The DSS for Design Electrical and Communication System in Internal Buildings

The DSS for Design Electrical and Communication System in Internal Buildings

  IJETT-book-cover  International Journal of Engineering Trends and Technology (IJETT)          
  
© 2015 by IJETT Journal
Volume-21 Number-4
Year of Publication : 2015
Authors : Prin Boonkanit, Ratchanee Pasanpan
DOI :  10.14445/22315381/IJETT-V21P238

Citation 

Prin Boonkanit, Ratchanee Pasanpan"The DSS for Design Electrical and Communication System in Internal Buildings", International Journal of Engineering Trends and Technology (IJETT), V21(4),212-218 March 2015. ISSN:2231-5381. www.ijettjournal.org. published by seventh sense research group

Abstract

The objective of this research is to develop a Decision Support System (DSS) for design electrical and communication system in internal buildings based upon expert system concept. This method can reduce designing time and designing errors from low-experienced staff and problems from frequently revised architectures according to customer requirements. The process of the DSS development has been started from analyzing various theories which are used for designs including with necessary data for consideration of factory electrical system design comprised of the electrical lighting system, the electrical power system and the electrical communication system. The whole knowledge has later been brought to design and develop the computer program by using C# Sharp Develop linked to nanoCad and MS-Excel Programs to make the system be conveniently utilized. Results from the experiments of a pilot project state that before applying the expert system program, design activities of electrical engineers generate the average error at 3.05 points with 5.98 hours per activity; and after applying the expert system program, the error from the designs can be reduced 46.15% with only 3.97 hours per a design activity. The highlight of this DSS is that the program can support customer drawing modification and enhance learning or training for low-experienced staff. A case study, recommendations, limitations, and further research are also presented.

References

[1] G., Engin, B., Aksoyer, U., Hanay, M., Avdagic, D., Maden, D., Bozanl?, G., Ertek, “Rule-based expert systems for supporting university students,” 2nd International Conference on Information Technology and Quantitative Management, Procedia of computer science, 2014.
[2] J., M.L, Gagne, M., Andersen, L. K., Norford, “An interactive expert system for day lighting design exploration,” Building and Environment Vol. 46, pp. 2351-2364. 2011.
[3] J. V., Harrington, H., Soltan, M. Forskitt, “Framework for knowledge based support in a concurrent engineering environment,” Knowledge-Based Systems, Vol. 9, pp. 207-215. 1996.
[4] C., Hicks, T., McGovern, C.F., Earl, “Supply chain management: A strategic issue in engineer to order manufacturing,” Int. J. Production Economics, Vol. 65, pp. 179-190, 2000.
[5] P. A., Jaques, H., Seffrin, G., Rubi, F., de Morais, I. I., Bittencourt, S., Isotani, C., Ghilardi, “Rule-based expert systems to support step-by-step guidance in algebraic problem solving: The case of the tutor PAT2Math,” Expert Systems with Applications, Vol. 40, pp. 5456–5465. 2013.
[6] F.J., Kohout, Statistics for Social Scientists. Coordinated Learning System. Wiley, New York, 1974.
[7] S.H., Liao, “Expert system methodologies and applications—a decade review from 1995 to 2004,” Expert Systems with Applications, Vol. 28, pp. 93–103, 2005.
[8] T. J., Mondragón, R., Martínez-Ramírez, F., Jiménez-Fraustro, R., Orozco-Martínez, R., Cruz-Cruz, “Power Plants Simulators with an Expert System to Train and Evaluate Operators,” Proceedings of the World Congress on Engineering and Computer Science 2010, Vol II WCECS 2010, October 20-22, 2010, San Francisco, USA, 2010.
[9] A., Muhammad, A. R., Ismail, I., Memon, “A Review on Expert System and its Applications in Civil Engineering,” International Journal of Civil Engineering and Built Environment, Vol.1, No.1, pp. 24-29, 2014.
[10] C. E., Ochoa, I. G., Capeluto, “Decision methodology for the development of an expert system applied in an adaptable energy retro?t façade system for residential buildings.” Renewable Energy, Vol. 78, pp. 498-508, 2015.
[11] E.U., Olugu, K. Y., Wong, “An expert fuzzy rule-based system for closed-loop supply chain performance assessment in the automotive industry.” Expert Systems with Applications, Vol. 39, pp. 375–384. 2012.
[12] S., Rahman, O., Hazim, “Load forecasting for multiple sites:development of an expert system-based technique.” Electronic Power Systems Research, Vol. 39, pp. 161–169, 1996.
[13] SharpDevelop. The Open Source Development Environment for .NET (2014),[Online],http://www.icsharpcode.net/OpenSource/SD/Download/#SharpDevelop5x
[14] E., Turban, J. E., Aronson, Decision support systems and intelligent systems, sixth Edition, 6th ed, Hong Kong: Prentice International Hall, 2001.
[15] H., Yang, D., Xue, A, concurrent engineering-oriented design database representation model. Computer-Aided Design, Vol. 36, pp. 947–965, 2004.
[16] nanoCad. [Online] www.nanocad.com
[17] S., Sahin, M.R., Tolun, R. Hassanpour, “Hybrid expert systems: A survey of current approaches and applications.” Expert Systems with Applications, Vol. 39, pp. 4609–4617, 2012.

Keywords
Decision Support System, Expert System, Computer aided Design, Electrical System Design.