Process parameter prediction via markov models of sub-activities
RAIRO - Operations Research - Recherche Opérationnelle, Volume 48 (2014) no. 3, pp. 303-324.

This work aims to fill a lacunae in the project-oriented production systems literature providing a formal analytic description of the rework effects formulae and the determination of the extended design time due to a certain degree of overlapping in a pair of activities. It is made through the utilization of concepts of workflow construction with hidden (semi) Markov models theory and establishing a way to disaggregate activities into sub-activities, in order to determine the activity parameters used by the project scheduling techniques. With the aim to make a correlation between the entropy of the state transitions and the probability of changes, the information theory is also used, and the concept of impact caused by the probability of changes is provided. Numerical examples are shown for the purpose to demonstrate the applicability of the concepts developed, and one example of overlapping of two activities is shown. The original contributions of this work are shown on the last section.

DOI: 10.1051/ro/2014009
Classification: 90B15, 90B30, 68M20
Keywords: activity parameters, sub-activities Markov model, entropy, project scheduling parameters, rework estimation
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     author = {Marujo, Lino G. and Qassim, Raad Y.},
     title = {Process parameter prediction \protect\emph{via }markov models of sub-activities},
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     publisher = {EDP-Sciences},
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Marujo, Lino G.; Qassim, Raad Y. Process parameter prediction via markov models of sub-activities. RAIRO - Operations Research - Recherche Opérationnelle, Volume 48 (2014) no. 3, pp. 303-324. doi : 10.1051/ro/2014009. http://archive.numdam.org/articles/10.1051/ro/2014009/

[1] R. Agrawal and D. Gunopulos, Mining Process Models from Workflow Logs. IBM Research Center (1998).

[2] R. Ahlswede, N. Cai, S.R. Li and R.W. Yeung, Network Information Flow. IEEE Trans. Inf. Theor. 46 (2000) 1204-1216. | MR | Zbl

[3] R. Ahmadi, T. Roemer and R.H. Wang, Structuring product development model. Eur. J. Oper. Res. 130 (2001) 539-558. | MR | Zbl

[4] Y. Bard, Estimation of state probabilities using the maximum entropy principle. IBM J. Res. Dev. 24 (1980) 563-569. | MR | Zbl

[5] P.O. Boaventura, Grafos: teoria, modelos, algoritmos. E. Blucher (1996).

[6] T.R. Browning, E. Fricke and H. Negele, Key concepts in modeling product development processes. Syst. Eng. 9 (2006) 104-128.

[7] H.H. Bui, D.Q. Phung and S. Venkatesh, Hierarchical hidden Markov models with general state hierarchy. In AAAI (2004).

[8] A.K. Chakravarty, Overlapping design and build cycles in product development. Eur. J. Oper. Res. 134 (2001) 392-424. | MR | Zbl

[9] S.H Cho and S.D. Eppinger, A simulation-based process model for managing complex design projects. IEEE Trans. Eng. Manage. 52 (2005) 316-327.

[10] J. Crampton, On the satisfiability of authorization constraints in workflow systems. Department of Mathematics, Royal Holloway, University of London (2004).

[11] P. Doshi, R. Goodwin, R. Akkiraju and K. Verma, Dynamic workflow composition using Markov decision processes. Int. J. Web Serv. Res. 2 (2005) 1-17.

[12] T.V. Duong, H.H. Bui, D.Q. Phung and S. Venkatesh, Activity recognition and abnormality detection with the switching hidden semi-Markov model. In IEEE (2005).

[13] S. Fine, Y. Singer and N. Tishby, The hierarchical hidden Markov model: analysis and applications. Mach. Learn. 32 (1998) 41-62. | Zbl

[14] D.N. Ford and J.D. Sterman, The Liar's Club: concealing rework in concurrent development. Concurr. Eng.: Res. Appl. 11 (2003) 211-119.

[15] J.E.V. Gerk and R.Y. Qassim, Project Acceleration via Activity Crashing, Overlapping and Substitution. IEEE Trans. Eng. Manage. 55 (2008) 509-601.

[16] S.T. Hackman and R.C. Leachman, An aggregate model of project-oriented production. IEEE Trans. Syst. Man Cybern. 19 (1989) 220-231.

[17] K.V. Hee et al., Scheduling-free resource management. Data Knowl. Eng. 61 (2007) 59-75.

[18] J. Herbst, An inductive approach to the acquisition and adaptation of workflow models. Daimler Chrysler AG Research and Technology (1999).

[19] J. Herbst, A machine learning approach to workflow management. Lect. Notes Comput. Sci. 1810 (2000) 183-194.

[20] J. Herbst and D. Karagiannis, Integrating machine learning and workflow management to support acquisition and adaptation of workflow models. In IEEE (1998).

[21] E.T. Jaynes, Information theory and statistical mechanics. Phys. Rev. 106 (1957) 620-630. | MR | Zbl

[22] D. Kimber, Notes on Statistical Mechanics, Information Theory and Thermodynamics. Xerox Palo Alto Research Centre (1994).

[23] V. Krishnan, Design process improvement: sequencing and overlapping activities in product development (1993).

[24] V. Krishnan, S.D. Eppinger and D.E. Whitney, A model-based framework to overlap product development activities. Manag. Sci. 43 (1997) 437-451. | Zbl

[25] W. Li and Y. Fan, Time constraints in workflow models. In ICAM (2003).

[26] S. Luhr, S. Venkatesh, G. West and H.H. Bui, Duration abnormality detection in sequences of human activity. Dept. of Computing, Curtin University of Technology (2004).

[27] J.U. Maheswari and K. Varghese, Project scheduling using dependency structure matrix. Int. J. Project Management 23 (2005) 223-230.

[28] C. Mitchell, M. Harper and L. Jamieson, On the complexity of explicit duration HMM's. IEEE Trans. Speech Audio Proc. 3 (1995) 213-217.

[29] S.K. Mitter, Statistical inference, statistical mechanics and the relationship to information theory. Lecture Notes, MIT (2004).

[30] K.P. Murphy, Hidden semi-Markov models (HSMMs). University of California at Berkeley (2002).

[31] S. Nicoletti and F. Nicoló, A concurrent engineering decision model: management of the project activities information flows. Int. J. Prod. Econ. 54 (1998) 115-127.

[32] L.R. Rabiner, A tutorial on hidden Markov models and selected applications in speech recognition. Proc. IEEE 77 (1989) 257-286.

[33] T.A. Roemer, R. Ahmadi and R.H. Wang, Time-cost trade-offs in overlapped product development. Oper. Res. 48 (2000) 858-865.

[34] T.L. Saaty and J.M. Alexander, Thinking with Models: Mathematical Models in the Physical, Biological and Social Sciences. Pergamon-Press (1981). | MR | Zbl

[35] C.E. Shannon, A mathematical theory of communications. The Bell Systems Technical Journal 27 (1948) 379-423, 623-656. | MR | Zbl

[36] H. Shatkay and L.P. Kaelbling, Learning geometrically-constrained hidden Markov models for robot navigation: bridging the topological-geometrical gap. J. Artificial Intelligence Res. 16 (2002) 167-207. | MR | Zbl

[37] J.H. Son and M.H. Kim, Improving the performance of time-constrained workflow processing. J. Syst. Softw. 58 (2001) 211-119.

[38] A. Stolcke, Bayesian Learning of Probabilistic Language Models (1994). | MR

[39] A.A. Yassine, R.S. Sreenivas and J. Zhu, Managing the exchange of information in product development. Eur. J. Oper. Res. 184 (2008) 311-326. | Zbl

[40] A.A. Yassine, D.E. Whitney and T. Zambito, Assessment of rework probabilities for simulating product development processes using the design structure matrix. In ASME (2001).

[41] H. Zhang, W. Qiu and H. Zhang, An approach to measuring coupled tasks strength and sequencing of coupled tasks in new product development. Concurr. Eng.: Res. Appl. 14 (2006) 305-311.

[42] H. Zhao and P. Doshi, Composing nested web processes using hierarchical semi-Markov decisioxn processes. In AAAI (2006).

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