1. S YSTEMIC V ULNERABILITY A NALYSIS OF A H IGH -F UNCTION ATM Tina Chang Lindsay Wiseman Juthamas Choomlucksana

2. O VERVIEW OF C ONTENTS Introduction Background Motivation for Analysis Literature Review Objectives of Research

3. O VERVIEW OF C ONTENTS Introduction Background Motivation for Analysis Literature Review Objectives of Research Methodology IDEF0 HMSEM Workbook

4. O VERVIEW OF C ONTENTS Introduction Background Motivation for Analysis Literature Review Objectives of Research Methodology IDEF0 HMSEM Workbook Recommendations

5. B ACKGROUND New high-function ATM is still in the design phase Made assumptions in regards to the user interface due to the information being proprietary

6. B ACKGROUND New high-function ATM is still in the design phase We had to make assumptions in regards to the user interface due to the information being proprietary High-function ATM Requires user to sign up as member to use services Have their picture taken Scan their finger print Enter in personal information Social security number, phone number, address, etc.

7. B ACKGROUND New high-function ATM is still in the design phase We had to make assumptions in regards to the user interface due to the information being proprietary High function ATM User must sign up for the services Scanning their personal identification Scanning their finger print Enter in personal information Social security number, phone number, address, etc. The ATM will then verify the information to accept or reject the application.

8. M OTIVATION FOR A NALYSIS Human errors increase as automatic teller machines become more sophisticated.

9. M OTIVATION FOR A NALYSIS Human errors increase as automatic teller machines become more sophisticated. Leaves both long-time and new customers frustrated when they attempt to complete a wide range of transactions.

10. M OTIVATION FOR A NALYSIS Human errors increase as automatic teller machines become more sophisticated. Leaves both long-time and new customers frustrated when they attempt to complete a wide range of transactions. A thorough human engineering psychology analysis can give a product design-criterion to avoid these frustrations and help keep their customers satisfied.

11. L ITERATURE R EVIEW (1) Zimmermann and Bridger (2000) developed two ATM interfaces to compare the efficiency and error profiles in current use: Green monochrome Color display with newer displays and distinctly different software

12. L ITERATURE R EVIEW (1) Zimmermann and Bridger (2000) developed two ATM interfaces to compare the efficiency and error profiles in ATM current use: Green monochrome Color display with newer displays and distinctly different software Results showed withdrawals were the most frequent transactions at ATMs by observing 300 members using ATMs in South Africa.

13. L ITERATURE R EVIEW (2) In 2003, Chan and Khalid used automatic speech recognition technology to investigate users’ usability and affective interaction with ATM.

14. L ITERATURE R EVIEW (2) In 2003, Chan and Khalid used automatic speech recognition technology to investigate users’ usability and affective interaction with ATM. All participants were required to be a current ATM user or at least possess an ATM card.

15. L ITERATURE R EVIEW (2) In 2003, Chan and Khalid used automatic speech recognition technology to investigate users’ usability and affective interaction with ATM. All participants were required to be a current ATM user or at least possess an ATM card. Participants performed two tasks, withdrawal and balance enquiry, using a real-world ATM. Showed that automatics speech recognition technology will not only improve system usability, but it also created a flexible interface in traditional ATM.

16. L ITERATURE R EVIEW (2) In 2003, Chan and Khalid used automatic speech recognition technology to investigate users’ usability and affective interaction with ATM. All participants were required to be a current ATM user or at least possess an ATM card. Participants performed two tasks, withdrawal and balance enquiry, using a real-world ATM. Showed that automatics speech recognition technology will not only improve system usability, but it also created a flexible interface in traditional ATM. Moreover, user emotions in terms of fun, joy and excitement should consider in design of affective user interface.

17. L ITERATURE R EVIEW (3) As Norman (1988) addressed, a good user interface can minimize the gap between the user’s knowledge and intentions with the system. Other perspectives to include in ATM design; Age Usability by the blind Psychological attitudes to innovativeness and computers (e.g., Adams and Thieben 1991, Mankze et al. 1992, Burgoyne et al. 1992)

18. O BJECTIVES Create a complete model of all transactions the customer can complete using this ATM

19. O BJECTIVES Create a complete model of all transactions the customer can complete using this ATM Compile a thorough list of human fallibilities that can occur

20. O BJECTIVES Create a complete model of all transactions the customer can complete using this ATM Compile a thorough list of human fallibilities that can occur Create a list of recommendations for ATM design project manager and engineers to prevent these errors from occurring

21. M ETHODOLOGY IDEF0 Model

22. M ETHODOLOGY IDEF0 Model Human Machine System Engineering Methodology (HMSEM) Workbook Informal List of Potential Errors

23. M ETHODOLOGY IDEF0 Model Human Machine System Engineering Methodology (HMSEM) Workbook Informal List of Potential Errors Task analysis

24. M ETHODOLOGY IDEF0 Model Human Machine System Engineering Methodology (HMSEM) Workbook Informal List of Potential Errors Task analysis Human Fallibility Identification and Remediation Methodology (HFIRM) Analysis

25. M ETHODOLOGY IDEF0 Model Human Machine System Engineering Methodology (HMSEM) Workbook Informal List of Potential Errors Task analysis Human Fallibility Identification and Remediation Methodology (HFIRM) Analysis Failure Modes and Effects Analysis (FMEA) analysis

26. IDEF0 M ODEL Used to represent all activities involved to complete a wide variety of transactions from the customers’ perspective Included all controls, mechanisms, inputs and outputs for every activity the customer will be involved it These mechanisms and controls were then further evaluated to help create an informal list of potential human errors.

27. IDEF0 L EVEL A-0

28. IDEF0 L EVEL A0

29. I NFORMAL L IST OF P OTENTIAL E RRORS Created as we developed the IDEF0 Model Connected the list of errors to where they could occur within the node list Examples Customer forgets to take ATM card back after sign- out process Customer fails to enter in correct PIN because of layout of keypad Customer may choose the wrong transaction because of poor viewing conditions

30. T ASK A NALYSIS Fill in the following bits of information for ten selected ‘youngest’ children Purpose/Value Added

31. T ASK A NALYSIS Fill in the following bits of information for ten selected ‘youngest’ children Purpose/Value Added Location

32. T ASK A NALYSIS Fill in the following bits of information for ten selected ‘youngest’ children Purpose/Value Added Location Frequency & Timing

33. T ASK A NALYSIS Fill in the following bits of information for ten selected ‘youngest’ children Purpose/Value Added Location Frequency & Timing Environmental Conditions

34. T ASK A NALYSIS Fill in the following bits of information for ten selected ‘youngest’ children Purpose/Value Added Location Frequency & Timing Environmental Conditions Information Requirements

35. T ASK A NALYSIS Fill in the following bits of information for ten selected ‘youngest’ children Purpose/Value Added Location Frequency & Timing Environmental Conditions Information Requirements Sensory/Congitive/Motor Actions

36. T ASK A NALYSIS E XAMPLE A221: C HOOSE ACCOUNT TO WITHDRAW FROM Purpose / Value Added Location Frequency & Timing Environmental Conditions Information Requirements Sensory / Cognitive / Motor Actions Allow customer to identify which account to withdraw cash from. Command window 1 per withdraw transaction Lighting, and weather condition surrounding ATM. Poor lighting condition can make it difficult for customer to be able to read the command window. Bright lighting condition can make it difficult for customer to be able to read the command window. Poor weather condition can limit customer ability to read the command window. 1.Customers should know which accounts they are able to withdraw from. 2. Customers should know if they sufficient funds to withdraw. 1.Decision making which account to withdraw from. 2.Visual sensation to be able to read all account titles. 3.Customer must be able to reach the command window.

37. Used the Human Fallibility Identification and Remediation Database (HFIRDB) to identify a formal list of human fallibilities for four of the ‘youngest children’ Continued our analysis using FMEA HFIRM A NALYSIS

38. FMEA A NALYSIS Completed analysis for all applicable human fallibilities that were identified using the HFIRM analysis. This helped us identify the following; (Other) Contributing Factor(s) Potential Failure Mode Potential Effects of Failure Mode Risk Priority Number (RPN) RPN = Severity ∙ Probability ∙ Nondetectability

39. FMEA A NALYSIS E XAMPLE : A221: C HOOSE ACCOUNT TO WITHDRAW FROM HF_ID Human Fallibility Definition (Other) Contributing Factor(s) Potential Failure Mode Potential Effects of Failure Mode Severity Probability Nondetectability RPN 95Word shape effect Tendency for words comprised of mixed- case letters to be recognized as global shapes and to be processed quickly and automatical ly when presented as printed sentences. mixed word format, size, case (words shape inconsistent) misreading, misinterpretati on selected the wrong account to withdraw from 52110

40. R ECOMMENDATIONS Make sure all features are physically accessible by roughly 95% of adults Redundancy Use lighted features on ATM to be activated when necessary as well as short video clips to show customer how to use all features Color coding on command window and keypad Audio cues to give warning/aid Proper lighting of the ATM Glare-free screen Light attached to ATM for camera use Group common transactions

41. Q UESTIONS ?

42. R EFERENCES Adams, A. S., and Thieben, K.A., (1991), “Automatic Teller Machines and the Older Population”, Applied Ergonomics, 22, 85-90. Burford, B. C., and Stanton, N. A., (1993), “ A User-centered Evaluation of a Simulated Adaptive Autoteller”, Contemporary Ergonomics, London, UK: Taylor and Francis Ltd, 117-122. Chan, F. Y., and Khalid, H. M., (2003), “Is Talking to an Automated Teller Machine Natural and Fun?”, Ergonomics, 46, 1386-1407. Mankze, J. M., Egan, D., H., Felix, D., and Krueger, H., (1998), “What Makes an Automated Teller Usable by Blind Users?”, Ergonomics, 41, 982-999. Norman, D. A., (1998), “The Design of Everyday Things”, Now York, Doubleday.