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The purpose of this paper is proposed a new structure design for high performance accelerometer.

An improved sensitivity structure considering sensitivity, natural frequency and cross-axis sensitivity is established and realized. The proposed structure was designed to improve the trade-off between the sensitivity and the natural frequency of piezoresistive accelerometer and eliminate the lateral sensitivity effect by the specific configuration, which is made possible by incorporating slots into the eight-beam structure. The mechanical model and its mathematical solution are established for calculating the sensitivity and natural frequency behavior of the designed structure. The developed sensor is fabricated on the n-type single-crystal silicon wafer and packaged for experiment. The accelerometer prototype was tested in the centrifugal machine and dynamic calibration system.

The experimental results show that the sensitivity of the designed sensor is 0.213 mV/(Vg) and the natural frequency of the sensor is 14.22 kHz. Compared with some piezoresistive accelerometers in literatures, the designed sensor possesses a suitable characteristic in sensitivity, natural frequency and transverse effect, which allows its usage in measuring high frequency vibration signals.

The accelerometer with slotted eight-beam structure shows a good performance in the static and dynamic experiments and can be used in measuring high frequency vibration signals.

The accuracy of the machining process is significantly impacted by the performance of hydrostatic bearings. This paper aims to analyze the influence of micro-textured on the performance of the hydrostatic bearing, and the performance of the bearing is improved by designing the arrangement of micro-textured.

Different designs have been used while creating micro-textured bearings. The finite element models of bearing with smooth and micro-textured were established and solved using the computational fluid dynamics method. The arrangement scheme of the micro-textured was evaluated by comparing the influence of the distribution position and arrangement of the micro-textured on the bearing performance.

To improve the performance of the bearing, the bearing capacity was significantly increased, and the friction coefficient of the bearing was decreased when the micro-textured was distributed in the form of an obtuse angle arrangement in the maximum pressure area of the bearing. The experimental findings validate the analysis method.

In this paper, the effect of irregularly arranged micro-textured on bearing performance is investigated to improve the bearing capacity and lubrication status.

The purpose of this paper is to investigate the effect of fluid–structure interaction in micro-scale on the performance of the hydrostatic spindle and improve the analysis precision of the dynamic performance of hydrostatic spindle.

Dynamic analysis of hydrostatic spindle before and after fluid–structure interaction is carried out according to stiffness and damping performance of the bearing, which demonstrates that the natural frequency and peak response of the spindle are increased in the micro-scale.

It is concluded from the simulation and experimental results that there is micro-scale effect in the actual operation of the spindle system and slippage exists in the oil film flow. The error between the modal detection result and the theoretical value is within 10 per cent, which also verifies the correctness of the above conclusions.

This paper analyzes the changes of the bearing performance parameters at macro- and micro-scale, which present the influence of the static and dynamic performance of the spindle in the micro-scale.

The purpose of this paper is to develop a risk evaluation method for the industrial network under high uncertain environment.

This paper introduces an extended safety and critical effect analysis (SCEA) method, which takes the weight of each industry in a network into risk assessment. Furthermore, expert experience and fuzzy logic are introduced for the evaluation of other parameters.

The proposed approach not only develops weight as the fifth parameter in quantitative risk assessment but also applies the interval type-2 fuzzy sets to depict the uncertainty in the risk evaluation process. The risk rating of each parameter excluding weight is determined by using the interval type-2 fuzzy numbers. The risk magnitude of each industry in the network is quantified by the extended SCEA method.

There is less study in quantitative risk assessment in the industrial network. Additionally, fuzzy logic and expert experience are expressed in the presented approach. Moreover, different parameters can be determined by different weights in network risk assessment in the future study.

The extended SCEA method presents a new way to measure risk magnitude for industrial networks. The industrial network is developed in risk quantification by assessing weights of nodes as a parameter into the extended SCEA. The interval type-2 fuzzy number is introduced to model the uncertainty of risk assessment and to express the risk evaluation information from experts.

Assessing the severity of failure modes of critical industrial machinery is often considered as an onerous task and sometimes misinterpreted by shop-floor engineer/maintenance personnel. The purpose of this paper is to develop an improved FMECA method for prioritizing the failure modes as per their risk levels and validating the same through a real case study of induction motors used in a process plant.

This paper presents a novel hybrid multi-criteria decision-making (MCDM) approach to prioritize different failure modes according to their risk levels by combining analytical hierarchy process (AHP) with a newly introduced MCDM approach, election based on relative value distance (ERVD). AHP is incorporated in the proposed approach to determine the criteria weights, evaluated in linguistic terms by industrial expert. Furthermore, ERVD, which is based on the concept of prospect theory of human cognitive process, is applied to rank the potential failure modes.

It is found that the proposed FMECA approach provides better results in accordance with the actual industrial scenario and helps in effectively prioritizing the failure modes. A comparison is also made to highlight the differences of results between the proposed approach with TOPSIS and conventional FMECA.

This research paper proposes an improved FMECA method and, thus, provides a deep insight to maintenance managers for effectively prioritizing the failure modes. The correct prioritization of failure modes will help in effective maintenance planning, thus reducing the downtime and improving profit to the organization.

A real case of process plant induction motor has been introduced in the research paper to show the applicability of this decision-making approach, and the approach is found to be suitable in correct prioritization of the failure modes.

Severity has been decoupled into various factors affecting it, to make it more relevant as per actual industrial scenario. Then, a novel modified FMECA has been developed using a hybrid MCDM approach (AHP and ERVD). This hybrid method, as well as its application in FMECA, has not been developed by any previous researcher. Moreover, the same has been thoroughly explained by considering a real case of process plant induction motors and validated with cross-functional experts.

This paper aims to report on a literature review that aimed to establish a guiding framework for the development of digital scholarship services in China’s university libraries.

The framework was developed through systematically searching, screening, assessing, coding and aggregating digital scholarship services as reported in the existing body of literature. Three types of literature were included in the analysis: international academic literature as reported in English; academic literature in Chinese; and relevant professional reports.

The literature analysis pointed to 25 different digital scholarship services, which emerged in six themes: supporting services, formulating research ideas, locating research partners, writing proposals, conducting research and publishing results.

Although this literature review focused on university libraries in China, the research findings and the guiding framework developed provide useful insights and indications that can be shared across international borders.

This study examined the students' academic performance through psychological capital, academic engagement and academic persistence. It also investigated the function of psychological capital in mediating the relationship between academic engagement, persistence and performance.

The study utilized a quantitative method and structural equation modeling using PLS-SEM version 3. A total of 900 questionnaires were issued to Chinese university students, and 814 data were analyzed.

Findings suggest that academic engagement and persistence significantly and positively impact psychological capital. Psychological capital is also mediated between academic engagement, persistence and performance. Additionally, the study made several recommendations for upcoming researchers and industry professionals.

Analyzing the pupils' academic achievement after COVID-19 reopening as it indicates their attention and engagement in the study. Although previous studies explored students' academic performance regarding the post-COVID effect, the role of psychological capital and engagement in academia in the study has been studied in a post-COVID context.

Asymmetric cost information exists between a supplier and a manufacturer regarding the manufacturer's process innovation for remanufacturing (PIR), which may hurt the supplier's profit. The authors therefore seek to develop a menu of nonlinear pricing contracts for channel information sharing.

Based on principal–agent theory, the supplier, acting as a Stackelberg leader, designs a menu of nonlinear pricing contracts to impel the manufacturer to disclose its private cost information on PIR (i.e. PIR efficiency). In addition, the authors compare the equilibrium outcomes under asymmetric and symmetric information to examine the effects of asymmetric PIR information on the production policies and profits of the supplier and the manufacturer.

The proposed contract menu encourages th4e manufacturer to spontaneously share PIR efficiency information with the supplier. Asymmetric PIR information may distort the output of new products upward or downward, but the output of remanufactured products may only be distorted downward. In addition, the manufacturer with high PIR efficiency gains information rent, and interestingly, the increase in the probability of low PIR efficiency amplifies its information rent. Finally, an asymmetric information environment may increase the threshold for the manufacturer to enter remanufacturing.

The authors probe the issue of the supplier's contract design by jointly considering remanufacturing, process innovation and information asymmetry. The paper expands the influencing mechanism of process innovation information in the remanufacturing field. The authors also observe new results that may offer guidance to decision makers.

The purpose of this paper is to propose an integrative approach for improving failure modes and effects analysis (FMEA).

An extensive literature review on FMEA has been performed. Then, an integrative approach has been proposed based on literature review. The proposed approach is an integration of FMEA and quality function deployment (QFD). The proposed approach includes a two-phase QFD. In the first phase, failure modes are prioritized based on failure effects and in the second phase, failure causes are prioritized based on failure modes. The proposed approach has been examined in a case example at the blast furnace operation of a steel-manufacturing company.

Results of the case example indicated that stove shell crack in hot blast blower, pump failure in cooling water supply pump and bleeder valves failed to operate are the first three important failure modes. In addition, fire and explosion are the most important failure effects. Also, improper maintenance, over pressure and excess temperature are the most important failure causes. Findings also indicated that the proposed approach with the consideration of interrelationships among failure effects, failure mode and failure causes can influence and adjust risk priority number (RPN) in FMEA.

As manufacturing departments are mostly dealing with failure effects and modes of machinery and maintenance departments are mostly dealing with causes of failures, the proposed model can support better coordination and integration between the two departments. Such support seems to be more important in firms with continuous production lines wherein line interruption influences response to customers more seriously. A wide range of future study opportunities indicates the attractiveness and contribution of the subject to the knowledge of FMEA.

Although the literature indicates that in most of studies the outcomes of QFD were entered into FMEA and in some studies the RPN of FMEA was entered into QFD as importance rating, the proposed approach is a true type of the so-called “integration of FMEA and QFD” because the three main elements of FMEA formed the structure of QFD. In other words, the proposed approach can be considered as an innovation in the FMEA structure, not as a data provider prior to it or a data receiver after it.

The purpose of this paper is to identify critical equipment by dynamically ranking them in interval-valued intuitionistic fuzzy (IVIF) circumstances. Accordingly, the main drawbacks of the conventional failure mode and effects analysis (FMEA) are eliminated. To this end, the authors have presented the interval-valued intuitionistic fuzzy condition-based dynamic weighing method (IVIF-CBDW).

To realize the objective, the authors used the IVIF power weight Heronian aggregation operator to integrate the data extracted from the experts’ opinions. Moreover, the multi-attributive border approximation area comparison (MABAC) method is applied to rank the choices and the IVIF-CBDW method to create dynamic weights appropriate to the conditions of each equipment/failure mode. The authors proposed a robust FMEA model where the main drawbacks of the conventional risk prioritization number were eliminated.

To prove its applicability, this model was used in a case study to rank the equipment of a HL5000 crane barge. Finally, the results are compared with the traditional FMEA methods. It is indicated that the proposed model is much more flexible and provides more rational results.

In this paper, the authors have improved and used the IVIF power weight Heronian aggregation operator to integrate information. Furthermore, to dynamically weigh each equipment (failure mode), they presented the IVIF-CBDW method to determine the weight of each equipment (failure mode) based on its equipment conditions in the O, S and D criteria and provide the basis for the calculation. IVIF-CBDW method is presented in this study for the first time. Moreover, the MABAC method has been performed, to rank the equipment and failure mode. To analyze the information, the authors encoded the model presented in the robust MATLAB software and used it in a real sample of the HL5000 crane barge. Finally, to evaluate the reliability of the model presented in the risk ranking and its rationality, this model was compared with the conventional FMEA, fuzzy TOPSIS method, the method of Liu and the modified method of Liu.