Predictive Engineering in Structural Application

The wide variety of fiber reinforced composites are used in structural applications like in construction beams, columns; bridges, storage tanks, pipe lines and pressure vessels and also in other corrosion-resistant equipments. They find their extensive usage in industries, civil constructions, automotives, naval and marine applications with crucial differences in engineering loading conditions, operating conditions and environment. Although most of the fiber reinforced composites proclaims the advantages of high specific strength at low weight and greater stiffness with promising durability, due to the instantaneous undesirable load conditions, harsh handling or operating conditions that is when subjected to conditions beyond its working capability and change in environmental conditions, test the endurance to required performance and durability of the material. The well-known fact is that structural maintenance cost is a major expense in case of any industries or in Nation building process. Conventionally, the structural maintenance is consciously regulated on preplanned fixed schedules to ensure reliability. Most scheduled maintenance is designed to be very frequent to achieve a desirable level of safety against malfunction or failure. Predictive maintenance monitors the performance and condition of equipment during normal operation to reduce the likelihood of failures. The Predictive maintenance aims at low maintenance frequency by reducing the Reactive Maintenance without incurring much cost and time in Preventive Maintenance. With the application of sensor technology, advanced software tools for modeling, integrated simulation capabilities and data analytics, it is possible to sense the symptoms and predict the occurrence of structural dysfunctionality. When there is automatic and continuous monitoring to sense or foresight the structural damage, this would enable to plan for maintenance activities in accordance with the predicted safety state of the structures rather than following traditional fixed schedule maintenance. When the collected predictive database is coupled with the maintenance decision-making, the Predictive Engineering is evolved. This requires the development of software model of the structure that have precisely the same behavior of the actual structural product. When it comes to synthetic, natural and hybrid fiber reinforced composites they behave differently with respect to structural, thermal, and fatigue properties. So they require dedicated modeling. The developed predictive digital model should remain synchronies in accordance with the entire product life cycle of real product. Predictive Engineering Analytics is a design and product development approach that uses computer integrated models, new software tools to let the simulation play active role in product design stage and predict the performance under nominal working conditions and also identify undesirable operating parameters and conditions that eventually leads to failure. With respect to the structural applications, from very early stage of design cycle itself, the Predictive Engineering Analytics predicts the behavior of the structural materials for all their functional requirements and changes in their physical and performance aspect on long run. This incorporates predictive functionalities into the system models, simulate their operations in system generated working conditions and the result information are fed back to design of structural elements. At the very early stage of product development cycle, the system modeling and simulation for testing enact a real time evaluation on the composite behavior in its application point. This type of system-based product development works towards reducing physical test, inspection and repair. The structural materials, monitoring machines and equipments are when connected by smart technologies, can also be accessed via cloud to predict the location and time of failures. This provokes maintenance actions thereby avoiding interruption in industrial process i.e. unnecessary downtime or even fatal accidents. The predictive Engineering has moved to an era where the material of the structure or product can remember the operating conditions and behavior of its operator, so that it can presume the next level of activities like prediction of failure and subsequent maintenance actions. The Predictive Maintenance is the most promising maintenance strategy that has proficiency to widen its scope as Predictive Engineering with more digital sophistications so as to develop materials for reliable structural applications.