Shimon Y. Nof

PRISM Center & School of Industrial Engineering

Purdue University, West Lafayette, Indiana

IIE/CIS Webinar, Thursday, February 16, 2012

nof@purdue.edu

2

• With our co-workers?

• With clients?

• With family members?

• With / through computers?

Answer : A lot!

• Is it effective? Can it be improved?

Humans-Humans ◦ Face to face

◦ Cyber-enabled This webinar; Social networks

◦ Cyber-supported Our goal through this webinar

Humans-Computers

Computers-Computers

◦ Agent-Agent (software agents)

◦ Robot teams

◦ Sensor networks

3

Objective

4

Broaden

science and

engineering

knowledge

Difficulties to

locate &

integrate

distributed

knowledge for

collaborative

understanding

HUB-CI to

enable +

optimize

human, system

and research

collaboration

HUB-CI: Integrate CI (Collaborative Intelligence) and CCT (Collaborative Control Theory ) to aid existing/emerging HUBs for service networks; innovation, education, and supply networks.

4

1. CRP : Collaboration Requirement Planning 2. Parallelism & KISS : Parallelize+“Keep it simple, cyber system!” 3. CEDP : Conflict & Error Detection and Prognostics 4. FTT : Fault-Tolerance by Teaming 5. JLR : Join/Leave/ Remain in a collaborative network 6. LOCC: Lines of Command and Collaboration (emergent)

Better than existing HUBs, HUB-CI focuses on improving human collaboration through CCT collaboration support

The concept of CI

Collaboratorium (Nof, 11)

5

Collaboration Science = CCT + CSS

Emerging global networks

(hubs/clouds) to

trade/adapt/engage/learn

diverse ideas through

collaboration

But…challenges:

◦ Cross-culture capabilities?

◦ Multi-cultural interaction

and infrastructures?

◦ Challenged web-based

applications?

◦ Asynchronous multimedia?

6

Challenges of EU-India Cross

Innovation Network targeted by

HUB-CI

6

nanoHUB ◦ A HUB for research, education, and training in nano-technology

◦ Collaboration & resource

sharing

◦ Plenty of simulation tools

◦ Direct access without

installation

But…challenges: ◦ Interactive resource

visualization?

◦ Tag clustering analysis?

◦ Best matching protocols?

◦ Intuitive interaction techniques?

7

Challenges of nanoHUB

addressed by HUB-CI

7

cceHUB (Cancer Care Engineering HUB)

◦ Combination of clinical, scientific and engineering disciplines

◦ Expose current paradigms

of cancer

◦ Share cancer related research

◦ Effectively exchange any materials

But…challenges:

◦ Research document repository

◦ Smart search engine

◦ Task assignment ability

◦ Selective posting and meeting

coordinating tools

8

Challenges of cceHUB

targeted by HUB-CI

8

◦ Combined marketing, mfg. & logistics engineering disciplines

◦ Select best models

of supply

◦ Help customers’ needs

◦ Effectively exchange

useful information

But…challenges:

◦ Knowledge repository

◦ Smarter search engine

◦ Task scheduling ability

◦ Automatic knowledge

matching through HUB tools

9

Challenges of Supply HUBs

targeted by HUB-CI

9

10

HUB-CI

CNO

Collaborative

Network

Optimization

KBMP

Knowledge Best

Matching

Protocols

Co-Vis

Collaborative

Visualization

Optimizes the networking by

using CRP, FTT, JLR, LOCC principles

Suggests appropriate knowledge &

tools to users by CRP, CEDP principles

Uses dynamic matching of

analytics, applying KISS

principle

10

11

Our goal:

Faster and better achievement of the collaboration goal by automated support, to:

1) Significantly enhance synthesis and integration of knowledge and discoveries

2) Understand the dynamics of interactive- collaborative research work

3) Timely delivery of critically needed discoveries and shared knowledge

11

1. Catlin, A.C. 2008. cceHUB: A Knowledge Discovery Environment for Cancer Care Engineering Research, HUBzero Workshop.

2. Chen, X.W., Nof, S.Y., 2009. Automating error and conflict prognostics and prevention, Ch. 30, Springer Handbook of Automation (S.Y. Nof, Ed.)

3. Chen, X.W., Nof, S. Y. 2010. A decentralized conflict and error detection and prediction model, International Journal of Production Research, 48(16), pp. 4829-43.

4. Chen, X.W., Nof, S.Y. 2012. Agent-based error prevention algorithms, Expert Systems with Applications, 39(1), pp. 280-287.

5. Chituc, C. M. Nof, S. Y., 2007. The Join/ Leave/ Remain (JLR) decision in collaborative networked organizations, Computers and Industrial Engineering, 53 (1), 173–195.

6. http://ccehub.org/

7. http://nanohub.org/

8. http://www.it.bton.ac.uk/research/euindia/theproject/index.htm

9. http://www.leadershipinitiatives.org/limk.pdf

10. http://www.opensourcephysics.org/

11. http://www.scipy.org/

12. Isern, D., Moreno, A. 2008. Computer-based execution of clinical guidelines: a review, International Journal of Medical Informatics, 77(12), 787–808.

13. Isern, D., Sánchez, D., Moreno, A. 2007. HeCaSe2: a multi-agent ontology-driven guideline enactment engine, Proceedings of the 5th International Central and Eastern European Conference on Multi-Agent Systems, CEEMAS, 4696, 322–324.

14. Isern, D., Sanchez, D., Moreno, A., 2010. Agents applied in health care: a review, International Journal of Medical Informatics, 79(3), 145-66.

15. Jeong, W., Nof, S.Y. 2008. Performance evaluation of wireless sensor network protocols for industrial applications,” J. Intelligent Manufacturing, 19(3), pp. 335–345.

16. Jeong, W., Nof, S.Y. 2009. A collaborative sensor network middleware for automated production systems. Special issue on collaborative e-Work networks in industrial engineering, International Journal of Computers and IE, 57(1), pp. 106-113.

17. Klimeck, G., McLennan, M., Brophy, S.P., Adams, G.B., III, and Lundstrom, M.S., 2008. nanoHUB.org: advancing education and research in nanotechnology, Computing in Science & Engineering, 10(5), pp.17-23.

12

16. Klimeck, G., McLennan, M., Lundstrom, M.S., Adams, G.B., 2008. NanoHUB.org - online simulation and more materials for semiconductors and nanoelectronics in education and research ,8th IEEE Conference on Nanotechnology (NANO), 401-404.

17. Ko, H.S., Nof, S.Y. 2012. Design and application of task administration protocols for collaborative production and service systems, International Journal of Production Economics, 135(1), pp. 177 – 189.

18. Kostkova, P., Mani-Saada, J. Madle, G., Weinberg, J.R. 2003. Applications of Software Agent Technology in the Health Care Domain, Ch. Agent-Based Up-to-date Data Management in National Electronic Library for Communicable Disease, pp. 105–124.

19. Lee, S. 2010. Fairness, stability, and optimality of adaptive multiagent systems: interaction through resource sharing. IEEE Transactions on Automation Science and Engineering, 7(3), pp. 427-439.

20. McLennan, M., Kennell, R., 2010. HUBzero: A Platform for Dissemination and Collaboration in Computational Science and Engineering, Computing in Science & Engineering, 12(2), 48-53.

21. Nof, S.Y., 2007. Collaborative control theory for e-Work, e-Production, and e-Service, Annual Reviews in Control, 31(2), pp. 281-292.

22. Nof, S. Y., 2011. Cultural Factors: Their Impact in Collaboration Support Systems and on Decision Quality, Chapter 8 in Cultural Factors in Systems Design: Decision Making and Action (Proctor, Nof, and Yih, editors), Francis & Taylor.

23. Ok, C., Lee, S., Mitra, P. Kumara, S. 2009. Distributed energy balanced routing for wireless sensor networks, Computers & Industrial Engineering, 57(1), pp. 125-135.

24. Rajan, V. N., Nof, S. Y., 1996(a). Cooperation requirement planning (CRP) for multiprocessors: Optimal assignment and execution planning, Journal of Intelligent and Robotic Systems, 15, 419-435.

25. Rajan, V.N., Nof, S.Y., 1996(b). Minimal precedence constraints for integrated assembly and execution planning, IEEE Transaction on Robotics and Automation, Special Issue on Assembly and Task Planning, 12(4), 175-186.

26. Reyes R.L.. Scavarda, M.B., Nof, S.Y. 2012. Collaborative production line control for collaborative supply networks. Proceedings of INCOM’12, Bucharest, Romania.

27. Seok, H. Nof, S.Y. (2011). Decision Support Protocol for Sustainability Issues in Supply Networks, Proceedings of the Industrial Engineering Research Conference (IERC), Reno, NV.

28. Seok, H.S., Nof, S.Y., Filip, F.G. 2012. Sustainability Decision Support System based on Collaborative Control Theory. Annual Reviews in Control (in print).

29. Velasquez, J. D., Nof, S. Y., 2009. Best-matching protocols for assembly in e-work networks, International Journal of Production Economics, 122(1), p 508-16.

30. Velasquez J.D., Nof, S.Y. 2009. Collaborative e-Work, e-Business, and e-Service. Ch. 88, Springer Handbook of Automation (S.Y. Nof, Ed.)

31. Villa, A., Dario, A. (Eds.) 2009. A Roadmap to the Development of European SME Networks, Towards Collaborative Innovation. Springer.

32. Yoon, S.W., Nof, S.Y. 2010. Demand and capacity sharing decisions and protocols in a collaborative network of enterprises,” Decision Support Systems, 49(4), pp. 442-450.

33. Yoon, S.W. Nof, S.Y. 2011. Affiliation/dissociation decision models in demand and capacity sharing collaborative network. Int. J. of Production Economics, 130(2), pp. 135-143.

13