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Implementing continuous improvement using genetic algorithms. Petter Øgland, Department of Informatics, University of Oslo QMOD/ICQSS Conference, Verona, Aug 28th 2009. Structure of presentation. Introduction Literature review of CQI methods The new CQI method

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Implementing continuous improvement using genetic algorithms

Implementing continuous improvement using genetic algorithms

Petter Øgland, Department of Informatics, University of Oslo

QMOD/ICQSS Conference, Verona, Aug 28th 2009


Structure of presentation
Structure of presentation

  • Introduction

  • Literature review of CQI methods

  • The new CQI method

  • Example of new method in practical use

  • Discussion

  • Conclusion


Classical qmod deming lewin
Classical QMOD: Deming & Lewin

Juran (1986): Plan, Control, Improve

Deming (1986): Plan, Do, Check, Act

Lewin (1950): Unfreeze, change, freeze




Research questions
Research questions individuals

  • 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 presentation1
Structure of presentation individuals

  • Introduction

  • Literature review of CQI methods

  • The new CQI method

  • Example of new method in practical use

  • Discussion

  • 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 understanding OD


Ga for implementing tqm
GA for implementing TQM of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)


Structure of presentation2
Structure of presentation of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

  • Introduction

  • Literature review of CQI methods

  • The new CQI method

  • Example of new method in practical use

  • Discussion

  • Conclusion


Genetic algorithm wikipedia 2009
Genetic Algorithm (Wikipedia, 2009) of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

  • 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 presentation3
Structure of presentation of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

  • Introduction

  • Literature review of CQI methods

  • The new CQI method

  • Example of new method in use

  • Discussion

  • Conclusion


Example the klibas system
Example: The KLIBAS system of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

  • 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
Process maturity in KLIBAS due to managing knowledge/power of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)


Qms as cas with automated pareto analysis at the nexus

SYNOP of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

AWS: Automatic weather stations

PRECIP: Manual precipitation stations

e-mail

e-mail

e-mail

UASS: upper air sounding stations

METAR: Airport weather stations

e-mail

Pareto analysis

e-mail

e-mail

HIRLAM: quality control by use of forecast data

e-mail

e-mail

Monitoring of system outputs and users (customer satisfaction)

System monitoring

QMS as CAS with automated Pareto analysis at the nexus


Ga implementation of daily maintenance development

Enter office on the morning of day of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)i.

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.

Exit office in the afternoon of day i.

i: = i + 1

GA implementation of daily maintenance & development


Productivity indicator
Productivity indicator of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)


Structure of presentation4
Structure of presentation of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

  • Introduction

  • Literature review of CQI methods

  • The new CQI method

  • Example of new method in practical use

  • Discussion

  • Conclusion


Is ga the same as kaizen
Is GA the same as kaizen? of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)


Ga is a special type of kaizen
GA is a SPECIAL type of kaizen of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

  • 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

But it works! of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)


Why others do not use this approach
Why others do not use this approach of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

  • People are unwilling to be run by computer

  • The GA approach generates complexity

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

  • TQM personnel lack technical skills for understanding GA

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


Structure of presentation5
Structure of presentation of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

  • Motivation

  • Overview of current CQI methods

  • The new CQI method

  • Example of method in use

  • Discussion

  • Conclusion


Conclusion
Conclusion of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)

  • 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

Thank you of a more general Complex Adaptive Systems (CAS) approach (Dooley et al., 1995; Dooley, 2000)


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