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Software controlled Electro‐
               Mechanical Systems Reliability
               软件控制的电子机械系统可靠
                            性

                                     David Tu
                                      杜允健
                               ©2011 ASQ & Presentation Tu
                              Presented live on Apr 13th, 2011



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  Software controlled Electro-
Mechanical Systems Reliability
                     by David Tu
 




     
AGENDA

•    Introduction
•         Government agencies
•           Standards and Guidelines
•                 Reliability model and function
•         Case Study
•           Conclusion & Discussing
INTRODUCTION


      Goal

Develop reliable software controlled electronic mechanical systems.

       Approach
          ,
Utilize agencies and regulations as supportive guidelines instead of obstacles.

      Procedures
1)             Identify government agencies
2)               Understand regulations and standards
3)                     Identify activities and develop procedures
4)
     Develop Reliability Program, MTBF analysis and test plan
5)                         Collaborate analysis and test
6)          Review results
7)                           Perform root cause analysis for findings
8)                           Collaborate and implement corrective actions
9)        Write reports
10)
Monitor and improve reliability during product life cycle
GOVERNMENT AGENCIES


• 
     Food and Drug Administration FDA http://www.fda.gov/
     Develop and enforce compliance for safety, effectiveness and reliability. FDA does not
     develop engineering specifications and standards for Medical Devices. FDA regulations are
     free for reference.

• 
 International Electrotechnical Commission http://www.iec.ch/
 Develop regulatory and engineering safety specifications and
 standards for medical device safety. Medical devices at
 European market requires CE marking. It is a self declaration
 process with the compliance of all applicable standards. IEC
 standards are available for purchase online.
GOVERNMENT REGULATIONS




                              Food and Drug Administration FDA
                                     ;                   ,
 21 CFR Parts 808, 812, and 820 Medical Devices; Current Good Manufacturing Practice (CGMP)
                           Final Rules Monday, October 7, 1996 Page 2
SUPPLEMENTARY INFORMATION: I. Background (Design controls vs. Production controls)

“Specifically, in January 1990, FDA published the results of an evaluation of device recalls that
occurred from October 1983 through September 1989, in a report entitled ‘‘Device Recalls: A Study
of Quality Problems’’. FDA found that approximately 44 percent of the quality problems that led to
voluntary recall actions during this 6-year period were attributed to errors or deficiencies that were
designed into particular devices and may have been prevented by adequate design controls.”

“A subsequent study of software-related recalls for the period of fiscal year 1983 through 1991
indicated that over 90 percent of all software related device failures were due to design related
errors, generally, the failure to validate software prior to routine production.”

Note: FDA makes CGMP as a regulation for companies to comply with.
GOVERNMENT REGULATIONS



                     Food and Drug Administration FDA

21 CFR Parts 808, 812, and 820 Medical Devices; Current Good
Manufacturing Practice (CGMP) Final Rule
A. General Provisions, page 55, § 820.3 Definitions

(b) Complaint means any written, electronic, or oral communication that
alleges deficiencies related to the identity, quality, durability, reliability,
safety, effectiveness, or performance of a device after it is released for
distribution.
;

                           General Principles of Software Validation;
                           Final Guidance for Industry and FDA Staff
                              Document issued on: January 11, 2002

2.4. Regulatory requirements for software validation
The FDA s analysis of 3140 medical device recalls conducted between 1992 and 1998 reveals
That 242 of them (7.7%) are attributable to software failures. Of those software related recalls,
192 (or 79%) were caused by software defects that were introduced when changes were
made to the software after its initial production and distribution. Software validation and other
related good software engineering practices discussed in this guidance are a principal means
of avoiding such defects and resultant recalls.

4.4. Software life cycle
Software validation takes place within the environment of an established software life cycle. The
software life cycle contains software engineering tasks and documentation necessary to support
the software validation effort. In addition, the software life cycle contains specific verification and
Validation tasks that are appropriate for the intended use of the software. This guidance does
     not
recommend any particular life cycle models - only that they should be selected and used for a
Software Development project.
;

                                  General Principles of Software Validation;
                                  Final Guidance for Industry and FDA Staff
                                     Document issued on: January 11, 2002

3.3. SOFTWARE IS DIFFERENT FROM HARDWARE
While software shares many of the same engineering tasks as hardware, it has some very
Important differences. For example:

•  One of the most significant features of software is branching, i.e., the ability to execute
  alternative series of commands, based on differing inputs. This feature is a major contributing factor for
   another characteristic of software – its complexity. Even short programs can be very complex and difficult
   to fully understand.

•  Typically, testing alone cannot fully verify that software is complete and correct. In addition to testing, other
   verification techniques and a structured and documented development process should be combined to
   ensure a comprehensive validation approach.

•  Unlike hardware, software is not a physical entity and does not wear out. In fact, software may improve with
   age, as latent defects are discovered and removed. However, as software is constantly updated and
   changed, such improvements are sometimes countered by new defects introduced into the software during
   the change.

•  Unlike some hardware failures, software failures occur without advanced warning. The
  software s branching that allows it to follow differing paths during execution, may hide some
  latent defects until long after a software product has been introduced into the marketplace.
;

                            General Principles of Software Validation;
                            Final Guidance for Industry and FDA Staff
                               Document issued on: January 11, 2002

•  Another related characteristic of software is the speed and ease with which it can be changed. This
   factor can cause both software and non-software professionals to believe that software problems
   can be corrected easily. Combined with a lack of understanding of software, it can lead managers
   to believe that tightly controlled engineering is not needed as much for software as it is for
   hardware. In fact, the opposite is true. Because of its complexity, the development process for
   software should be even more tightly controlled than for hardware, in order to prevent problems that
   cannot be easily detected later in the development process.

•  Seemingly insignificant changes in software code can create unexpected and very significant
   problems elsewhere in the software program. The software development process should be
   sufficiently well planned, controlled, and documented to detect and correct unexpected results from
   software changes.
;

                       General Principles of Software Validation;
                       Final Guidance for Industry and FDA Staff
                                Document issued on: January 11, 2002

•  Given the high demand for software professionals and the highly mobile workforce, the software
   personnel who make maintenance changes to software may not have been involved in the
   original software development. Therefore, accurate and thorough documentation is essential.

•  Historically, software components have not been as frequently standardized and interchangeable
   as hardware components. However, medical device software developers are beginning to use
   component-based development tools and techniques. Object-oriented methodologies and the
   use of off-the-shelf software components hold promise for faster and less expensive software
   development. However, component-based approaches require very careful attention during
   integration. Prior to integration, time is needed to fully define and develop reusable software
   code and to fully understand the behavior of off-the-shelf components.

  For these and other reasons, software engineering needs an even greater level of
  Managerial scrutiny and control than does hardware engineering.
Reliability model and function
A Reliability Program detects, identifies and mitigates the risks of
product defects.


                         Design Inputs and
                             Planning

     End of Life                                Design Verification
    Analysis and                                 and Validation
      Report


                            Reliability
                            Program
                           Management




   Full Market Release                       Limited Commercial
    Surveillance and                         Release Surveillance
         Control                                 and Control
Reliability model
Reliability Modeling with assumptions
      Mechanical

Mechanical reliability is assumed to be a Normal distribution.


Hardware (Electronic systems, subsystems, components, connectors and PCBA etc.)
                                                        )

Reliability function is assumed to be an Exponential distribution. Its Mean (MTBF) is
a Chi-Square distribution. Include infant mortality and wear-out high failure rate periods.

      Software
                                             ,
Software reliability function is assumed to be a discrete uniform distribution with constant
failure rates.

     System
                              ,


System Reliability function is assumed to be a combination of Normal, Exponential and discrete uniform
distribution. Mechanical MTBF is the mean of a normal distribution. Hardware and Software MTBF is a Chi-
Square distribution. System has higher failure rates at infant mortality and wear-out periods. Software failure rate
elevates System failure rate Bathtub curve. The combination of three sub-systems need more study. Should be
modeled by life tests, not mathematical models.
Reliability Modeling Diagram
                                     System
                         Software/Electronic/Mechanical
                               Confidence = 80%
                                Reliability = 90%



                                  Software
                              Confidence = 80%
                              Reliability = 96%



                                 Electronics
                               Confidence = 80%
                               Reliability = 96%




                                 Mechanical
                               Confidence = 80%
                               Reliability = 96%



•  Allocate 7.7% x 5 factor to estimated failure rate for software reliability
•  Mechanical part has the highest failure rate allocation by author’s experience
•  Field return database provides realistic pictures
CASE STUDY
                          产     Pre Production Release


                      PRODUCT: Pacemaker Interrogating Equipment


                  Tests Performed

•             (           ) Performance tests (Various Pacemakers)
• 
     Safety (Electromagnetic Compatibility and Safety per CE marking regulation)
• 
     Environmental tests (Vibration, Temperature, Humidity)
• 
   MTBF Prediction (SR-332)
•  风险
   Risk Analysis
• 
   Failure Mode Effects and Criticality Analysis
•  Submit and obtain FDA approval
CASE STUDY
                                 Production Release
                       PRODUCT: Pacemaker Interrogating Equipment
•             Supplier surveillance
 -               Supplier yield improvement
 -
    Supplier final inspection and test control, development and implementation
•                   Production quality assurance
 - 进 检验 试验开发 实
   Incoming inspection and test development and implementation
 -
   Production line inspection and test development and implementation
•                          Engineering update and upgrade controls
 -
    Review, re-test, re-verify and control changes
•                   Field returns management
 -                  Root Cause Analysis
 -
    Engineering for all identified failures
 - Re-verification and implement solutions
 - Document all findings and corrective actions

 -
 -
CASE STUDY

 PRODUCT: Pacemaker Interrogating Equipment

         End of Product Life Cycle Analysis


•      Documentation  
- 
- Equipment models, serial numbers and corrective actions
- 
- What, when, who, where, why and how

•  
-
  Failure Return data base analysis
•                        FDA
 •        FDA              IEC60601 - 1                 ,            ISO14971
       EN1441 IEC60601 - 1 – 4
 • 

   
 •  

                                    SUMMARY

•  Author confirms FDA failure rate guidance by experience
•  Comply with FDA Good Manufacturing Practice, IEC60601-1 Safety,
   Risk Analysis per ISO14971(EN1441) & IEC60601-1-4
•  Perform Risk Analysis, Failure Mode Effects and Criticality Analysis, MTBF
   prediction, Accelerated Life Tests, Environmental tests, Validation tests & Safety
   compliance tests
•  Analyze test results, confirm root causes and collaborate corrective actions

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Software controlled electron mechanical systems reliability

  • 1. Software controlled Electro‐ Mechanical Systems Reliability 软件控制的电子机械系统可靠 性 David Tu 杜允健 ©2011 ASQ & Presentation Tu Presented live on Apr 13th, 2011 http://reliabilitycalendar.org/The_Reli ability_Calendar/Webinars_‐ _Chinese/Webinars_‐_Chinese.html
  • 2. ASQ Reliability Division  Chinese Webinar  Series One of the monthly webinars  on topics of interest to  reliability engineers. To view recorded webinar (available to ASQ Reliability  Division members only) visit asq.org/reliability To sign up for the free and available to anyone live  webinars visit reliabilitycalendar.org and select English  Webinars to find links to register for upcoming events http://reliabilitycalendar.org/The_Reli ability_Calendar/Webinars_‐ _Chinese/Webinars_‐_Chinese.html
  • 3. http://sites.google.com/site/resiliencereliability/ Software controlled Electro- Mechanical Systems Reliability by David Tu
  • 4.      
  • 5. AGENDA •  Introduction •  Government agencies •  Standards and Guidelines •  Reliability model and function •  Case Study •  Conclusion & Discussing
  • 6. INTRODUCTION Goal Develop reliable software controlled electronic mechanical systems. Approach , Utilize agencies and regulations as supportive guidelines instead of obstacles. Procedures 1) Identify government agencies 2) Understand regulations and standards 3) Identify activities and develop procedures 4) Develop Reliability Program, MTBF analysis and test plan 5) Collaborate analysis and test 6) Review results 7) Perform root cause analysis for findings 8) Collaborate and implement corrective actions 9) Write reports 10) Monitor and improve reliability during product life cycle
  • 7. GOVERNMENT AGENCIES •  Food and Drug Administration FDA http://www.fda.gov/ Develop and enforce compliance for safety, effectiveness and reliability. FDA does not develop engineering specifications and standards for Medical Devices. FDA regulations are free for reference. •  International Electrotechnical Commission http://www.iec.ch/ Develop regulatory and engineering safety specifications and standards for medical device safety. Medical devices at European market requires CE marking. It is a self declaration process with the compliance of all applicable standards. IEC standards are available for purchase online.
  • 8. GOVERNMENT REGULATIONS Food and Drug Administration FDA ; , 21 CFR Parts 808, 812, and 820 Medical Devices; Current Good Manufacturing Practice (CGMP) Final Rules Monday, October 7, 1996 Page 2 SUPPLEMENTARY INFORMATION: I. Background (Design controls vs. Production controls) “Specifically, in January 1990, FDA published the results of an evaluation of device recalls that occurred from October 1983 through September 1989, in a report entitled ‘‘Device Recalls: A Study of Quality Problems’’. FDA found that approximately 44 percent of the quality problems that led to voluntary recall actions during this 6-year period were attributed to errors or deficiencies that were designed into particular devices and may have been prevented by adequate design controls.” “A subsequent study of software-related recalls for the period of fiscal year 1983 through 1991 indicated that over 90 percent of all software related device failures were due to design related errors, generally, the failure to validate software prior to routine production.” Note: FDA makes CGMP as a regulation for companies to comply with.
  • 9. GOVERNMENT REGULATIONS Food and Drug Administration FDA 21 CFR Parts 808, 812, and 820 Medical Devices; Current Good Manufacturing Practice (CGMP) Final Rule A. General Provisions, page 55, § 820.3 Definitions (b) Complaint means any written, electronic, or oral communication that alleges deficiencies related to the identity, quality, durability, reliability, safety, effectiveness, or performance of a device after it is released for distribution.
  • 10. ; General Principles of Software Validation; Final Guidance for Industry and FDA Staff Document issued on: January 11, 2002 2.4. Regulatory requirements for software validation The FDA s analysis of 3140 medical device recalls conducted between 1992 and 1998 reveals That 242 of them (7.7%) are attributable to software failures. Of those software related recalls, 192 (or 79%) were caused by software defects that were introduced when changes were made to the software after its initial production and distribution. Software validation and other related good software engineering practices discussed in this guidance are a principal means of avoiding such defects and resultant recalls. 4.4. Software life cycle Software validation takes place within the environment of an established software life cycle. The software life cycle contains software engineering tasks and documentation necessary to support the software validation effort. In addition, the software life cycle contains specific verification and Validation tasks that are appropriate for the intended use of the software. This guidance does not recommend any particular life cycle models - only that they should be selected and used for a Software Development project.
  • 11. ; General Principles of Software Validation; Final Guidance for Industry and FDA Staff Document issued on: January 11, 2002 3.3. SOFTWARE IS DIFFERENT FROM HARDWARE While software shares many of the same engineering tasks as hardware, it has some very Important differences. For example: •  One of the most significant features of software is branching, i.e., the ability to execute alternative series of commands, based on differing inputs. This feature is a major contributing factor for another characteristic of software – its complexity. Even short programs can be very complex and difficult to fully understand. •  Typically, testing alone cannot fully verify that software is complete and correct. In addition to testing, other verification techniques and a structured and documented development process should be combined to ensure a comprehensive validation approach. •  Unlike hardware, software is not a physical entity and does not wear out. In fact, software may improve with age, as latent defects are discovered and removed. However, as software is constantly updated and changed, such improvements are sometimes countered by new defects introduced into the software during the change. •  Unlike some hardware failures, software failures occur without advanced warning. The software s branching that allows it to follow differing paths during execution, may hide some latent defects until long after a software product has been introduced into the marketplace.
  • 12. ; General Principles of Software Validation; Final Guidance for Industry and FDA Staff Document issued on: January 11, 2002 •  Another related characteristic of software is the speed and ease with which it can be changed. This factor can cause both software and non-software professionals to believe that software problems can be corrected easily. Combined with a lack of understanding of software, it can lead managers to believe that tightly controlled engineering is not needed as much for software as it is for hardware. In fact, the opposite is true. Because of its complexity, the development process for software should be even more tightly controlled than for hardware, in order to prevent problems that cannot be easily detected later in the development process. •  Seemingly insignificant changes in software code can create unexpected and very significant problems elsewhere in the software program. The software development process should be sufficiently well planned, controlled, and documented to detect and correct unexpected results from software changes.
  • 13. ; General Principles of Software Validation; Final Guidance for Industry and FDA Staff Document issued on: January 11, 2002 •  Given the high demand for software professionals and the highly mobile workforce, the software personnel who make maintenance changes to software may not have been involved in the original software development. Therefore, accurate and thorough documentation is essential. •  Historically, software components have not been as frequently standardized and interchangeable as hardware components. However, medical device software developers are beginning to use component-based development tools and techniques. Object-oriented methodologies and the use of off-the-shelf software components hold promise for faster and less expensive software development. However, component-based approaches require very careful attention during integration. Prior to integration, time is needed to fully define and develop reusable software code and to fully understand the behavior of off-the-shelf components. For these and other reasons, software engineering needs an even greater level of Managerial scrutiny and control than does hardware engineering.
  • 14.
  • 15. Reliability model and function A Reliability Program detects, identifies and mitigates the risks of product defects. Design Inputs and Planning End of Life Design Verification Analysis and and Validation Report Reliability Program Management Full Market Release Limited Commercial Surveillance and Release Surveillance Control and Control
  • 17. Reliability Modeling with assumptions Mechanical Mechanical reliability is assumed to be a Normal distribution. Hardware (Electronic systems, subsystems, components, connectors and PCBA etc.) ) Reliability function is assumed to be an Exponential distribution. Its Mean (MTBF) is a Chi-Square distribution. Include infant mortality and wear-out high failure rate periods. Software , Software reliability function is assumed to be a discrete uniform distribution with constant failure rates. System , System Reliability function is assumed to be a combination of Normal, Exponential and discrete uniform distribution. Mechanical MTBF is the mean of a normal distribution. Hardware and Software MTBF is a Chi- Square distribution. System has higher failure rates at infant mortality and wear-out periods. Software failure rate elevates System failure rate Bathtub curve. The combination of three sub-systems need more study. Should be modeled by life tests, not mathematical models.
  • 18. Reliability Modeling Diagram System Software/Electronic/Mechanical Confidence = 80% Reliability = 90% Software Confidence = 80% Reliability = 96% Electronics Confidence = 80% Reliability = 96% Mechanical Confidence = 80% Reliability = 96% •  Allocate 7.7% x 5 factor to estimated failure rate for software reliability •  Mechanical part has the highest failure rate allocation by author’s experience •  Field return database provides realistic pictures
  • 19. CASE STUDY 产 Pre Production Release PRODUCT: Pacemaker Interrogating Equipment Tests Performed •  ( ) Performance tests (Various Pacemakers) •  Safety (Electromagnetic Compatibility and Safety per CE marking regulation) •  Environmental tests (Vibration, Temperature, Humidity) •  MTBF Prediction (SR-332) •  风险 Risk Analysis •  Failure Mode Effects and Criticality Analysis •  Submit and obtain FDA approval
  • 20. CASE STUDY Production Release PRODUCT: Pacemaker Interrogating Equipment •  Supplier surveillance - Supplier yield improvement - Supplier final inspection and test control, development and implementation •  Production quality assurance - 进 检验 试验开发 实 Incoming inspection and test development and implementation - Production line inspection and test development and implementation •  Engineering update and upgrade controls - Review, re-test, re-verify and control changes •  Field returns management - Root Cause Analysis - Engineering for all identified failures - Re-verification and implement solutions - Document all findings and corrective actions  -  -
  • 21. CASE STUDY PRODUCT: Pacemaker Interrogating Equipment End of Product Life Cycle Analysis •  Documentation   -  - Equipment models, serial numbers and corrective actions -  - What, when, who, where, why and how •   - Failure Return data base analysis
  • 22. •   FDA •   FDA IEC60601 - 1 , ISO14971 EN1441 IEC60601 - 1 – 4 •     •   SUMMARY •  Author confirms FDA failure rate guidance by experience •  Comply with FDA Good Manufacturing Practice, IEC60601-1 Safety, Risk Analysis per ISO14971(EN1441) & IEC60601-1-4 •  Perform Risk Analysis, Failure Mode Effects and Criticality Analysis, MTBF prediction, Accelerated Life Tests, Environmental tests, Validation tests & Safety compliance tests •  Analyze test results, confirm root causes and collaborate corrective actions