Cutting tool wear degrades the product quality in manufacturing processes. Hence, real-time online estimation of is important for suggesting a replacement before limit reached, order to protect workpiece and CNC machine from damage breakdown. In this study, using both statistical features wavelet extracted sensor signals, an adaptive evolutionary extreme learning (ELM) paradigm developed high-speed milling process. proposed method, discrete differential evolution (DE) algorithm used select...

Lithium-ion battery is a core component of many systems such as satellite, spacecraft, and electric vehicles its failure can lead to reduced capability, downtime, even catastrophic breakdowns. Remaining useful life (RUL) prediction lithium-ion batteries before the future event extremely crucial for proactive maintenance/safety actions. This study proposes hybrid prognostic approach that predict RUL degraded using physical laws data-driven modeling simultaneously. In this approach, relevant...

Tool condition monitoring can be employed to ensure safe and full utilization of the cutting tool. Hence, remaining useful life (RUL) prediction a tool is an important issue for effective high-speed milling process-monitoring system. However, it difficult establish mechanism model decreasing process owing different wear rates in various stages This study proposes three-stage Wiener-process-based degradation estimation prediction. classification RUL are jointly addressed this work order take...

This research work embellishes a cost and loss model with Taguchi's function to incorporate the avoidable surplus quality losses due failure detect out-of-control state for economic statistical optimisation design of S control charts. The considered as multi-objective decision-making problem is carried out based on adequate knowledge related process shifts, which extracted from field operation conventional An improved crowding distance fuzzy particle swarm (CD-FMOPSO) developed solve such in...

Unnatural patterns exhibited on process mean and variance control charts can be associated separately with different assignable causes. Quick accurate knowledge of the type chart (CCPs), either because or variance, greatly facilitate identification Over past few decades, however, CCPs are seldom studied simultaneously in statistical literature. This study proposes a hybrid learning-based model for simultaneous monitoring CCPs. In this model, self-organization map neural network-based...

The application of Internet Things technologies has led to a data-rich manufacturing environment by connecting objects as collaborative community. However, advanced analytics approach is comparatively inadequate for work-in-process (WIP) trajectory data. On the other hand, although topic mining frequent patterns raised great deal attention, it mainly focuses on fields vehicle traffic management and users' behaviours. When applied in shop floor, extracted knowledge physical lacks...

The prediction of regenerative chatter stability has long been recognized as an important issue concern in the field machining community because it limits metal removal rate below machine’s capacity and hence reduces productivity machine. Various full-discretization methods have designed for predicting stability. main problem such is that they can predict but do not efficiently determine lobe diagrams (SLDs). Using third-order Newton interpolation Hermite techniques, this study proposes a...

The rolling element bearing is a core component of many systems such as aircraft, train, steamboat, and machine tool, their failure can lead to reduced capability, downtime, even catastrophic breakdowns. Due misoperation, manufacturing deficiencies, or the lack monitoring maintenance, it often found be most unreliable within these systems. Therefore, effective efficient fault diagnosis bearings has an important role in ensuring continued safe reliable operation host This study presents trace...

A novel particle swarm optimization algorithm for multi-objective (MOO) based on fuzzy velocity updating strategy is developed and implemented in this paper. The proposed incorporates strategy, which can characterize to some extent the uncertainty true optimality of global best position, into (PSO) so as avoid premature convergence maintain diversity. In addition, a crowding distance computation operator promoting solution diversity an efficient mutation searching feasible non-dominated...

Abstract Stability prediction of milling is great significance as the regenerative chatter can reduce machining quality and limit efficiency productivity. The stability lobe diagrams (SLDs) are most popular used approach, which determined by solving delay-differential equations (DDEs) describing dynamic system. In this study, a precise efficient updated third-order full-discretization approach (PE3rdFDM) considering analytical solution free vibration proposed to determine SLDs. each time...