| Asset |
A1. Identify Functional Failures |
When identifying and mapping the functional failures of the equipment, it is possible to establish what are the possible parameters that indicate these failures. |
- Interpret the relevant parameters in the equipment; |
(Kumar et al., 2018Kumar, A., Shankar, R., & Thakur, L. S. (2018). A big data driven sustainable manufacturing framework for condition-based maintenance prediction. Journal of Computational Science, 27, 428-439. http://dx.doi.org/10.1016/j.jocs.2017.06.006.
http://dx.doi.org/10.1016/j.jocs.2017.06...
) |
| - Establish abnormal conditions. |
| A2. Equipment Health |
Monitoring the health status of the equipment employs sensors within the structure of the equipment (such as motors, tracks, bearings, etc.) monitoring and providing predictions about the current state. |
- Preserve equipment integrity in data acquisition; |
(Wang et al., 2017Wang, Y., Gogu, C., Binaud, N., Bes, C., Haftka, R. T., & Kim, N. H. (2017). A cost driven predictive maintenance policy for structural airframe maintenance. Chinese Journal of Aeronautics, 30(3), 1242-1257. http://dx.doi.org/10.1016/j.cja.2017.02.005.
http://dx.doi.org/10.1016/j.cja.2017.02....
) |
| - Supervise equipment performance. |
| A3. Reliability in Data Acquisition |
If acquired reliably, the information has potential value, both to create a historical database and to discover patterns and relationships between parameters. |
- Perform the monitoring of several parameters in parallel; |
(Karim et al., 2016Karim, R., Westerberg, J., Galar, D., & Kumar, U. (2016). Maintenance analytics: the new know in maintenance. IFAC-PapersOnLine, 49(28), 214-219. http://dx.doi.org/10.1016/j.ifacol.2016.11.037.
http://dx.doi.org/10.1016/j.ifacol.2016....
) |
| - Compare purchases with models and standards already specified. |
| A4. Telemetry |
In maintenance, there is a tendency for all equipment to have more embedded electronics and monitoring through the same of its main subsets. |
- Quality and properly installed sensors; |
(Furch et al., 2018Furch, J., Turo, T., Krobot, Z., & Stastny, J. (2018). Using Telemetry for Maintenance of Special Military Vehicles. In: J. Mazal (Eds.), Modelling and Simulation for Autonomous Systems (Lecture Notes in Computer Science, Vol. 10756). https://doi.org/10.1007/978-3-319-76072-8_28.
https://doi.org/10.1007/978-3-319-76072-...
) |
| - Guarantee up-to-date information in the monitoring of data. |
| Integration |
A5. Connectivity |
Wireless sensor networks (WSNs) can provide a lot of useful data and are being used more and more in the scope of maintenance. |
- Use robust network protocols; |
(Botta et al., 2016Botta, A., Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: a survey. Future Generation Computer Systems, 56, 684-700. http://dx.doi.org/10.1016/j.future.2015.09.021.
http://dx.doi.org/10.1016/j.future.2015....
) |
| - Ensure an adequate data transmission rate; |
| - Certify the reach of the required communication band. |
| A6. Security / Stability |
Even with the demand for connected elements increasing, it is necessary to ensure continuous operation. |
- Operational reliability; |
(Santos et al., 2009Santos, M. M., Resende, D., Garzedin, O., Portugal, P., & Vasques, F. (2009). Technical and economical assessment of the use of wireless gateways in industrial networks. In 35th Annual Conference of IEEE Industrial Electronics (pp, 2499–2504). Piscataway, NJ: IEEE. http://dx.doi.org/10.1109/IECON.2009.5415223.
http://dx.doi.org/10.1109/IECON.2009.541...
) |
| - Use confirmation protocols; |
| - Encrypt data transmitted by gateways. |
| A7. Flexibility |
Gateway devices require a high level of flexibility, allowing hardware to be integrated into the network. |
- Devices with updated firmware; |
Wintrich et al., 2015) |
| - Connected elements have knowledge about other elements connected to the network. |
| A8. Interoperability |
Maintenance systems must be able to communicate and exchange information. |
- Allow the ability to connect with different industrial protocols; |
(Karim et al., 2016Karim, R., Westerberg, J., Galar, D., & Kumar, U. (2016). Maintenance analytics: the new know in maintenance. IFAC-PapersOnLine, 49(28), 214-219. http://dx.doi.org/10.1016/j.ifacol.2016.11.037.
http://dx.doi.org/10.1016/j.ifacol.2016....
) |
| - Use gateways validated by networks; |
| - Use data access middleware for direct connectivity between apps and databases. |
| Communication |
A9. Security and Privacy |
With the increasing usability of technologies such as Cloud, concerns arise such as network security, suppliers and leakage of sensitive information to the company. |
- Ensure access control of devices; |
(Botta et al., 2016Botta, A., Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: a survey. Future Generation Computer Systems, 56, 684-700. http://dx.doi.org/10.1016/j.future.2015.09.021.
http://dx.doi.org/10.1016/j.future.2015....
) |
| - Properly designed access authorization policies. |
| A10. Mobility |
In the scope of maintenance, technological mobility plays an important role in making information accessible. |
- Allow connection and exchange of information on mobile devices; |
(Muller et al., 2008Muller, A., Crespo Marquez, A., & Iung, B. (2008). On the concept of e-maintenance: review and current research. Reliability Engineering & System Safety, 93(8), 1165-1187. http://dx.doi.org/10.1016/j.ress.2007.08.006.
http://dx.doi.org/10.1016/j.ress.2007.08...
) |
| - Interactivity and operability in real time. |
| A11. Data Source Heterogeneity |
Predictive maintenance requires an efficient data management system from a variety of devices. |
- Relate different types and cloud architectures; |
(Botta et al., 2016Botta, A., Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: a survey. Future Generation Computer Systems, 56, 684-700. http://dx.doi.org/10.1016/j.future.2015.09.021.
http://dx.doi.org/10.1016/j.future.2015....
) |
| - Adjust data at different levels; |
| - Allocate services and applications in different layers. |
| A12. Scalability |
Important feature in the communication system, which indicates how many active elements in the system the network can support. |
- Use protocols that allow the unique identification of elements on the network; |
(Botta et al., 2016Botta, A., Donato, W., Persico, V., & Pescapé, A. (2016). Integration of cloud computing and internet of things: a survey. Future Generation Computer Systems, 56, 684-700. http://dx.doi.org/10.1016/j.future.2015.09.021.
http://dx.doi.org/10.1016/j.future.2015....
) |
| - Limit the number of requests over the network at a time. |
| Information |
A13. Speed |
To maintain the efficiency of maintenance systems, it is necessary to ensure the speed and proactivity of the system's information flow. |
- Design architectures that balance data latency, requirements and decision cycle; |
(Laney, 2001Laney, D. (2001). Evidence of two effects in the size segregation process in dry granular media. Physical Review E, 70(5), 051307.) |
| - Check the ideal data processing speed; |
| - Use point-to-point connections between the database and the applications. |
| A14. Volume |
A network with multiple sensors (WSNs) relies heavily on having robustness to store data about maintenance. |
- Ensure data storage capacity; |
(Laney, 2001Laney, D. (2001). Evidence of two effects in the size segregation process in dry granular media. Physical Review E, 70(5), 051307.) |
| - Reduce certain analytical structures to a percentage of statistically valid sample data; |
| - Monitor data usage to identify unused information and discard it. |
| A15. Variety |
The variety refers to the range of type and data sources. Along with Speed and Volume, they are the 3Vs in a system that operates with information. |
- Establish a filter to avoid repetition of data; |
(Laney, 2001Laney, D. (2001). Evidence of two effects in the size segregation process in dry granular media. Physical Review E, 70(5), 051307.) |
| - Create a data profile to resolve inconsistencies and discover data relationships. |
| A16. Utility |
The information about the equipment should have an influence and be useful in the results of the maintenance analysis. |
- Interpret and map only the important parameters in the equipment; |
(Schmidt et al., 2017Schmidt, B., Wang, L., & Galar, D. (2017). Semantic framework for predictive maintenance in a cloud environment. Procedia CIRP, 62, 583-588. http://dx.doi.org/10.1016/j.procir.2016.06.047.
http://dx.doi.org/10.1016/j.procir.2016....
) |
| - Guarantee the quality of the recorded information; |
| - Filter the information to make it more useful and accurate. |
| A17. Data Fusion |
Merging data is a prerequisite to obtain data inference when handling a maintenance system, with multiple sensors and different data sources. |
- Preventing data overload; |
(Welz et al., 2017Welz, Z., Coble, J., Upadhyaya, B., & Hines, W. (2017). Maintenance-based prognostics of nuclear plant equipment for long-term operation. Nuclear Engineering and Technology, 49(5), 914-919. http://dx.doi.org/10.1016/j.net.2017.06.001.
http://dx.doi.org/10.1016/j.net.2017.06....
) |
| - Ability to prioritize and differentiate data; |
| - Create data models about maintenance and compare them. |
| Functional |
A18. Diagnosis |
The diagnosis has the objective of detecting the irregularity, and providing information about its origin and severity. Diagnosis is an important factor in the assertiveness of decision-making. |
- Identify deficiencies in the process; |
(Yam et al., 2001Yam, R. C. M., Tse, P. W., Li, L., & Tu, P. (2001). Intelligent predictive decision support system for condition-based maintenance. International Journal of Advanced Manufacturing Technology, 17(5), 383-391. http://dx.doi.org/10.1007/s001700170173.
http://dx.doi.org/10.1007/s001700170173...
) |
| - Create a database with a history of failures and monitoring of equipment health; |
| - Define the tasks to be performed and the time spent based on the state of the equipment. |
| A19. Intelligence |
Systems need to evolve in automatic fault detection, acquiring learning based on fault history. |
- Improve the accuracy of the algorithms that reproduce human decision-making; |
(Yokoyama, 2015Yokoyama, A. (2015). Innovative changes for maintenance of railway by using ICT-To achieve “smart Maintenance.”. Procedia CIRP, 38, 24-29. http://dx.doi.org/10.1016/j.procir.2015.07.074.
http://dx.doi.org/10.1016/j.procir.2015....
) |
| - Use hybrid intelligent systems that learn to identify and predict anomalous situations. |
| A20. Efficiency |
The maintenance system should improve compared to past maintenance histories. |
- To assimilate several parameters and indicators to strengthen the confidence of the result; |
(Baidya & Ghosh, 2015Baidya, R., & Ghosh, S. K. (2015). Model for a predictive maintenance system effectiveness using the analytical hierarchy process as analytical tool. IFAC-PapersOnLine, 48(3), 1463-1468. http://dx.doi.org/10.1016/j.ifacol.2015.06.293.
http://dx.doi.org/10.1016/j.ifacol.2015....
) |
| - Record failure prediction learning based on maintenance history; |
| - Optimize the proactivity of real-time information integration. |
| A21. Results View |
The results should be presented in a practical and detailed way to assist the decision maker. |
- Present fault characteristics, monitored parameters, possible causes and mapping of all maintenance steps; |
(Efthymiou et al., 2012Efthymiou, K., Papakostas, N., Mourtzis, D., & Chryssolouris, G. (2012). On a predictive maintenance platform for production systems. Procedia CIRP, 3(1), 221-226. http://dx.doi.org/10.1016/j.procir.2012.07.039.
http://dx.doi.org/10.1016/j.procir.2012....
) |
| - Present diagnostics in a friendly and intuitive way to those responsible. |
| Business |
A22. Availability |
Predictive maintenance should ensure greater availability of equipment, reducing machine downtime. |
- Use downtime indicators to define maintenance planning and scheduling; |
(Jantunen et al., 2011Jantunen, E., Emmanouilidis, C., Arnaiz, A., & Gilabert, E. (2011). e-Maintenance: trends, challenges and opportunities for modern industry. IFAC Proceedings Volumes, 44(1), 453-458. http://dx.doi.org/10.3182/20110828-6-IT-1002.02824.
http://dx.doi.org/10.3182/20110828-6-IT-...
) |
| - Use the information correctly to avoid uncertain machine stops. |
| A23. Resources |
The availability of the resources used needs to be made in a timely manner, otherwise efficiency will be lost and the equipment unavailability gaps will increase. |
- Have a specialist with know-how in predictive maintenance to regulate the appropriate combination of technologies; |
(Behera & Sahoo, 2016Behera, P. K., & Sahoo, B. S. (2016). Leverage of multiple predictive maintenance technologies in root cause failure analysis of critical machineries. Procedia Engineering, 144, 351-359. http://dx.doi.org/10.1016/j.proeng.2016.05.143.
http://dx.doi.org/10.1016/j.proeng.2016....
) |
| - Early availability of the necessary tools based on the predictions made; |
| - Explore mobility solutions to facilitate the performance of tasks regarding maintenance. |
| A24. Decision-making |
The assertiveness in knowing which is the best decision to face a failure and the time to do it is one of the main points in the field of predictive maintenance. |
- Provide and structure information about the problems encountered; |
(Yam et al., 2001Yam, R. C. M., Tse, P. W., Li, L., & Tu, P. (2001). Intelligent predictive decision support system for condition-based maintenance. International Journal of Advanced Manufacturing Technology, 17(5), 383-391. http://dx.doi.org/10.1007/s001700170173.
http://dx.doi.org/10.1007/s001700170173...
) |
| - Use of statistical tools to support decisions; |
| - Assist in an easy and quick way in individual decision making. |
| A25. Costs |
Today maintenance is considered a cost center for the company, being necessary to evaluate the investment of the implementation with indicators such as ROI for example. |
- Strategically assess the feasibility of implementing the necessary technologies; |
(Jantunen et al., 2011Jantunen, E., Emmanouilidis, C., Arnaiz, A., & Gilabert, E. (2011). e-Maintenance: trends, challenges and opportunities for modern industry. IFAC Proceedings Volumes, 44(1), 453-458. http://dx.doi.org/10.3182/20110828-6-IT-1002.02824.
http://dx.doi.org/10.3182/20110828-6-IT-...
) |
| - Optimization with intelligent methods of resource sharing. |
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