Due to the artificial division of a machine performance state and unpredictable external working conditions, transition strength multistate machines (that is, their fuzzy characteristic) cannot be accurately identified. Moreover, existing research on reliability evaluation systems does not consider operating mechanism manufacturing system. Therefore, this article proposes mission method for based an extended stochastic flow network (ESFN). First, from relationship between production task...

During the abnormal operations before breakdown of a multistate manufacturing system, product quality loss could systematically characterise affected economic cost in advance. However, few studies have considering valuable data, thus, novel risk-oriented optimisation approach integrated maintenance is proposed work-in-process (WIP) obtained from system. First, functional risks systems are expounded and classified by detectable deviations potential defects finished based on machine...

The actual health state of a system is difficult to measure in online applications. Hence, features extracted from the sensor data are usually fused as composite index (HI) represent status. If HI shows explicit increasing or decreasing trend, prognostic methods applied extrapolate future degradation and predict remaining useful life (RUL). However, practical requirements prognostics for construction often not considered. Thus, advanced may capture fault progression well, which would lead...

Degradation modeling and prognostics serve as the basis for system health management. Recently, various sensors provide plentiful monitoring data that can reflect status. A multitude of feature fusion techniques based on multisensor have been proposed to generate a composite index (HI) prognostics, which represent underlying degradation mechanism. Most existing methods used linear models neglected practical requirements HI construction, are insufficient reveal nonlinear relations among...

This paper develops an optimal replacement policy V* for a multi-state manufacturing system. The system would be repaired imperfectly once its performance cannot meet the production demand, and replaced when demand is not met V*-th time. Due to imprecise state assignments unpredictable external working conditions, transition intensity of machine accurately identified then inevitably lead epistemic uncertainty. In addition, economic dependence resource that prevailed in should considered....

Remaining useful life (RUL) Prediction is crucial for the predictive maintenance of industrial manufacturing systems. The challenges encountered in prediction RUL include identifying a pertinent health indicator (HI), effectively modeling t he degradation pattern across diverse features, and selecting optimal methodologies to enhance accuracy. This paper establishes construction HI using PCA, utilizing data from aircraft engines. Bi-LSTM with optimization algorithm investigated evaluation...

Bobbin dyeing is a low-liquor-ratio technique that consumes less water and generates wastewater. However, the bobbin carried out in closed kettle body, many interfering factors affect rate uptake concentration cannot be observed controlled real time. Dyeing digitization can used to achieve real-time monitoring of amount on yarn bobbin, an important means obtaining information dyeing. To digital dyeing, this paper, mathematical model for mass transfer based principles established first,...

ABSTRACT Predicting the remaining useful life (RUL) of mechanical equipment is one key tasks prognostics and health management (PHM). Modern often operates under complex operating conditions failure modes, making it difficult to extract features, construct indicators, predict life. This paper presents a novel method for RUL prediction. The proposed extracts vibration signal data from employs ensemble empirical mode decomposition (EEMD) reconstruction denoise signals. Sequential Forward...

Selective maintenance is widely used as a reliability-centered strategy due to the limited resources. However, existing selective studies only consider basic reliability, which cannot systematically describe operating mechanism of multistate system, thereby resulting in inability obtain an optimal strategy. Moreover, intelligent manufacturing systems are highly representative typical industrial systems. In this study, mission reliability-oriented optimization model for that considers...

The rapid development of complexity and intelligence in manufacturing systems leads to an increase potential operational risks therefore requires a more comprehensive system-level health diagnostics approach. Based on the massive multi-source data collected by smart sensors, this paper proposes mission reliability-driven system state evaluation method. Characteristic attributes affecting reliability are monitored analyzed based different sensor groups, including performance equipment,...

Previous studies of reliability centered maintenance (RCM) rarely consider the quality for operation condition monitoring manufacturing system. Therefore, a quality-oriented approach multistate system with aid mission is proposed. First, connotations and are expounded on basis operational mechanism. Second, stochastic flow network (QSFN) model established, novel presented. Third, reliability–centered framework systems proposed, optimal integrated strategy obtained by minimizing total cost....

Predictive health analysis and diagnostics are essential functional elements of “Smart Manufacturing,” but existing studies mostly limited to discrete manufacturing equipment without a holistic on the entire system state. In consideration enhancement risk control in production quality management advocated ISO 9001:2015, modeling monitoring during operation core aspects bottlenecks for achieving prognostics. Therefore, novel operational approach systems is proposed by fusing data quantify...