(Special) Reliability Engineering Augmented with PHM
Chair: Dr. Jong Won PARK (Korea Institute of Machinery and Materials)
What Are the Effects of the Reliability Model Uncertainties in the Maintenance Decisions? Prof. Bruno CASTANIER, Fabrice GUERIN and Laurent SAINTIS (ISTIA/University of Angers)
While the risk due to the quality and quantity of the available data is one of the major concerns in the product design and qualification processes, this issue seems not to be tackled in the operational phases and especially for the optimization of maintenance policies. Indeed, the vast majority of the works proposed in the literature concentrates on the definition of a maintenance rule for the maximization of a long-term economic profitability by assuming well-defined and stationary reliability or degradation models. However, the convergence to these stationary states can be really slow and strongly related to the knowledge level of the failure modes and therefore to the data collected during its operation. In order to reduce this uncertainty, it is necessary to integrate some of knowledge acquired during the various product qualification and endurance tests. This remains, from our point of view, one of the major areas of improvement in industrial practices, especially for the
development of the condition-based maintenance approaches.
The context of this work is the definition of optimization criteria which embrace the uncertainty on the reliability models and, in a longer term, to strengthen the relationships between the product design and qualification processes to the operating and maintenance phases. The focus of this paper is to highlight, based on numerical examples, the impact of the level of the available data on the efficiency of the maintenance decision, especially in condition-based maintenance, and, subsequently, to discuss on possible extensions in the maintenance decision criteria.
Framework for a Uniform Description of Prognostics and Health Management Mr. Mark HENSS, Peter ZEILER and Bernd BERTSCHE (University of Stuttgart - Institute of Machine Components, Esslingen University of Applied Sciences)
The successful application of Prognostics and Health Management (PHM) systems increase world-wide steadily due to an increase of smart products on the market. Today PHM systems are developed and applied in different engineering disciplines using different models and methods. The diversity regarding models, methods and types of products lead to highly complex systems. To handle the complexity in an efficient way there is a need for a framework of PHM systems.
This paper describes the mathematical framework of PHM based on a generic model and a clear formalization (notation and semantic). The model includes modeling, diagnostics, prognostics and optimization. By the kind of application (e.g. the used lifetime method) the characteristics of the model are defined. Lifetime methods to estimate the Remaining Useful Life (RUL) are separated from the models to make the framework manageable for all disciplines. Combined with probability mathematics the uncertainties in PHM systems (model, prognostics, RUL etc.) are shown.
On the one hand, a common notation, semantic and a clear framework is necessary to manage highly complex systems. On the other hand, the cost and benefit of a PHM system are connected to the uncertainties. Both points are presented in this paper as the base to choose the right PHM system design.
Feasibility Study on Image-based Faulty Nozzle Detection Method for Digital Textile Printing Dr. Dong-Cheon BAEK (Korea Institute of Machinery & Materials)
In recent years, as the output speed of the digital textile printing(DTP) equipment has been increased, there is a high risk of failure due to the absence of the operator. To reduce the downtime and increase the operational efficiency, it is necessary to detect the defective nozzle and control the DTP head automatically. In this study, we developed an algorithm that identifies defective nozzle positions by acquiring images of printed fabric in real time.When we started printing on the fabric, we used a method of finding a clogged nozzle by comparing the designed layout with the head design information.
A Study on Development of Reliability Assessment Method for Industrial Drone Dr. Jong Won PARK, Jin Hee LEE and Byung-Oh CHOI (Korea Institute of Machinery and Materials)
In the past, drones have been developed for military use. Recently, however, the use of drones in industrial and civilian markets has been spreading rapidly because of their potential for various applications. The main application areas of industrial drones are aerial photography, logistics transportation, lifesaving, policing, wildfire monitoring and spraying agricultural pesticide. The reliability assessment and performance test methods of drones are not systematically established against such a rapidly growing market situation until these days. Therefore, in this study, we developed reliability assessment methods and equipments that can evaluate reliability of drone by performance test, environmental test, safety test, life test method, which can be used to ensure safety of individual users and reliability of industrial drones. In the development of the reliability assessment method for industrial drones, we tried to verify the reliability and to show the acceptable minimum limit required by reliability as the test result. Furthermore, it is expected that we possibly gather the reliability change of the flight performance and the durability through the comprehensive performance test and life test via applying the usage history and load in the laboratory. The developed methods were set up reflecting international standards, user requirements and field operating conditions. Since the field failure data of industrial drone is rare in the manufacturing companies or research institutes, it is necessary to obtain about 10,000 hours of the actual usage history and the failure data for the future in order to correct or supplement the reliability method proposed in this study.