Search results

The combination of improved PSO (IPSO) algorithm and artificial neural network (ANN) model for intelligent monitoring of the bearing performance of the hydrostatic turntable.

This paper proposes an artificial neural network model based on IPSO algorithm for intelligent monitoring of hydrostatic turntables.

The theoretical model proposed in this paper improves the accuracy of the working performance of the static pressure turntable and provides a new direction for intelligent monitoring of the static pressure turntable. Therefore, the theoretical research in this paper is novel.

Theoretical novelties: an ANN model based on the IPSO algorithm is designed to monitor the load-bearing performance of a static pressure turntable intelligently; this study show that the convergence accuracy and convergence speed of the IPSO-NN model have been improved by 52.55% and 10%, respectively, compared to traditional training models; and the proposed model could be used to solve the multidimensional nonlinear problem in the intelligent monitoring of hydrostatic turntables.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-03-2024-0081/

The purpose of this paper is to design a climbing robot connected by a connecting rod mechanism to achieve multi-functional tasks such as obstacles crossing and climbing of power transmission towers.

A connecting rod type gripper has been designed to achieve stable grasping of angle steel. Before grasping, use coordination between structures to achieve stable docking and grasping. By using the alternating movements of two claws and the middle climbing mechanism, the climbing and obstacle crossing of the angle steel were achieved.

Through a simple linkage mechanism, a climbing robot has been designed, greatly reducing the overall mass of the robot. It can also carry a load of 1 kg, and the climbing mechanism can perform stable climbing. The maximum step distance of the climbing robot is 543 mm, which can achieve the crossing of angle steel obstacles.

A transmission tower climbing mechanism was proposed by analyzing the working environment. Through the locking ability of the screw nut, stable clamping of the angle steel is achieved, and a pitch mechanism is designed to adjust the posture of the hand claw.

High power rotating machinery requires large diameter bearings that can perform under extreme conditions. Vibrations and critical speeds of rotor supported by tilting pad journal bearing (TPJBs) exceeding their design limits may cause unit failure. This paper aims to investigate the experimental technique for large diameter bearings.

To obtain the experimental support for rotor-bearing system design, an experiment focusing on vibration monitoring is given. The sensors arrangement, monitoring system and critical speed identification method are provided.

By using test bench in factory unit, a large amount of vibrations data of different working situations is obtained. In addition, a method named non-excitation identification for critical speed is proposed. The critical speed of rotor identified through vibration data is given. The theoretical calculation results are also presented.

The basis for rotor-bearing system design can be obtained through comparisons between the experimental results and the theoretical calculation data.

This paper aims to automatically plan sequence for complex assembly products and improve assembly efficiency.

An assembly sequence planning system for workpieces (ASPW) based on deep reinforcement learning is proposed in this paper. However, there exist enormous challenges for using DRL to this problem due to the sparse reward and the lack of training environment. In this paper, a novel ASPW-DQN algorithm is proposed and a training platform is built to overcome these challenges.

The system can get a good decision-making result and a generalized model suitable for other assembly problems. The experiments conducted in Gazebo show good results and great potential of this approach.

The proposed ASPW-DQN unites the curriculum learning and parameter transfer, which can avoid the explosive growth of assembly relations and improve system efficiency. It is combined with realistic physics simulation engine Gazebo to provide required training environment. Additionally with the effect of deep neural networks, the result can be easily applied to other similar tasks.

The government plays an important role in the financing process of small and medium enterprises (SMEs), but the current government-enterprise cooperation (GEC) mechanism cannot well solve the financing problem of SMEs. In addition, since government-enterprise cooperation is a long-term dynamic process, this study aims to explore the cooperation strategy between the government and core enterprises in supply chain finance (SCF) under the dynamic structure.

Considering both parties have the characteristics of disappointment aversion, our research constructs a game theory model of government subsidy and the effort of the enterprise to implement SCF based on differential game and studies different game strategies in the non-cooperative game, the Stackelberg game and the cooperative game.

Our findings show that the government subsidy can significantly spur the enterprise in the supply chain to implement SCF. We also find that the limitation of the government subsidy exists. In addition, the optimal strategy, the optimal benefit and the total benefit of the financing system formed by the government and the enterprise in the cooperative game are better than those in the non-cooperative game. Pareto optimality is achieved.

The limitations of this paper are: (1) In theory, this paper only takes the government and enterprise as game subjects without considering other participants in the supply chain. In addition, only disappointment aversion is taken into consideration while in reality the participants often exhibit multiple behavior preferences. (2) In methodology, only the numerical solution is given through the solution algorithm and all parameters are assumed to be determined as time changes for the convenience of calculation.

The government can motivate enterprises in the supply chain to implement SCF by providing subsidies. However, it should be noted that excessive subsidy will make the enterprise dependent on the government and as a result, decrease the effort level to implement SCF. Thus, it is necessary for the government to keep track of the business conditions of the enterprise to make a subsidy strategy. In addition, the government can reduce the impact of disappointing aversion by making more targeted policies and taking risk management measures.

On one hand, it is necessary for the government to keep track of the business conditions of the enterprise to make a subsidy strategy. In addition, the government can reduce the impact of their own disappointing aversion by making more targeted policies and adopting risk management measures. On the other, it is important for the enterprise to improve the regulatory mechanism and optimize the compensation structure of decision-makers to inhibit the impact of decision-makers' disappointing aversion.

This study is the first to investigate the mechanism of GEC in the setting of SCF based on a differential game. Furthermore, our study provides a theoretical basis for the government and enterprises to cooperate in SCF.

The paper seeks to investigate the laser engineered net shaping (LENS) of metal thick‐wall parts from Ni‐based alloy powders.

The composition of Ni‐based alloy powders was determined from phase diagram, which was 84Ni14.4Cu1.6Sn. The powders were prepared by gas atomization. Deoxygenation and screen separation were applied to the powders to improve the sintering ability and narrow the particle size distribution before shaping. Thick‐wall metal parts were built by LENS under different conditions. The microstructures, surface morphologies of the prepared parts were characterized.

The gas atomized powders were almost uniformly spherical after sieving. Most of oxygen contained in the alloy powders could be removed in H₂ atmosphere for heating at 550°C for 2 h. These nickel‐based alloy powders with 150‐200 mesh size were suitable for powder feed system. And these powders were shaped successfully by LENS. Thick‐wall parts with thickness ranged from 20 to 25 mm were fabricated. The thickness of each layer was between 400 and 600 μm by scanning electron microscope. Metallographs revealed that dendritic structures with different characteristics were grown on XY‐, YZ‐ and XZ‐section.

The present experiments were limited by the atmosphere control during the LENS process. The oxide at the interface between two neighbor layers could decrease the mechanical properties if without good inert gas protection, such as a protective atmosphere chamber.

This paper describes a refined experimental program that is needed to resolve the remaining technical issues in LENS of thick‐wall parts. The nickel‐based alloy powders suitable for the LENS process were studied and prepared. After pretreatment, the self‐made powders have good shaping ability. Microstructure features were first discussed with the variation of the face orientation. The dendrite arm distance obtained by this experiment is between 8 and 20 μm, well conforming to the theory. The thick‐wall parts with dense structures were fabricated successfully to widen the field of application of LENS.

This paper aims to present the theoretical and experimental investigation of the temperature of high speed and heavy haul tilting pad journal bearing.

The bearing is 152.15 mm in diameter with three slenderness ratios (L/D) and three clearance ratios. The equations that govern the flow and energy transport are solved by the finite difference method, and the experimental tests are conducted in a test rig of high speed and heavy haul tilting pad journal bearing. The shaft speed ranges from 3,000 to 16,500 r/min (the highest linear-velocity equals 131.4 m/s), and the three static loads are 10, 20 and 30 KN.

The comparisons between numerical results and experimental results show better correlations. It is shown in the theoretical and experimental results that the temperature increases with static load and shaft speed and decreases with clearance ratio and L/D.

The theoretical models presented in this paper can be used to predict the temperature of tilting pad journal bearing when the shaft’s linear velocity is up to 130 m/s.

This paper provides the latest systematic literature review (SLR) of prevailing studies on the interrelationship among executive compensation, financial performance and sustainable business practices. This SLR is done in three parts: (1) examine the theories employed by previous studies; (2) identify the unique variables employed by researchers in analysing this interrelationship and (3) explore potential opportunities for further study in the field.

This study conducted an SLR analysing studies from the Web of science, Scopus and EBSCO in over 20 countries from 2009 to 2022 published in several top-ranked journals. We utilised various search strings using the key phrases “executive compensation”, “CEO Pay”, “financial performance” and “sustainable business practices”. The initial sample of 27,210 was filtered with our meticulous inclusion and exclusion criteria to produce a list of 161 studies.

Our findings are as follows: first, most studies encompassing this subject area lack multi-theoretical perspectives with agency theory being the most dominant theoretical viewpoint; second, we observed the use of monotonous quantitative research methods, with studies heavily lacking qualitative and mixed-method research approaches; finally, there is a palpable gap in cross-country studies.

There are a few limitations that must be acknowledged. First, the inclusion criteria ensured that only articles published in the CABS journal ranking of three star and above. Thus, this review may not be a precise reflection of the EC, FP and SBPs literature scope. The inclusion criteria also limit our review to only accounting, finance, management and business-related studies about the topic. Therefore, future studies could explore studies ranked three star and below and from other subject areas.

This study contributes to the existing literature by conducting a comprehensive SLR that examines both the theoretical underpinnings and empirical evidence on this topic. It builds upon previous research and extends our understanding of the interrelationship among executive compensation, financial performance and sustainable business practices.

This study aims to examine the impact of logistics and merchant certification information on consumer behaviour in hybrid retail platforms. Furthermore, it explores the moderating role of online shopping experience on the certification effect.

The authors utilize transaction-level data from over 2.5 million consumers involving 30,000 stock keeping units (SKUs) on JD.com in March 2018. They analyse the impact of different types of certification information on consumer behaviour using ordinary linear regression and linear probability models.

The findings reveal that, compared with information without certification, (1) single logistics certification information can enhance consumers' search depth and purchase intention; (2) dual logistics and merchant certification information also has a positive impact on consumer behaviour; and (3) single certification information is more effective for inexperienced consumers, while dual certification is more effective for experienced consumers.

Theoretically, this study contributes to the literature on certification information in hybrid retail platforms and broadens information communication methods for online shopping. Our discovery is meaningful for managers in locating customers and allocating resources. In addition, we encourage online retailers to utilize certification information to engage consumer.

Hand, foot and mouth disease (HFMD) is a common infectious disease in infants and children. HFMD has caused millions of cases and a large epidemic worldwide. A number of studies have shown that the incidence of HFMD is closely related to various factors such as meteorological factors, environmental air pollution factors and socio-economic factors. However, there are few studies that systematically consider the impact of various factors on the incidence of HFMD. The paper aims to discuss these issues.

This study used grey correlation analysis and principal component analysis (PCA) method to systematically analyse the impact of meteorological factors, health resource factors, socio-economic factors and environmental air pollution factors on the incidence of HFMD in Shenzhen.

The incidence of HFMD in Shenzhen was affected by multiple factors. Grey correlation analysis found eight influencing factors which are as follows: volume of industrial waste gas emission; the days of air quality equal to or above grade; the volume of industrial nitrogen oxide emission; precipitation; the mean air temperature; the gross domestic product; the expenditure for medical and health care; and the gross domestic product per capita. PCA found that the gross domestic product, the volume of industrial soot emission, the relative humidity, and the days of air quality equal to or above grade have a higher load value.

This study is the one of the first studies that apply the grey correlation analysis to analyse the influencing factors of HFMD in the English literature, which to some extent fills up the blank in this field.