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The purpose of this paper is to define new criteria for measuring workload smoothness of two-sided assembly lines and propose an algorithm to solve a two-sided assembly line balancing problem focusing on distributing the idle time and the workload as evenly as possible among the workstations.

This paper points out that the mean absolute deviation (MAD) and the smoothness index (SI) used to measure the workload smoothing in one-sided assembly lines are both inappropriate to evaluate the workload balance among workstations in two-sided assembly lines, as the idle time occur at the beginning and in the middle of a cycle within workstations. Then, the finish-time-based SI and MAD (FSI and FMAD) are defined, and a heuristic procedure based on the core mechanism of Moodie and Young method is proposed to smooth the assembly workload in two-sided assembly lines.

The computational results indicate that the proposed heuristic algorithm combined with the FMAD is effective in distributing the idle time and the workload among workstations as evenly as possible in two-sided assembly lines.

The two-sided assembly line balancing problem with the objective of the line efficiency can be effectively solved by the proposed approach.

The FMAD is proposed to effectively improve the workload smoothing in two-sided assembly lines.

Steam turbine final assembly is a dynamic process, in which various interference events occur frequently. Currently, data transmission relies on oral presentation, while scheduling depends on the manual experience of managers. This mode has low information transmission efficiency and is difficult to timely respond to emergencies. Besides, it is difficult to consider various factors when manually adjusting the plan, which reduces assembly efficiency. The purpose of this paper is to propose a knowledge-based real-time scheduling system under cyber-physical system (CPS) environment which can improve the assembly efficiency of steam turbines.

First, an Internet of Things based CPS framework is proposed to achieve real-time monitoring of turbine assembly and improve the efficiency of information transmission. Second, a knowledge-based real-time scheduling system consisting of three modules is designed to replace manual experience for steam turbine assembly scheduling.

Experiments show that the scheduling results of the knowledge-based scheduling system outperform heuristic algorithms based on priority rules. Compared with manual scheduling, the delay time is reduced by 43.9%.

A knowledge-based real-time scheduling system under CPS environment is proposed to improve the assembly efficiency of steam turbines. This paper provides a reference paradigm for the application of the knowledge-based system and CPS in the assembly control of labor-intensive engineering-to-order products.

The purpose of this paper is to propose an algorithm based on genetic algorithm (GA) to solve the block erection scheduling problem in shipbuilding.

The block erection scheduling problem is defined as the identical parallel machine‐scheduling problem with precedence constraints and machine eligibility (PCME) restrictions. A GA is proposed to find near optimal solution, and a few lower bounds and the percentage of the reduced makespan are defined to evaluate the performance of the proposed algorithm. Finally, the GA for block erection scheduling problem in a shipyard is illustrated by using the real data from a local shipyard.

The proposed GA produces lesser values of makespan against the random heuristic algorithm for the collected real instances.

The proposed GA can solve other similar parallel machine‐scheduling problems with PCME to minimize makespan.

Based on the proposed GA, the developed scheduling system for block erection in a shipyard can reduce the makespan of block erection, and contribute to the productivity improvement.

The allocation of block erection to the crane is modeled as a parallel machine‐scheduling problem with PCME, and the GA is developed to solve this problem to minimize makespan.

Customization, a marketing strategy through providing personalized products, might be a new solution to motivate consumer feedbacks in electronic commerce (e-commerce) websites. Taking the dual-value of customization (emotional involvement and uniqueness expression) as the theoretical basis, this study aims to investigate the impact of customization on consumer's word-of-mouth (WOM) behaviors and contents by motivating: (1) more, (2) faster, (3) positive at first and then negative, (4) longer and (5) more helpful WOMs.

A field study was conducted with multi-sourced data: customer order data from a Chinese retailer and WOM data from Amazon.com. The two datasets were matched to filter out 463 online reviews among 6,892 customers who placed customized orders. Heckman's two-stage model, logistic regression, Ordinary least squares regression, Tobit regression, analysis of covariance and Lind–Mehlum U Test were used in the data analysis.

This study has found that (1) customization level motivates WOM behaviors including WOM posting and WOM speed, (2) an inverted U-shaped relationship exists between customization level and consumer rating and (3) customization level has a significantly positive impact on WOM helpfulness but not on WOM length.

This study advances theoretical development in the area of WOM motivators by proposing a new product-centric approach, customization, to stimulate voluntary WOMs. Empirical field research that analyzes consumer's real responses to customization is in scarcity. The dual-value of customized products is proposed as the underlying mechanism to explain the impact of customization level on consumer's WOM behaviors/contents. An interesting inverted U-shaped relationship is found between customization level and customer rating. This research provides nuanced practical guidance for websites, companies and consumers.

This study aims to focus on the dynamics in influencer-consumer relationships to understand how Generation Z consumers’ identification and social comparison with influencers shape their response to influencers’ branded posts. Specifically, this study investigates how perceived similarity and wishful identification lead to distinct social comparison mechanisms that affect Generation Z consumers’ self-improvement motives, which, in turn, drive their message engagement, brand attitudes and purchase intentions.

An online survey was conducted with 295 college students who are digital natives and whose purchase decisions are heavily influenced by social media influencers.

The study findings confirmed that perceived similarity positively influenced assimilative comparison emotions of optimism, admiration and aspiration while negatively influenced contrastive comparison emotions of envy, depression and resentment. Wishful identification positively affected both assimilative and contrastive comparison emotions. Both types of social comparison emotions further affected consumers’ motivations to follow the influencer for self-improvement, thereby enhancing their brand attitude, purchase intention and engagement behaviors.

This study is one of the earliest attempts to investigate the relationship dynamics between influencers and consumers from the lens of social comparison. The study examines the antecedents of perceived similarity and wishful identification, the mediators of upward comparison emotions and self-improvement motives and the brand evaluation outcomes of message engagement, brand attitude and purchase intention.

This research aims to investigate the trajectory tracking problem for a four-wheel independent drive autonomous vehicle (4WID) and propose an integrated, coordinated control strategy to address the mutual interference between trajectory tracking and stability control in extreme cases.

The authors establish an adaptive preview model that modifies the preview distance based on vehicle speed. They utilize a three-degrees-of-freedom vehicle model and employ model predictive control to calculate the necessary front wheel angle for trajectory tracking. In terms of longitudinal control, a longitudinal coordinated control mechanism is established to achieve the two conflicting objectives of trajectory tracking accuracy and dynamic stability through early deceleration. A stability controller based on sliding mode control (SMC) is designed, considering tire constraints and tracking the optimal yaw angle and sideslip angle. Furthermore, a lateral coordinated control strategy is developed, considering the weight coefficient of stability control, and the yaw moment is calculated and distributed based on the vehicle torque requirements.

The proposed integrated, coordinated control strategy successfully addresses the mutual interference between trajectory tracking and stability control in extreme cases for the 4WID vehicle. The strategy achieves trajectory tracking accuracy, dynamic stability and reduced energy consumption while taking into account tire constraints.

We have proposed a cooperative control strategy for the trajectory tracking problem of autonomous driving vehicles. This strategy is different from previous methods in that we have taken into account the integrated dynamic control in both longitudinal and lateral directions, balancing the conflicting control requirements and reducing energy consumption, improving trajectory tracking accuracy and vehicle dynamic stability. We have verified the feasibility of this strategy through joint simulation under different driving conditions.

This paper aims to develop sliding mode control (SMC) methods for second-order multi-agent systems (MAS) in the presence of mismatched uncertainties.

Based on the disturbance observer (DOB), discontinuous and continuous sliding mode protocols are designed to achieve finite-time consensus in spite of the disturbances.

Compared with integral SMC, numerical simulation results show that the proposed control methods exhibit better performance with respect to reduction of chattering.

The main contributions are the following: MAS described with mismatched uncertainties are considered; both discontinuous and continuous sliding mode controllers are considered; with the proposed sliding mode controller, the desired sliding surface can be reached in finite time and the DOB is introduced in the controller to alleviate the chattering phenomenon.

In this paper, the C80 special coal gondola car was taken as the subject, and the load test data of the car body at the center plate, side bearing and coupler measured on the dedicated line were broken down to generate the random load component spectrums of the car body under five working conditions, namely expansion, bouncing, rolling, torsion and pitching according to the typical motion attitude of the car body.

On the basis of processing the measured load data, the random load component spectrums were equivalently converted into sinusoidal load component spectrums for bench test based on the principle of pseudo-damage equivalence of load. Relying on the fatigue and vibration test bench of the whole railway wagon, by taking each sinusoidal load component spectrum as the simulation target, the time waveform replication (TWR) iteration technology was adopted to create the drive signal of each loading actuator required for the fatigue test of car body on the bench, and the drive signal was corrected based on the equivalence principle of measured stress fatigue damage to obtain the fatigue test loads of car body under various typical working conditions.

The fatigue test results on the test bench were substantially close to the measured test results on the line. According to the results, the relative error between the fatigue damage of the car body on the test bench and the measured damage on the line was within the range of −16.03%–27.14%.

The bench test results basically reproduced the fatigue damage of the key parts of the car body on the line.

The purpose of this paper is to study the aerodynamic characteristics of Ahmed body in longitudinal and lateral platoons under crosswind by computational fluid dynamics simulation. It helps to improve the aerodynamic characteristics of vehicles by providing theoretical basis and engineering direction for the development and progress of intelligent transportation.

A two-car platoon model is used to compare with the experiment to prove the accuracy of the simulation method. The simplified Ahmed body model and the Reynolds Averaged N-S equation method are used to study the aerodynamic characteristics of vehicles at different distances under cross-winds.

When the longitudinal distance x/L = 0.25, the drag coefficients of the middle and trailing cars at β = 30° are improved by about 272% and 160% compared with β = 10°. The side force coefficients of the middle and trailing cars are increased by 50% and 62%. When the lateral distance y/W = 0.25, the side force coefficients of left and middle cars at β = 30° are reduced by 38% and 37.5% compared with β = 10°. However, the side force coefficient of the right car are increased by about 84.3%.

Most of the researches focus on the overtaking process, and there are few researches on the neat lateral platoon. The innovation of this paper is that in addition to studying the aerodynamic characteristics of longitudinal driving, the aerodynamic characteristics of neat lateral driving are also studied, and crosswind conditions are added. The authors hope to contribute to the development of intelligent transportation.

This paper aims to present a method for improving the performance of the visual-inertial navigation system (VINS) by using a bio-inspired polarized light compass.

The measurement model of each sensor module is derived, and a robust stochastic cloning extended Kalman filter (RSC-EKF) is implemented for data fusion. This fusion framework can not only handle multiple relative and absolute measurements, but can also deal with outliers, sensor outages of each measurement module.

The paper tests the approach on data sets acquired by a land vehicle moving in different environments and compares its performance against other methods. The results demonstrate the effectiveness of the proposed method for reducing the error growth of the VINS in the long run.

The main contribution of this paper lies in the design/implementation of the RSC-EKF for incorporating the homemade polarized light compass into visual-inertial navigation pipeline. The real-world tests in different environments demonstrate the effectiveness and feasibility of the proposed approach.