Failure Pattern Recognition and Extended Tactical Spare Parts Supply Chain Planning
Final Report Abstract
The project was part of the international research project "Integrating Intelligent Maintenance Systems and Spare Parts Supply Chains" (I2MS2C) in the Brazilian-German Collaborative Research Initiative in Manufacturing (BRAGECRIM) framework funded by the German Research Foundation (DFG) and the Brazilian Research Agency CAPES. The project has been conducted jointly with our three Brazilian project partners, the Universidade Federal do Rio Grande do Sul (UFRGS), the Universidade Federal de Santa Catarina (UFSC) as well the Universidade Federal do Rio Grande (FURG). The main objective of the overall project was to improve the management of supply chains for spare parts and maintenance services. Especially, managing service operations for complex technical systems should be made more effective and efficient. As machine failures and breakdowns happen very suddenly, corresponding demand for spare parts and maintenance services is intermittent and therefore very difficult to forecast. In order to achieve forecasts that are more reliable and perform maintenance activities before machines break down, the project integrates current machine condition information. Embedded sensors of intelligent maintenance systems (IMS) are used to monitor the machines and their components. The project team developed an integrated concept that includes the provided sensor information (vibrations, temperature etc.) into advanced forecasting methods and uses them further to plan and coordinate the processes and activities in a spare part supply chain. In general, maintenance operations of complex technical systems benefit from the integrated concept of improved planning by synchronizing spare parts and maintenance service demands with spare parts availability and service capacities. Besides many others, an interesting potential application of the project results could be demonstrated with the maintenance of electric valves in pipeline networks. The integrated project concept proved to support the monitoring of the valves as well as the early planning and execution of corresponding maintenance activities before failures occur. The project has been conducted in two consecutive phases. In the first project phase, the technical focus (Brazilian project part) has been to improve IMS capabilities to achieve forecasts that are more reliable forthe remaining useful life of a machine. The German project part tackled corresponding spare parts management activities. Based on the newly available IMS condition monitoring information, reference business processes and a planning method were developed for the integrated planning of spare parts inventory and distribution as well as maintenance services along a spare parts supply chain. Consequently, the so-called Framework for Intelligent Supply Chain Collaboration (FRISCO) has been developed to enable the design and evaluation of planning concepts for the companies within supply chains. Moreover, an ontology was created for the information exchange between the IMS and the information systems planning spare parts supply chains. In the second project phase, in the technical area of IMS two further advanced technologies have been applied: distributed IMS and accelerated lifetime simulation. Distributed IMS enable and utilize the sharing of knowledge and failure information across similar machines. Accelerated lifetime simulation accelerates the degradation behavior of machines during testing to generate failure information. The spare parts management area applied data analytics techniques to improve the quality of failure and demand forecasting methods. Furthermore, the integrated and collaborative planning methods were extended as well as linked to the forecasting methods to utilize their results for planning. In addition, an integration layer was developed to connect the different applied information systems for planning and controlling a spare parts supply chain as well as IMS.
Publications
- (2014) Conceptual Approach for Integrating Condition Monitoring Information and Spare Parts Forecasting Methods. In: Production and Manufacturing Research: An Open Access Journal 2(1): 725-737
Hellingrath B, Cordes A
(See online at https://doi.org/10.1080/21693277.2014.943431) - (2015) An Approach for Assessing the Applicability of Collaborative Planning Concepts. In: Hawaii International Conference on System Sciences (HICSS), Kauai, Hawaii, USA
Küppers P, Saalmann P, Hellingrath B
(See online at https://dx.doi.org/10.1109/HICSS.2015.129) - (2015) Coordination in heterarchical supply chains - A Framework for the Design and Evaluation of Collaborative Planning Concepts. Logos-Verlag, Berlin
Küppers, P
- (2015) Development of a Reference Model for Spare Parts Logistics. In: Dethloff J., Haasis H.-D., Köpfer H., Kotzab H.. Schönberger J. (eds.): Logistics Management. Lecture Notes in Logistics. Springer, Cham, Switzerland
Cordes A. Hellingrath B
(See online at https://dx.doi.org/10.1007/978-3-319-13177-1_13) - (2015) On the Integration of Intelligent Maintenance and Spare Parts Supply Chain Management. In: Proceedings of the 15th IFAC Symposium on Information Control Problems in Manufacturing, Ottawa, Canada
Hellingrath B, Pereira C, Espmdola D, Frazzon E, Cordes A, Saalmann P, Zuccolotto M
(See online at https://dx.doi.org/10.1016/j.ifacol.2015.06.211) - (2016) An Overview of Useful Data and Analyzing Techniques for Improved Multivariate Diagnostics and Prognostics in Condition-Based Maintenance. In: Annual Conference of the Prognostics and Health Management Society 2016, Denver, USA
Wagner C, Saalmann P, Hellingrath B
- (2016). Master Model for Integrating Inventory, Transport and Service Personnel Capacity Planning. In Proceedings of the IFAC Symposium on Telematics Applications, Porto Alegre, Brazil
Cordes A, Hellingrath B
(See online at https://doi.org/10.1016/j.ifacol.2016.11.165) - (2017) Prozesse, Prognose und Planung in Ersatzteil-Supply-Chains für die zustandsorientierte Instandhaltung - Entwicklung eines Referenzprozessmodells, eines Nachfrageprognoseverfahrens und eines integrierten Planungsmodells am Beispiel der Maschinenbauindustrie, Dissertation, Fakultät für Wirtschaftswissenschaften, Westfälische Wilhelms-Universität Münster
Cordes A
