Green manufacturing has become a new production mode for the development and operation of modern and future manufacturing industries. The flexible job shop scheduling problem (FJSP), as one of the key core problems in the field of green manufacturing process planning, has become a hot topic and a difficult issue in manufacturing production research. In this paper, an improved multi-objective wolf pack algorithm (MOWPA) is proposed for solving a multi-objective flexible job shop scheduling problem with transportation constraints. Firstly, a multi-objective flexible job shop scheduling model with transportation constraints is established, which takes the maximum completion time and total energy consumption as the optimization objectives. Secondly, an improved wolf pack algorithm is proposed, which designs individual codes from two levels of process and machine. The precedence operation crossover (POX) operation is used to improve the intelligent behavior of wolves, and the optimal Pareto solution set is obtained by introducing non-dominated congestion ranking. Thirdly, the Pareto solution set is selected using the gray relational decision analysis method and analytic hierarchy process to obtain the optimal scheduling scheme. Finally, the proposed algorithm is compared with other algorithms through a variety of standard examples. The analysis results show that the improved multi-objective wolf pack algorithm is superior to other algorithms in terms of solving speed and convergence performance of the Pareto solution, which shows that the proposed algorithm has advantages when solving FJSPs.

To improve the scheduling efficiency of flexible job shops, this paper proposes a multi-objective collaborative intelligent agent reinforcement learning algorithm based on weight distribution. First, a mathematical model for flexible job shop scheduling optimization is established, with the makespan and total energy consumption of the shop as optimization objectives, and a disjunctive-graph is introduced to represent state features. Second, two intelligent agents are designed to address the simultaneous decision making problems of jobs and machines. Encoder-decoder components are implemented to facilitate state recognition and action output by the agents. Reward parameters are computed based on temporal differences at various moments, constructing a multi-objective Markov decision-process training model. Using hypervolume, set coverage and inverted generational distance as evaluation metrics, the algorithm is compared with those proposed in other studies on standard instances. The results demonstrate that the proposed method significantly outperforms other algorithms in solving the flexible job shop scheduling problem. Finally, a real-world case study further validates the effectiveness and practicality of the proposed algorithm.

In order to achieve minimum energy consumption in computerized numerical control (CNC) lathe processing under the premise of ensuring the imposed roughness of the machined surface, a black hole-continuous ant colony optimization algorithm (BH-ACO_R) is proposed to optimize the turning parameters. Taking turning specific energy and surface roughness as the optimization objectives, a turning test was designed. Subsequently, a multi-objective mathematical model of the cutting stage was formulated through the application of the least-squares method to fit the test data. The black hole algorithm was introduced to mitigate the shortcomings of the continuous-domain ant colony algorithm, which easily falls into a local optimum, so as to put forward a kind of BH-ACO_R that is applicable to multi-objective optimization. The algorithm was applied to the multi-objective mathematical model in the turning stage to determine the optimal cutting parameters. Through simulation and test verification, the validity and practicability of the proposed method are further proved.

The tension system is one of the most critical systems in gravure printed electronic equipment. It possesses a complex structure that spans the entire feeding process, from unwinding through printing to rewinding. This article focuses on the research of multi-span tension control for printing systems. Firstly, the characteristics and requirements of the tension-control system in the printing section were analyzed, and a multi-span tension-control structure was devised. Then, based on the coupled mathematical model of the multi-span tension system, a static decoupling model was formulated, and a first-order active disturbance rejection control (ADRC) controller was designed utilizing active disturbance rejection control technology. Finally, to verify the control performance of the ADRC decoupling controller for the printing tension system, simulation and experimental studies were conducted using MATLAB/Simulink R2018a and a dedicated experimental platform, and the results were then compared with those obtained from a traditional PID controller. The research findings indicate that the designed multi-span tension-control system demonstrates outstanding decoupling performance and anti-interference capabilities, effectively enhancing the tension-control accuracy of gravure printed electronic equipment.

Due to the large size of the bottom surface, the slipper pair of the large displacement piston pump (LDPP) will form a larger linear speed difference in the inner and outer positions of the slipper relative to the center of the swash plate during high-speed rotation. It is more likely to lead to the slipper overturning, which makes the slipper partially worn. To make improvements, the comprehensive performance of the slipper pair of the LDPP, the motion law of the slipper pair of the LDPP was explored. Firstly, a mathematical model of the oil film thickness of the slipper pair of the LDPP under the state of residual compression force is established, based on the consideration of the linear velocity difference formed by the high-speed rotation of the large bottom surface slipper and the theory of dynamics and thermodynamics. Secondly, the impact of rotational speed, piston chamber pressure and oil temperature on the oil film thickness of the slipper pair was simulated and analyzed. Finally, to measure the oil film thickness of the slipper pair, oil film thickness measuring equipment was created, and the accuracy of the mathematical model was verified. The study revealed the changing rules of the oil film thickness and tilt angle of the bottom surface of the slipper pair under various working conditions. The consistency of the simulation and test findings demonstrates that the mathematical model can accurately describe influencing elements and changing rules of the LDPP slipper pair’s oil film lubrication characteristics.

To improve the performance of the tension control system in gravure printed electronic equipment, it is necessary to study the tension system model of gravure-printing electronic equipment. This paper focuses on the coupling characteristics of multi-span tension systems. Firstly, based on the single-span tension model, the mathematical model of the printing tension subsystem is established and simplified into a general multi-span tension coupling model. Then, using the relationship between the inputs and outputs of the system, the coupling model is simulated using MATLAB/Simulink and verified through experiments on the gravure printed electronic platform. Finally, the coupling relationship and influence laws among multi-physical quantities of the system are analyzed. The research results show that changes in the input web tension of the multi-span system will affect the steady-state tension values of all subsequent spans. Moreover, the speed change in a roller in the multi-span system will not only affect the steady-state tension value of its own span, but also cause transient tension fluctuations in all subsequent spans. The findings of this paper provide an important theoretical basis for the research of the tension system in gravure printed electronic equipment, contributing to the enhancement of printed electronic product quality.