An adaptive evolutionary algorithm with two-stage local search is proposed to solve the multi-objective flexible job-shop scheduling problem (MOFJSP). Adaptivity and efficient solving ability are the two main features. An autonomous selection mechanism of crossover operator is designed, which divides individuals into different levels and selects the appropriate one according to the both sides' levels to improve the self-adaptation. In parameter setting, the autonomous determination and adjustment mechanism is proposed, and parameters are adjusted autonomously according to the job scale and iteration number, so as to reduce the complexity of parameter setting and further improve the adaptivity. For improving solving ability, two-stage local search mechanism is designed. The first stage is performed before the evolution operation, so that each individual has more good genes to participate in the following operation. The second stage is performed after the evolution operation to further search the optimal solutions. Finally, a large number of comparative numerical tests are carried out, compared with other excellent algorithms, the proposed algorithm has fewer parameters to be set and stronger solving ability.

Purpose: The purpose of this paper is to study a method to optimize the arrangement of the devices on a smart assembly workbench, which help to reduce fatigue and improve efficiency for the worker. Design/methodology/approach: The optimization priority is studied based on the users’ decisions, a mathematical model of the layout optimization is established from ergonomic perspective and an improved algorithm is adopted to solve the built the mathematical model. Findings: Ergonomic software Jack is chosen to simulate the four layout schemes obtained. Through comparative analysis of the simulation results, it is proven that the optimal solution can be obtained using the improved algorithm. Originality/value: The mathematical model built on observation comfort, operation comfort and device accessibility, as well as the improved algorithm in this paper, has some reference values for the layout design of smart assembly workbench.

The paper puts forward a monitoring system of machine tools based on the InTouch to solve the problem of poor precision retaining ability of domestic composite CNC machine tools. The system goal is to predict the precision retaining ability of machine tools by Real-time monitoring the MES which provides the key parts of the machining parameters such as size, roughness parameters. The system will alarm to reduce the loss if the precision cannot reach the requirements of the machining. The paper puts forward the framework of the system, and the method of designing the system by combining SQL Server, Matlab and InTouch.

For transformer enterprises, energy consumption and environmental pollution mainly occur in the manufacturing process. The conventional manufacturing mode does not conform to the current green manufacturing mode. The green manufacturing mode requires enterprises to improve the transformer production technology, the utilization rate of materials and equipment, and the production efficiency and to achieve clean production through energy conservation and consumption reduction. The main objective of this research is to schedule the blanking of multiple transformer cores together rather than the conventional calculation conducted one by one. An optimization model of the silicon steel coil blanking is established, an evaluation method for blanking schemes is proposed, algorithms to solve the optimization model are analyzed in detail, and the solving processes and results are compared through a case study. Compared with the current manual calculation, this paper is of practical significance for transformer manufacturers to improve the production efficiency, reduce material waste, meet the personalized market demand characterized by multiple varieties and small batches, and achieve the green manufacturing of transformers.