Increasing Profitability Supported by Innovative Methods and Designing Monitoring Software in Condition-Based Maintenance: A Case Study
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.
[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.
[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.
@article{"International Journal of Mechanical, Industrial and Aerospace Sciences:59102", author = "Nasrin Farajiparvar", title = "Increasing Profitability Supported by Innovative Methods and Designing Monitoring Software in Condition-Based Maintenance: A Case Study", 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.", volume = "6", number = "11", pages = "2480-9", }
