Paper Status Tracking

Article
Author(s)

Beata Nowogońska

Affiliation(s)

Institute of Building Engineering, University of Zielona Góra, Zielona Góra, 65-516, Poland.

ABSTRACT

All technical objects are at risk of damages during the consecutive years of their usage. Reliability of an object is an essential issue during its usage. The main problem is the strive to eliminate damage formation. Predicting the reliability of an object should allow qualitative and quantitative analysis of the possibility of occurrence of unfavorable events. The adaptation of mathematical models describing the degradation processes in mechanical and electronic devices creates opportunities to develop diagnostic standards for buildings erected in traditional technology. The article presents the methodology of prediction of reliability of a building, and the values of performance features are defined by the parameters of the Weibull distribution function.

KEYWORDS

Weibull distribution, reliability prediction, degree of technical wear

Cite this paper

References
[1] Andrews, J. D., Moss, T. R. Reliability and Risk Assessment. New York: John Wiley 1993.
[2] Bucior J. Fundamentals of reliability. Publisher Rzeszow University of Technology 1989.
[3] Cempel C., Natke H., Damage Evolution and Diagnosis in Operating Systems. In Safety Evaluation Based on Identification Approaches Related to Time-Variant and Nonlinear Structures. Germany: Vieweg+Teubner Verlag, 1993. 
[4] Cordeiro, G., Ortega, M., and Lemonte, A. The Exponential-Weibull Lifetime Distribution, Journal of Statistical Computation and Simulation 2013, 84 (12) 1-15.
[5] Corner P. 11th Advances in Reliability Technology Symposium. Elsevier Applied Science, Barking 1990.
[6] Emmons P. H., Vaysburd A. M. System concept in design and construction of durable concrete repairs. Construction and Building Materials, 1996, 10 (1), pp. 69-75.
[7] Fouchera, B., Boulliéa, J., Mesletb, B., and Dasb, D. A Review of Reliability Prediction Methods for Electronic Devices, Microelectronics Reliability 2002 42 (8): 1155-62.
[8] Frankel, E. G. Systems Reliability and Risk Analysis. Netherlands: Springer 1984.
[9] Khelassi, A., Theilliol, D., and Weber, P. 2011. Reconfigurability Analysis for Reliable Fault-Tolerant Control Design. International Journal of Applied Mathematics and Computer Science 21 (3) 2011:   431-9.
[10] Knyziak P. Analysis of the technical state for large-panel residential buildings using artificial neural networks, 17th International Conference On The Application Of Computer Science And Mathematics In Architecture And Civil Engineering, Weimar, Germany, 12 14.06.2006, p. 36.
[11] Kolowrocki, K. On Limit Reliability Functions of Large Systems. Part I. Statistical and Probabilistic Models in Reliability. Boston: Birkhäuser Boston 1999.
[12] Masters L. W., Brandt E. Systematic Methodology for Service Life Prediction of Building Materials and Components. Materials and Structures nr 22/1989.
[13] Migdalski J. Reliability engineering, ZETOM Warszawa 1992.
[14] Moan, T. Life-Cycle Assessment of Marine Civil Engineering Structures. Structure and Infrastructure Engineering: Maintenance, Management, Life-Cycle Design and Performance 2007-7: 11-32.
[15] Młynczak, M., and Nowakowski, T. Rank Reliability Assessment of the Technical Object at Early Design Stage with Limited Operational Data—A Case Study. International Journal of Automation and Computing 2006 -3 (2): 169-76.
[16] Moubray, J. RCM II—Reliability Centred Maintenance. Oxford: Industrial Press 2007.
[17] Murzewski J. Reliability engineering structures Arkady, Warszawa 1989.
[18] Nireki T. Service life design. Construction and Building Materials, Vol. 10, No 5, 1996 Elsevier Science Ltd, Printed in Great Britain 1996.
[19] Nizinski S., Pelc H. Diagnosis of mechanical equipment. Publisher of Science and Technology, Warszawa 1990.
[20] Nowak A. S., Collins K. R. Reliability of Structures, Mc Graw-Hill Int. Edition 2000.
[21] Nowogońska B. Model of the Reliability Prediction of Masonry Walls in Buildings Journal of Mechanics Engineering and Automation 4 (2014) 975-980.
[22] Runkiewicz, L. Evaluation of the Quality of Materials in Historic Buildings. Presented at the IV Conference on Scientific and Technological Sciences and PZITB on “Engineering Problems of the Old Town Historic Restoration”, Cracow 1988.
[23] Salamonowicz T. Models reliability serviceable objects of preventive service. The Journal Issues machine operation, issue 2/2001.
[24] Sotskow B. S. Reliability of components and automation equipment. Publisher of Science and Technology,Warszawa 1973.
[25] Ścislewski Z. Life Building. Kielce: Kielce University of Technology Press, Kielce 1995.
[26] Walpde R. E., Myers R. H. Probability and Statistics for Engineers and Scientists, Macmillan Publishing Company, London 1985.
[27] Winniczek W. Valuation of buildings and structures from reconstruction approach CUTOB-PZITB, Wrocław 1993.
[28] Woliński Sz, Statistics and Reliability, University of Technology Rzeszów 2001.
[29] Wysokowski A. Effect of fatigue on the durability of steel highway bridges, Archives of Civil Engineering 2002, Vol. 48, no 1, s. 59-91.
[30] Zaidi A., Bouamama B., Tagina M. Bayesian reliability models of Weibull systems: state of the art. International Journal of Applied Mathematics and Computer Science, 2012, vol. 22, no 3, pp. 585–600.

About | Terms & Conditions | Issue | Privacy | Contact us
Coryright © 2015 David Publishing Company All rights reserved, 616 Corporate Way, Suite 2-4876, Valley Cottage, NY 10989
Tel: 1-323-984-7526, 323-410-1082; Fax: 1-323-984-7374, 323-908-0457 , www.davidpublisher.com, Email: order@davidpublishing.com