A knowledge-based algorithm for supply chain conflict detection based on OTSM-TRIZ problem flow network approach

Document Type : Article

Authors

1 School of Industrial Engineering, College of Engineering, University of Tehran, Tehran, Iran

2 Young Researchers and Elite Club, Majlesi Branch, Islamic Azad University, Isfahan, Iran

3 Faculty of Engineering, Urmia University, Urmia, West Azerbaijan Province, Iran

Abstract

The coordination and integration of efforts and activities of supply chain (SC) members that is a key component of supply chain management success has become a challenging activity due to conflicts in such systems.  Lack of proper detection of conflicts in a SC and therefore mismanagement of them will increase disruption risk in the SC. In this article, a knowledge-based algorithm is presented based on the OTSM-TRIZ (general theory of powerful thinking) problem flow network approach to identify, formulate and solve the conflicts of SCs before they occur and cause harmful effects.  The proposed algorithm involves analyzing and developing network of problems (NoP) in order to transfer it into a network of conflicts. This study validated the proposed algorithm through a case demonstration. Through the implementation and application, the result demonstrated that this knowledge- based algorithm was able to identify and formulate supply chain conflicts before they occur and more importantly it greatly increased the coordination between supply chain entities.

Keywords

Main Subjects


References
1. Behzadi, G., O0Sullivan, J., Olsen, T., Scrimgeour,
F., and Zhang, A. \Robust and resilient strategies
for managing supply disruptions in an agribusiness
supply chain", International Journal of Production
Economics, 191, pp. 207-220 (2017).
2. Barutcu, S. and Dugan, H. \Supply chain-based con-

ict: A study from textile exporter's perspectives",
Journal of Global Strategic Management, 42, pp. 231-
244 (2010).
3. Lam, P.K., Chin, K.S., and Pun F.T. \Managing
con
ict in collaborative new product development: a
supplier perspective", International Journal of Quality
& Reliability Management, 24(9), pp. 891-907 (2007).
4. Vachon, S., Halley, A., and Beaulieu, M. \Aligning
competitive priorities in the supply chain: The role
of interactions with suppliers", International Journal
of Operations & Production Management, 29(4), pp.
322-340 (2009).
5. Ogunlana, S.O. and Mahato, B.K. \Con
ict dynamics
in a dam construction project: A case study", Built
Environment Project and Asset Management, 1(2), pp.
1-21 (2011).
6. Alam, T. and Faridi, M.R. \Con
icts in supply
chain management", VSRD-IJBMR, 1(10), pp. 648-
654 (2011).
7. Klibi, W. and Martel, A. \Modeling approaches for
the design of resilient supply networks under disruptions",
International Journal of Production Economics,
135(2), pp. 882-898 (2012).
8. Rice, J. and Caniato, F. \Building a secure and
resilient supply chain", Supply Chain Management
Review, 7(5), pp. 22-30 (2003).
9. Brockman, J.L. \Interpersonal con
ict in construction:
Cost, cause, and consequence", Journal of Construction
Engineering and Management, 140(2) (2014).
DOI: doi.org/10.1061/(ASCE)CO.1943-7862.0000805
10. Pyke, D. and Tang, C.S. \How to mitigate product
safety risks proactively? Process, challenges and
opportunities", International Journal of Logistics Research
and Applications: A Leading Journal of Supply
Chain Management, 13(4), pp. 243-256 (2010).
11. Hendricks, K.B. and Singhal, V.R. \The e ect of
demand-supply mismatches on rm risk", Production
and Operations Management, 23, pp. 2137-2151
(2014).
12. Hendricks, K.B. and Singhal, V.R. \The e ect of
supply chain glitches on shareholder wealth", Journal
of Operations Management, 21, pp. 501-522 (2003).
13. Hendricks, K.B. and Singhal, V.R. \An empirical
analysis of the e ect of supply chain disruptions on
long run stock price performance and equity risk of the
rm", Production and Operations Management, 14(1),
pp. 35-52 (2005).
14. Hendricks, K.B. and Singhal, V.R. \The e ect of
supply chain disruptions on shareholder value", Total
Quality Management, 19(7), pp. 777-791 (2008).
15. Lam, P.K. and Chin, K.S. \Identifying and prioritizing
critical success factors for con
ict management in
collaborative new product development", Industrial
Marketing Management, 34(8), pp. 761-772 (2005).
16. Felty, A. and Namjoshi, K. \Feature speci cation and
automated con
ict detection", ACM Transactions on
Software Engineering and Methodology, 2(1), pp. 3-27
(2003).
17. Mitkus, S. and Mitkus, T. \Causes of con
icts in a
construction industry: A communicational approach",
Procedia-Social and Behavioral Sciences, 110, pp. 777-
786 (2014).
18. Acharya, N.K., Dai, L.Y., and Kim, J.K. \Critical
construction con
icting factors identi cation using analytical
hierarchy process", KSCE Journal of Civil
Engineering, 10(3), pp. 165-174 (2006).
19. Hsieh, C., Wee, H., and Chen, A. \Resilient logistics
to mitigate supply chain uncertainty: A case study of
an automotive company", Scientia Iranica, 23(5), pp.
2287-2296 (2016).
20. John, F.R. and Prasad, P.S.S. \Supply chain con
ict
detection with colored petri nets", Journal of Advances
in Management Research, 9(2), pp. 208-216 (2012).
21. He, S., Hipel, K.W., and Kilgour, D.M. \A hierarchical
approach to study supply chain con
icts between
Airbus and Boeing", IEEE International Conference
on Systems, Man, and Cybernetics (SMC), San Diego,
CA, pp. 1559-1564 (2014).
22. He, S., Hipel, K.W., and Kilgour, D.M. \A hierarchical
graph model of a two-level carbon emission con
ict in
China", IEEE International Conference on Systems,
Man, and Cybernetics (SMC), Budapest, pp. 3423-
3428 (2016).
23. Alaei, S. and Setak, M. \Supply chain coordination via
two-way cooperative advertising contract considering
competing retailers", Scientia Iranica, 23(5), pp. 2330-
2340 (2016).
24. Khomenko, N., De Guio, R., Lelait, L., and Kaikov,
I. \A framework for OTSM-TRIZ based computer
support to be used in complex problem management",
International Journal of Computer Applications in
Technology, 30(1), pp. 88-104 (2007).
3712 J. Razmi et al./Scientia Iranica, Transactions E: Industrial Engineering 25 (2018) 3700{3712
25. Cavallucci, D., Rousselot, F., and Zanni, C. \Initial
situation analysis through problem graph", CIRP
Journal of Manufacturing Science and Technology,
2(4), pp. 310-317 (2010).
26. Cavallucci, D. and Khomenko, N. \From TRIZ to
OTSM-TRIZ: Addressing complexity challenges in
inventive design", International Journal of Product
Development, 4(1), pp. 4-21 (2007).
27. Yan, W., Liu, H., Zanni- Merk, C., and Cavallucci,
D. \Ingenious TRIZ: An automatic ontology-based
system for solving inventive problems", Knowledge-
Based Systems, 75, pp. 52-65 (2015).
28. Baldussu, A., Becattini, N., and Cascini, G. \Network
of contradictions analysis and structured identi cation
of critical control parameters", Procedia Engineering,
9, pp. 3-17 (2011).
29. Chechurin, L. and Borgianni, Y. \Understanding TRIZ
through the review of top cited publications", Computers
in Industry, 82, pp. 119-134 (2016).
30. Cheng, J. and Sheu, J. \Inter-organizational relationships
and strategy quality in green supply chains -
moderated by opportunistic behavior and dysfunctional
con
ict", Industrial Marketing Management,
41(4), pp. 563-572 (2012).
31. Ntabe, E.N., LeBel, L., Munson, A.D., and Santa-
Eulalia, L.A. \A systematic literature review of the
supply chain operations reference (SCOR) model application
with special attention to environmental issues",
International Journal of Production Economics,
169, pp. 310-332 (2015).
32. Cavallucci, D., Rousselot, F., and Zanni, C. \On
contradiction clouds", Procedia Engineering, 9, pp.
368-378 (2011).

Volume 25, Issue 6
Transactions on Industrial Engineering (E)
November and December 2018
Pages 3700-3712
  • Receive Date: 27 November 2016
  • Revise Date: 02 August 2017
  • Accept Date: 23 December 2017