Di Zhou

• Doctor of Engineering
• PhD Student at Northeastern University

As automated labeling on products in intelligent manufacturing grows in importance, detecting anomalies in the end-effectors used for industrial robots labeling is essential for maintaining production line stability and efficiency. Considering the distinct characteristics of specific movements in the labeling process, different motions, such as mov...

Remaining useful life (RUL) prediction based on health information is of vital significance in the prognostics & health management(PHM). In recent years, accuracy RUL prediction by data-driven methods is the hotpot. However, most data-driven RUL prediction methods lack the ability to capture spatial-temporal features from input monitoring data, whi...

Due to the production process for continuous process manufacturing system (CPMS) cannot be stopped, the “opportunities” for maintenance can only occur within the specified time intervals. To improve the completion rate of production process, the focus of opportunistic maintenance for CPMS is whether the maintenance is to be performed at known time....

Degradation modeling and prognostics serve as the basis for system health management. Recently, various sensors provide plentiful monitoring data that can reflect the system status. A multitude of feature fusion techniques based on multisensor data have been proposed to generate a composite health index (HI) for prognostics, which can represent the...

This paper develops an optimal replacement policy V* for a multi-state manufacturing system. The manufacturing system would be repaired imperfectly once its performance cannot meet the production demand, and would be replaced when the production demand is not met for the V*-th time. Due to imprecise state assignments and unpredictable external work...

Mechanical equipment is always influenced by environmental factors or random excitations, such as random collision, rock fall, sea wave and wind force. It is significant to analyze the statistical information of the system performance for the operation security and kinematic accuracy. Considering time-varying stiffness and nonlinearity, a stochasti...

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 a composite health index (HI) to represent the system status. If the HI shows explicit increasing or decreasing trend, prognostic methods are applied to extrapolate the future degradation and predic...

Degradation paths of the products exhibiting two-phase patterns are commonly seen in practice due to the changeable internal mechanisms and external environments. In this paper, we propose a two-phase Gaussian process (TPGP) degradation model with a change-point, which comprises the Wiener process-based change-point models as special cases, to desc...

As multi-state reliability models and the dependency theory can characterize the polymorphism of manufacturing systems during degradation, they have been discussed in depth over the past few decades. However, most studies on the dependence of manufacturing systems ignored the dynamic characteristics (the production rhythm). Therefore, a reliability...

The explicit polynomial function can replace the actual limit state function for failure probability. In this study, the fractional order is introduced to an extended family of polynomial functions to guarantee a smooth relationship between the sample data and polynomial expression. The fractional polynomial method is proposed to establish the func...

Machine utilization and production efficiency of manufacturing systems can be effectively improved through reasonable production scheduling. Traditionally, production scheduling and maintenance planning are considered as two independent issues, but it may lead to a suboptimal solution that is unable to maximize the productivity of the manufacturing...

Quality accidents (QAs) of high frequencies in various fields have caused large economic and reputational losses to manufacturers, and identification of the root causes of vicious QAs is a top priority and a major challenge for manufacturers. Especially in the era of big data, the large number of data could be collected from the product life cycle...

The quality and reliability level of the produced product is the key performance and health state indicator of the running manufacturing system. Hence, the workpiece quality centered operational data originated from the production process should be considered to predict the health state of the intelligent manufacturing system. However, studies of s...

Dynamic reliability analysis must consider both dynamic performance and parametric randomness to evaluate system safety in operation. The saddle-point approximation method is utilized to establish the dynamic probability distribution for known or unknown types of random variables. The cumulative distribution function is used to establish the approx...

Assembling variations caused by assembling system reliability degradation are the root causes of poor-assembled product reliability, and the reliability loss is the barometer of assembling quality risks. However, few studies have integrated reliability loss with assembling quality risk analysis. Therefore, a modeling approach of assembling quality...

During the abnormal operations before breakdown of a multistate manufacturing system, product quality loss could systematically characterise the affected economic cost in advance. However, few studies have considering the valuable quality loss data, thus, a novel risk-oriented optimisation approach of integrated maintenance is proposed considering...

Due to the artificial division of a machine performance state and unpredictable external working conditions, the performance and state transition strength of multistate machines (that is, their fuzzy multistate characteristic) cannot be accurately identified. Moreover, existing research on the reliability evaluation of multistate systems does not c...

Predictive health analysis and diagnostics are essential functional elements of “Smart Manufacturing,” but existing studies are mostly limited to discrete manufacturing equipment without a holistic analysis on the entire system health state. In consideration of the enhancement of risk control in production quality management advocated in ISO 9001:2...

Selective maintenance is widely used as a reliability-centered maintenance strategy due to the limited maintenance resources. However, existing selective maintenance studies only consider basic reliability, which cannot systematically describe the operating mechanism of a multistate system, thereby resulting in the inability to obtain an optimal ma...

Infant failures are the natural enemy of customer satisfaction of electronic product. The change point is a precondition to optimize the burn-in time, warranty period, and root causes in production reliability assurance. However, the method for modeling and detecting the change point is unavailable due to the deficient research on the mechanism of...

In high-quality manufacturing processes, the yield is no more the only issue, and the quality control approach that also considers the product’s actual performance gradually becomes the focus. Reliability is a critical dimension of quality, and its degradation in usage is always determined by the manufacturing quality. To mitigate the degradation o...

Assembly quality is the barometer of assembly system health, and a healthy assembly system is an important physical guarantee for producing reliable products. Therefore, for ensuring the high reliability of products, the operational data of the assembly system should be analyzed to manage health states. Therefore, based on the operational data of t...

Superior manufacturing quality is prerequisite to continuously produce reliable products, and the proactive product reliability assurance is always a crucial routine task for manufacturing. Therefore, this paper presents a reliability-oriented optimization model for joint preventive maintenance (PM) and process quality control with time-between-eve...

The rapid development of complexity and intelligence in manufacturing systems leads to an increase in potential operational risks and therefore requires a more comprehensive system-level health diagnostics approach. Based on the massive multi-source operational data collected by smart sensors, this paper proposes a mission reliability-driven manufa...

Product infant failure is the most crucial part of product quality risk that critically affects customer satisfaction. However, most of manufacturers lack sufficient understanding of the formation mechanism of product infant failure and quantitative infant failure risk modeling technology. These issues cause the inefficiency of warranty policy in p...

The paper presents a High order stochastic response surface method (HOSRSM) for reliability and reliability-based sensitivity analyses of transmission mechanism of a shearer in heavy and impulsive environments. Dynamic analysis is affected by several sources of uncertainty, and it is important to quantify their combined effect on performance of the...

The paper considers the reliability and reliability-based sensitivity analyses of planetary gear systems in shearer mechanisms. It is important to quantify the dynamic performance of planetary gear system to aid in risk assessment and risk mitigation of the shearer mechanism. Failure of the system is defined as the dynamic contact stress exceeding...