systemic vulnerability analysis of a high functioning atm...

SYSTEMIC VULNERABILITY ANALYSIS OF A HIGH-FUNCTION ATM

Tina ChangLindsay WisemanJuthamas Choomlucksana

OVERVIEW OF CONTENTS Introduction

Background Motivation for Analysis Literature Review Objectives of Research



Methodology IDEF0 HMSEM Workbook



Methodology IDEF0 HMSEM Workbook

Recommendations

BACKGROUND New high-function ATM is still in the design phase

Made assumptions in regards to the user interface due to the information being proprietary

BACKGROUND 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.

BACKGROUND 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.

MOTIVATION FOR ANALYSIS 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.



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.

LITERATURE REVIEW (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

LITERATURE REVIEW (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.

LITERATURE REVIEW (2) In 2003, Chan and Khalid used automatic

speech recognition technology to investigate users’ usability and affective interaction with ATM.


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.


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.


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.

LITERATURE REVIEW (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)

OBJECTIVES Create a complete model of all transactions

the customer can complete using this ATM


the customer can complete using this ATM Compile a thorough list of human fallibilities

that can occur


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

METHODOLOGY IDEF0 Model

METHODOLOGY IDEF0 Model Human Machine System Engineering

Methodology (HMSEM) Workbook Informal List of Potential Errors


Methodology (HMSEM) Workbook Informal List of Potential Errors Task analysis


Methodology (HMSEM) Workbook Informal List of Potential Errors Task analysis Human Fallibility Identification and Remediation

Methodology (HFIRM) Analysis


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

IDEF0 MODEL 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.

IDEF0 LEVEL A-0

IDEF0 LEVEL A0

INFORMAL LIST OF POTENTIAL ERRORS 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

TASK ANALYSIS Fill in the following bits of information for ten

selected ‘youngest’ children Purpose/Value Added


selected ‘youngest’ children Purpose/Value Added Location


selected ‘youngest’ children Purpose/Value Added Location Frequency & Timing


selected ‘youngest’ children Purpose/Value Added Location Frequency & Timing Environmental Conditions


selected ‘youngest’ children Purpose/Value Added Location Frequency & Timing Environmental Conditions Information Requirements


selected ‘youngest’ children Purpose/Value Added Location Frequency & Timing Environmental Conditions Information Requirements Sensory/Congitive/Motor Actions

TASK ANALYSIS EXAMPLEA221: CHOOSE ACCOUNT TO WITHDRAW FROM

Purpose / Value Added Location Frequency

& TimingEnvironmental

ConditionsInformation Requirement

s

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.

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 ANALYSIS

FMEA ANALYSIS 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

FMEA ANALYSIS EXAMPLE:A221: CHOOSE ACCOUNT TO WITHDRAW FROM

HF_ID HumanFallibility Definition

(Other) Contributing Factor(s)

Potential Failure Mode

Potential Effects of

Failure Mode

Severity

Probability

Nondetectability

RPN

95 Word shape effect

Tendency for words comprised of mixed-

case letters to

be recognized as global shapes

and to be processed

quickly and

automatically when

presented as printed sentences.

mixed word format, size, case (words

shape inconsistent)

misreading, misinterpretati

on

selected the wrong account to

withdraw from

5 2 1 10

RECOMMENDATIONS 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

QUESTIONS?

REFERENCES 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.

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