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1 Multidisciplinary Teams and Knowledge Models Professor M Neil James Faculty of Technology University of Plymouth.

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Presentation on theme: "1 Multidisciplinary Teams and Knowledge Models Professor M Neil James Faculty of Technology University of Plymouth."— Presentation transcript:

1 1 Multidisciplinary Teams and Knowledge Models Professor M Neil James Faculty of Technology University of Plymouth

2 2 Multidisciplinary Teams MDT's harness powerful knowledge benefits from members  Advances in technology in different areas  New ideas  Cross-fertilisation of concepts from other disciplines What knowledge do other people possess that the MDT is unaware of ?  Information retrieval/mining

3 3 Knowledge Pools Standard business model – Bonsai tree  Fruit – saleable products  Trunk – core skills  Roots generic knowledge Small and perfect Not easily capable of growth Expansion into new areas difficult

4 4 Knowledge Pools Need to 'dip' into other knowledge pools  Innovative synergies  Ready-made problem solutions  New openings for growth and product range Leads to the 'sequoia' model of business growth

5 5 Knowledge Pools Sequoia can be 80-100 m high Root system contained in top 1.5 m of soil Spreads out over 4 square acres Clone by suckers Young trees use ancient root system of adults

6 6 Knowledge Pools Young trees use ancient root system of adults  Share water resources  'Dip' into each others pools  Share root linkage  Fast growth once water supply stabilised  New roots for mutual support

7 7 Knowledge Pools Business analogy  Dipping into different knowledge bases  Mutative growth possible Fundamental process 'keys' in nature

8 8 Knowledge Pools Business analogy  Dipping into different knowledge bases  Mutative growth possible Fundamental process 'keys' in nature  Mutation

9 9 Knowledge Pools Business analogy  Dipping into different knowledge bases  Mutative growth possible Fundamental process 'keys' in nature  Mutation  Replication (cloning)

10 10 Knowledge Pools Equivalent 'keys' in business  Design innovation General Atomics Predator B unmanned aircraft

11 11 Knowledge Pools Equivalent 'keys' in business  Design innovation  Smart fabrication

12 12 Role of Team Leaders Manage problem constraints

13 13 Role of Team Leaders Manage problem constraints Coach and counsel team members

14 14 Role of Team Leaders Manage problem constraints Coach and counsel team members Resolve conflicts

15 15 Role of Team Leaders Manage problem constraints Coach and counsel team members Resolve conflicts Attributes:  Forceful

16 16 Role of Team Leaders Manage problem constraints Coach and counsel team members Resolve conflicts Attributes:  Forceful  Goal orientated

17 17 Role of Team Leaders In short, a caring Genghis Khan….. SAVE the WHALE

18 18 Application to Design MDT's drawn from several potential disciplines  Different interests  Different skills

19 19 Application to Design MDT's drawn from several potential disciplines  Different interests  Different skills Gain experience in information retrieval from different 'pools'

20 20 Application to Design MDT's drawn from several potential disciplines  Different interests  Different skills Gain experience in information retrieval from different 'pools' Harness the internet as a data mining source Image from Journal of Data Mining and Knowledge Discovery, Kluwer Academic Publishers http://www.digimine.com/usama/datamine/

21 21 Application to Design MDT's drawn from several potential disciplines  Different interests  Different skills Gain experience in information retrieval from different 'pools' Harness the internet as a data mining source Develop conceptual thought processes

22 22 Application to Design MDT's drawn from several potential disciplines  Different interests  Different skills Gain experience in information retrieval from different 'pools' Harness the internet as a data mining source Develop conceptual thought processes Develop skills in identifying critical areas in problems

23 23 Application to Design Visualise the web of linkages between:  Modules

24 24 Application to Design Visualise the web of linkages between:  Modules  Skills

25 25 Application to Design Visualise the web of linkages between:  Modules  Skills  Disciplines

26 26 Application to Design Visualise the web of linkages between:  Modules  Skills  Disciplines Individual disciplines are all part of the overall field of engineering  Interlinked  Interdependent

27 27 What Might MDT's Achieve in the Future ? Reduced product development times  Classic example is Liberty ship design  Riveted construction ~ 242 days  Welded construction < 7 days

28 28 What Might MDT's Achieve in the Future ? Reduced product development times  Classic example is Liberty ship design  Riveted construction ~ 242 days  Welded construction < 7 days Increased risk avoidance  Greater reliability  More holistic understanding of linkages/problems

29 29 What Might MDT's Achieve in the Future ? Impact of network technologies  Information access  Real communication

30 30 What Might MDT's Achieve in the Future ? Impact of network technologies  Information access  Real communication Effective knowledge capture  Higher recycling potential  Lean and efficient materials usage

31 31 What Might MDT's Achieve in the Future ? Impact of network technologies  Information access  Real communication Effective knowledge capture  Higher recycling potential  Lean and efficient materials usage 'Virtual' design and manufacturing environments  Game technology  Process modelling

32 32 What Might MDT's Achieve in the Future ? Potential limitations  Shortage of multi-skilled MDT team leaders  Loss of social dimension  Cyber-nerds There is hope however……. http://romance.live.com.au/articles/index.jsp http://romance.live.com.au/articles/snaggies.jsp


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