Implementing continuous improvement using genetic

algorithms

Petter Øgland, Department of Informatics, University of Oslo

QMOD/ICQSS Conference, Verona, Aug 28th 2009

Structure of presentation

1. Introduction

2. Literature review of CQI methods

3. The new CQI method

4. Example of new method in practical use

5. Discussion

6. Conclusion

Classical QMOD: Deming & Lewin

Deming (1986): Plan, Do, Check, ActJuran (1986): Plan, Control, Improve

Lewin (1950): Unfreeze, change, freeze

Unpredictable organizations where project-by-project approaches fail

Genetic Algorithms: Cultivate the flock rather than the individuals

Research questions

• RQ1: Is it possible to use the GA approach for effective QMS design?

• RQ2: If it is possible, why is it not used?

Structure of presentation

1. Introduction

2. Literature review of CQI methods

3. The new CQI method

4. Example of new method in practical use

5. Discussion

6. Conclusion

GA for understanding OD

• Genetic Algorithms (GA) has been suggested for QM as a part of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

• GA on a metaphorical level (Goldstein, 1993; Nelson & Winter, 1982)

• Simulation models based on GA (Bruderer & Singh, 1996)

• GA as integrated part of decision support systems (Greer & Ruhe, 2003)

GA for implementing TQM

Embracing control (OR)

Embracing chaos (CAS)

Organizational development (OD)

Lewin (1950) Goldstein (1993)

Dooley (2000)

Quality management (TQM)

Juran (1964)

Deming (1986)

Imai (1986)???

Structure of presentation

1. Introduction

2. Literature review of CQI methods

3. The new CQI method

4. Example of new method in practical use

5. Discussion

6. Conclusion

Genetic Algorithm (Wikipedia, 2009)

• Choose initial population• Evaluate the fitness of each individual in the

population • Repeat until termination: (time limit or sufficient

fitness achieved) – Select best-ranking individuals to reproduce– Breed new generation through crossover and/or

mutation (genetic operations) and give birth to offsping

– Evaluate the individual fitnesses of the offspring – Replace worst ranked part of population with

offspring

Structure of presentation

1. Introduction

2. Literature review of CQI methods

3. The new CQI method

4. Example of new method in use

5. Discussion

6. Conclusion

Example: The KLIBAS system

• 1991-95– Formal development project– High prestige, management commitment– Project “completed”, but nothing worked

• 1996-99– Informal maintenance cycle– Low prestige, little management commitment– Problems, complaints requests fixed as reported– A practical and useful system develop through many

small iterations

Process maturity in KLIBAS due to managing knowledge/power

Development project

Maintenance process

On paper Systematic (managed by people)

Chaotic

In reality Chaotic Systematic

(managed by computer)

QMS as CAS with automated Pareto analysis at the nexus

Pareto analysis

PRECIP: Manual precipitation stations

AWS: Automatic weather stations

METAR: Airport weather stations

UASS: upper air sounding stations

HIRLAM: quality control by use of forecast data

Monitoring of system outputs and users (customer satisfaction)

SYNOP

System monitoring

e-mail

e-mail

e-maile-mail

e-mail

e-maile-mail

e-mail

GA implementation of daily maintenance & development

Evaluate population:Real-time and nightly automatic data collection for total system by use of e-mail.

Select solutions for next population:Run a Pareto analysis for setting the agenda for the day. This defines the population of processes to be improved.

Perform crossover and mutation:Read, write, discuss; design and implement etc.; the daily practical work of process improvement.

Enter office on the morning of day i.

Exit office in the afternoon of day i.

i: = i + 1

Productivity indicator

0

20

40

60

80

100

120

140

1992

1993

1994

1995

1996

1997

1998

1999

Productivity AVG = 91UCL = 112 LCL = 70

Structure of presentation

1. Introduction

2. Literature review of CQI methods

3. The new CQI method

4. Example of new method in practical use

5. Discussion

6. Conclusion

Is GA the same as kaizen?

Kaizen GA

Similarities Technical kaizen sounds like GA (Imai, 1986)

Social GA sounds like kaizen (Goldberg, 2000)

Differences Social implementation (skills and attitudes)

Technical implementation (following an algorithm)

GA is a SPECIAL type of kaizen

• It is strictly mathematical (an algorithm), not dependent on intuitive or cultural skills

• It is ”stupid” in the sense that each ant in a colony has a lesser brain than an elephant

• It is ”unfocused” as it aims for many improvements at the same time

• It is ”inefficient” as it progresses by trial and error

But it works!

Why others do not use this approach

1. People are unwilling to be run by computer

2. The GA approach generates complexity

3. It is “common knowledge” that the unfreeze-change-freeze approach is the “one best way”

4. TQM personnel lack technical skills for understanding GA

5. GA makes TQM invisible and thus a poor choice when wanting work acknowledgement

Structure of presentation

1. Motivation

2. Overview of current CQI methods

3. The new CQI method

4. Example of method in use

5. Discussion

6. Conclusion

Conclusion

• There are sociological reasons why people might reject the GA approach to TQM, although it WORKS and it is SIMPLE to implement

• The GA approach seems well-suited for designing QMS bottom-up in complex organizations or as a TQM method for people who enjoy living in chaos

Thank you