, Das D (2002) A review of reliability prediction methods for electronic devices. Microelectron Reliab 42:1155–1162

    Article  Google Scholar 

  6. Ebel GH (1998) Reliability physics in electronics: a historical view. IEEE Trans Reliab 47:379–389

    Article  Google Scholar 

  7. Engelmaier W (1983) Fatigue life of leadless chip carrier solder joints during power cycling. IEEE Trans Compon Hybrids Manuf Technol 6:232–237

    Article  Google Scholar 

  8. Kimseng K, Hoit M, Tiwari N, Pecht M (1999) Physics-of-failure assessment of a cruise control module. Microelectron Reliab 39:1423–1444

    Article  Google Scholar 

  9. Snook I, Marshall JM, Newman RM (2003) Physics of failure as an integrated part of design for reliability. In: Proceedings of the reliability and maintainability symposium, pp 46–54

  10. Condra LW (1993) Reliability improvement with design of experiments. Marcel Dekker, New York

    Google Scholar 

  11. Blischke WR, Murthy DNP (2000) Reliability: modeling, prediction and optimization. Wiley, New York

    MATH  Google Scholar 

  12. Vemuri KK, Dugan JB, Sullivan KJ (1999) Automatic synthesis of fault trees for computer-based systems. IEEE Trans Reliab 48:394–402

    Article  Google Scholar 

  13. Geymayr JAB, Ebecken NFF (1995) Fault-tree analysis: a knowledge-engineering approach. IEEE Trans Reliab 44:37–45

    Article  Google Scholar 

  14. Birolini A (2004) Reliability engineering: theory and practice. Springer, New York

    Google Scholar 

  15. Jones J, Marshall J, Aulak G, Newman B (2003) Development of an expert system for reliability task planning as part of the REMM methodology. In: Proceedings of the reliability and maintainability symposium, pp 423–428

  16. Thome B (1993) Systems engineering: principles and practice of computer-based systems engineering. Wiley, Chichester

    Google Scholar 

  17. Booker JM, McNamara LA (2005) Expert knowledge in reliability characterization: a rigorous approach to eliciting, documenting, and analyzing expert knowledge. In: Nikolaidis E, Ghiocel DM, Singhal S (eds) Engineering design reliability handbook. CRC Press, New York, pp 13.13–31.1

  18. Gorti SR, Gupta A, Kim GJ, Sriram RD, Wong A (1998) An object-oriented representation for product and design processes. Comput Aided Des 30:489–501

    Article  MATH  Google Scholar 

  19. Patterson-Hine FA, Koen BV (1989) Direct evaluation of fault trees using object-oriented programming techniques. IEEE Trans Reliab 38:186–192

    Article  Google Scholar 

  20. Peak RS, Lubell J, Srinivasan V, Waterbury SC (2004) STEP, XML, and UML: complementary technologies. J Comput Inf Sci Eng 4:379–390

    Article  Google Scholar 

  21. Zhao Z, Shah JJ (2005) Domain independent shell for DfM and its application to sheet metal forming and injection molding. Comput Aided Des 37:881–898

    Article  Google Scholar 

  22. Harmon P, Watson M (1997) Understanding UML: The developer’s guide. Morgan Kaufmann Publishers, Inc., San Francisco

    Google Scholar 

  23. Kim I (2008) Development of a knowledge model for the computer-aided design for reliability of electronic packaging systems. Georgia Institute of Technology, Atlanta, Ph.D. Thesis

  24. Leemis LM (1995) Reliability: probability models and statistical methods. Prentice-Hall, Upper Saddle River

    MATH  Google Scholar 

  25. Wood AP (2001) Reliability-metric varieties and their relationships. In: Proceedings of the reliability and maintainability symposium, pp 110–115

  26. Kim I, Pucha RV, Peak RS, Sitaraman SK (2008) Development of reliability allocation and assessment algorithms for designing multilevel microelectronic systems. J Microelectron Electron Packag 5(1):12–25

    Google Scholar 

  27. Oracle [Online]. Available: http://www.oracle.com. Accessed on 1st April, 2007

  28. ANSYS [online]. Available: http://www.ansys.com. Accessed on 1st April, 2007

  29. DoD, (1991) Reliability prediction of electronic equipment (MIL-HDBK-217F), Department of Defense, Washington, DC

  30. Steinberg DS (2001) Preventing thermal cycling and vibration failures in electronic equipment. Wiley, New York

    Google Scholar 

  31. Perkins A, Sitaraman SK (2003) Thermo-mechanical failure comparison and evaluation of CCGA and CBGA electronic packages. In: Proceedings of the 53rd electronic components and technology conference. New Orleans, United States, pp 422–430

  32. Perkins A, Sitaraman SK (2004) Vibration-induced solder joint fatigue of a ceramic column grid array (CCGA) package. In: Proceedings of the 54th electronic components and technology conference, Las Vegas, NV, United States, pp 1271–1278

  33. SysML [online]. Available: http://www.omgsysml.org. Accessed on 1st April, 2007

  34. Peak RS, Burkhart RM, Friedenthal SA, Wilson MW, Bajaj M, Kim I (2007) Simulation-based design using SysML—part 1: a parametrics primer. INCOSE international symposium, San Diego

  35. Peak RS, Burkhart RM, Friedenthal SA, Wilson MW, Bajaj M, Kim I (2007) Simulation-based design using SysML—part 2: celebrating diversity by example. INCOSE international symposium, San Diego

  36. Sudarsan R, Fenves SJ, Sriram RD, Wang F (2005) A product information modeling framework for product lifecycle management. Comput Aided Des 37:1399–1411

    Article  Google Scholar 

Download references

Acknowledgments

We gratefully acknowledge the following people at Georgia Tech for their helpful comments and cooperation in this research: Jamie Ahmad, Manas Bajaj, Shashikant Hegde, Karan Kacker, Kevin Klein, Kang Joon Lee, Andrew Perkins, Raghuram Pucha, Krishna Tunga, and Jiantao Zheng. We also acknowledge LKSoftWare GmbH for use of JSDAI and STEP-Book toolkit.

Author information

Authors and Affiliations

  1. Productivity Research Institute, LG Electronics Inc., 19-1, Cheongho-ri, Jinwi-myeon, Pyeongtaek-si, Gyeonggi-do, 451-713, South Korea

    Injoong Kim

  2. Product and Systems Lifecycle Management Center, Georgia Institute of Technology, Atlanta, GA, 30332-0560, USA

    Russell S. Peak

  3. Computer-Aided Simulation of Packaging Reliability Laboratory, George W. Woodruff School of Mechanical Engineering, Georgia Institute of Technology, Atlanta, GA, 30332-0405, USA

    Suresh K. Sitaraman

Authors
  1. Injoong Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Russell S. Peak
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Suresh K. Sitaraman
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Injoong Kim.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kim, I., Peak, R.S. & Sitaraman, S.K. ROM: a reliability knowledge representation for collaborative system design. Engineering with Computers 26, 11–33 (2010). https://doi.org/10.1007/s00366-009-0135-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00366-009-0135-4

Keywords

Search

Navigation