Increasing Profitability Supported by Innovative Methods and Designing Monitoring Software in Condition-Based Maintenance: A Case Study
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 32797
Increasing Profitability Supported by Innovative Methods and Designing Monitoring Software in Condition-Based Maintenance: A Case Study

Authors: Nasrin Farajiparvar

Abstract:

In the present article, a new method has been developed to enhance the application of equipment monitoring, which in turn results in improving condition-based maintenance economic impact in an automobile parts manufacturing factory. This study also describes how an effective software with a simple database can be utilized to achieve cost-effective improvements in maintenance performance. The most important results of this project are indicated here: 1. 63% reduction in direct and indirect maintenance costs. 2. Creating a proper database to analyse failures. 3. Creating a method to control system performance and develop it to similar systems. 4. Designing a software to analyse database and consequently create technical knowledge to face unusual condition of the system. Moreover, the results of this study have shown that the concept and philosophy of maintenance has not been understood in most Iranian industries. Thus, more investment is strongly required to improve maintenance conditions.

Keywords: Condition-based maintenance, Economic savings, Iran industries, Machine life prediction software.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1074489

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1529

References:


[1] Al-Najjar, B. (2000a). Accuracy, eefectiveness and improvement of vibration-based maintenance in paper mills: Case studies. Journal of Sound and Vibration 229 (2), 389-410.
[2] Al-Najjar, B. (2000b). Accuracy, effectiveness and improvement of vibration-based maintenance in paper mills: A case study. Journal of Sound and Vibration 229 (2), 389-410.
[3] Al-Najjar, B. (1998). Improved effectiveness of vibration monitoring of rolling element bearings in paper mills. Journal of Engineering Tribology,ImechE. Proceedings of the Institution of Mechanical Engineers 212 (J), 111-120.
[4] Al-Najjar, B. (2007). The lack of maintenance and not maintenance which costs: a model to describe and quantify the impact of vibrationbased mantenence on company's business. International Journal of Production Economics 107, 260-273.
[5] Al-Najjar, B., Alsyouf, I. (2004). Enhancing a company's profitability and competitiveness using integrated vibration-based maintenance: A case study. European Journal of Operational Research 157 (3), 643-658.
[6] Al-Najjar,B., Alsyouf, I.,Salgado, E., Khoshaba, S., Faaborg, K. (2001). Economic important of maintenance-planning when using vibrationbased maintenance policy. Vaxjo University, LCC project report.
[7] Alsyouf, I. (2009). Maintenance practices in Swedish industries: Survey result. International Journal of Production Economics 121, 212-223.
[8] Alsyouf, I. (2007). The role of maintenance in improving companies' productivity and profitability. International Journal of Production economics 105(1), 70-78.
[9] Anon. (1998). Integrated plant-wide condition monitoring and process data system. Insight/non-destructive testing and condition monitoring. Journal of the British Institute 40 (12), 809.
[10] Bevilacqua, M., Braglia, M. (2000). The analytical hierarchy process applied to maintenance strategy selection. Reliability Engineering and System Safety 70, 71-83.
[11] Bob, V. (2007). Experts lay out a case for ROI of maintenance. Plant Engineering 61 (8), 12.
[12] Dekker, R. (1996). Applications of maintenance optimisation models: A review and analysis. Reliability Engineering and System Safety 51, 229- 240.
[13] Eti, M.C., Ogaji, S.O.T., Probert, S.D. (2006). Development and implementation of preventive-maintenance practices in Nigerian industries. Applied Energy 8, 1163-1179.
[14] Grall, A., Berenguer, C., Dieulle, L. (2002). A condition-based maintenance policy for stochastically deteriorating systems. Reliability Engineering and System Safety 76, 167-180.
[15] Holmberg, K. (2001). Competitive reliability 1996-2000. . Technology Programme Report 5/2001, Final Report, National Technology Agency, Helsinki.
[16] Jardine, AKS., Lin, DM., Banjevic, D. (2006). A review on machinery diagnostics and prognostics implementing condition-based maintenance. Mechanical Systems and Signal Processing 20 (7), 1483-1510.
[17] Kaiser, KA., Gebraeel, NZ. (2009). Predictive maintenance management using sensor-based degradation models. IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans 39 (4), 840-849.
[18] Klingenberg, W., de Boer, T.W. (2008). Condition-based maintenance in punching/blanking of sheet metal. International Journal of Machine Tools & Manufacture 48, 589-598.
[19] Luce, S. (1999). Choice criteria in conditional preventive maintenance: short paper. Mechnical Systems and Signal processing 13 (1), 163-168.
[20] Macintyre, J., Smith, P., Harris, T., & Brason. (1994). Neural network for intelligent machinery diagnostics. Engineering System Design and Analysis 64, 507-512.
[21] Mann, L., Saxena, A., Knapp, G.M., (1995). Statistical-based or condition-based preventive maintenance? Journal of Quality in Maintenance Engineering 1 (1), 46-59.
[22] Mckone, K., Weiss, E. (1998). TPM: Planned and autonomous maintenance: Bridging the gap between practice and research. Production and Operations Management 7 (4), 335-351.
[23] Moubray, J. (1991). Reliability Centred Maintenance. Butterworth Heinemann, Oxford, UK.
[24] Pintelon, L.M., Gelders, L.F. (1992). Maintenance management decision making. European Journal of Operational Research 58, 301-317.
[25] Riis, J., Luxhoj, J., Thorsteneinsson, U. (1997). A situational maintenance model. International Journal of Quality and Reliability Management 14 (4), 349-366.
[26] Rohani, A., Abbaspour-Fard, M.H., Abdolahpour, S. (2011). Prediction of tractor repair and maintenance costs using Artificial Neural Network. Expert Systems with Applications 38, 8999-9007.
[27] Sherwin, D.J. (2000). A review of overall models for maintenance management. Journal of Quality in Maintenance Engineering 6 (3), 138- 164.
[28] Swanson, L. (2003). An information-processing model of maintenance management. International Journal of Production Economics 83 (1), 45- 64.
[29] Swanson, L. (2001). Linking maintenance strategies to performance. International Journal of Production Economics 70, 237-244.
[30] Tian, Z., Jin T., Wu, B., Ding, F. (2011). Condition based maintenance optimization for wind power generation systems under continuous monitoring. Renewable Energy 36, 1502-1509.
[31] Tian, Z., Liao, H. (2011). Condition based maintenance optimization for multi-component systems using proportional hazards model. Reliability Engineering and System Safety 96, 581-589.
[32] Tsang AHC. (1995). Condition-based maintenance: tools and decision making. Journal of Quality in Maintenance Engineering 1(3), 3-17.
[33] Van Wyk, E.M.P., & Hoffman,A.J. (2003). Detecting long-term trends in turbo-generator stator end-winding vibrations through neural network modelling. Journal of Sound and Vibration 253 (3), 529-544.
[34] Vineyard, M., Amoako-Gyampah, K., Meredith, J. (2000). An evaluation of maintenance policies for flexible manufacturing systems: a case study. International Journal of Operations and Production Management 20 (4), 409-426.
[35] Waeyenbergh, G., Pintelon, L. (2002). A framework for maintenance concept development. International Journal of Production Economics 77, 299-313.
[36] Wang, W., Hussin, B., Jefferis, T. (2012). A case study of condition based maintenance modeling based upon the oil analysis data of marine diesel engines using stochastic filtering. International Journal of Production Economics 136, 84-92.
[37] Williams, J., Davies, A., Drake, P. (1994). Condition-Based Maintenance and Machine Diagnostics. Chapman & Hall, London.