Smart Materials–Enabled Sensing and Control Framework for Condition-Based Maintenance in Cyber-Physical Production Systems

Abstract

In smart manufacturing environments, Cyber-Physical Production Systems (CPPS) provide increased automation, energy efficiency, and operational reliability. With current maintenance approaches based on time and reaction, they tend to lead to unplanned downtimes, high energy consumption, and higher costs throughout the lifecycle. Reports document that 30–35% of equipment failures are the result of material fatigue that goes undetected. Microstructural degradation can lead to a loss of up to 25% of productivity. This paper presents the CPPS framework to address these issues. This framework presents a new approach to smart materials and how they can work to enable the Cyber-Physical framework. Integrating multifunctional sensing materials is the goal. This paper aims to work towards an integrated framework of smart materials for condition-based maintenance (CBM) that combines multifunctional sensing materials with intelligent cyber-physical systems. The framework uses smart materials to integrate components that enable real-time strain, vibration, temperature monitoring, and the structural health of the component. This data is used to develop a real-time monitoring framework of the Structural Health Monitoring (SHM) system that is used to document any real-time changes and to document any changes to the presumed state. This data can provide a real-time assessment of the system and provide metrics to define the remaining useful life (RUL) of the system. This data is processed within an Industrial Internet of Things (IIoT) system and subjected to edge analytics and machine learning-based data analytics, which can develop a system to predict control measures. This system provides the ability to schedule maintenance and optimize machine use with the purpose of minimizing energy consumption and reducing the time the system is operational. This framework provides a CPPS testbed that is integrated with automated machining and transfer systems to validate the systems. Periodic maintenance strategies have shown that you can save maintenance costs by 28% and improve equipment availability by 31%, and reduce energy costs by 18%. Also, there is up to 42% reduction in the failure of equipment, and an astonishing 94.6% accurate prediction of equipment failure by using smart sensors. This means that smart sensors are reliable as predicted. Fewer resources are used by the framework, and so are energy costs. The sustainable framework, along with the smart grid technologies, offers the industry the means for the development of next-generation maintenance that can provide self-aware, flexible, and energy-efficient systems. This is also applicable to Industry 5.0.