Aiming at the problems of irrational allocation of resources, low efficiency caused by unbalanced production line layout, and slow production line upgrade of the smart factory, this paper builds a real physical smart factory platform through the optimal control strategy and uses the GRAFCET algorithm to optimize the logistics scheduling during the actual system operation. The genetic algorithm is used to optimize the layout effect of the production line; the digital twin technology is used to provide predictive analysis technical support for the upgrading and reengineering of the production line. Through the analysis and comparison of the production capacity and equipment utilization of the physical smart factory and the virtual smart factory processing scheme, practice shows that the design of the digital twin system can effectively improve the effect and accuracy of the lean production method in the production process reorganization. Quantitative analysis of manufacturing industry provides powerful theoretical and technical support.

Energy-intensive enterprises lack a scientific and effective energy efficiency assessment framework and methodology. This lack leads to an inaccurate understanding of energy usage and its benefits. As a result, there is energy wastage and loss. This wastage and loss negatively affect product costs. They also present a challenge to effective energy management. To address these issues, this paper introduces a novel, comprehensive energy efficiency evaluation system. This system integrates both qualitative and quantitative measures. It proposes an evaluation model based on the Particle Swarm Optimization (PSO) combined with the Analytic Hierarchy Process (AHP) and Fuzzy Comprehensive Evaluation (FCE), wherein PSO is employed to optimize the weights determined by AHP, ensuring that the significance attributed to various indicators is scientific, objective, and rational. The FCE method is utilized to convert diverse factors affecting corporate energy efficiency, across different types and scales, into standardized 0–1 values, enabling a comparative analysis of the impact of each process and indicator on energy efficiency. Furthermore, the paper introduces an energy efficiency prediction model employing a multivariate linear regression algorithm, which demonstrates a good fit, facilitating the transition from retrospective energy efficiency evaluation to proactive improvements. Utilizing data on actual consumption of water, electricity, and steam from an enterprise, along with expert assessments on the implementation levels of new processes, technologies, equipment, personnel scheduling proficiency, steam recovery rates, and adherence to policies and assessments, a simulation experiment of the proposed model was conducted using Python. The evaluation yielded an energy efficiency score of 0.68; this is consistent with the real-world scenario of the studied enterprise. The predicted mean square error of 9.035416039503998 $\times {10}^{-9}$ indicates a high model accuracy, validating the practical applicability and effectiveness of the proposed approach.

With the global water crisis is getting more and more serious, industrial and sewage treatment are becoming the urgent problem need to be solved.In this paper, sewage treatment project of a factory is research object, the design using the upper computer configuration software from YAKONG of China which named KINGVIEW6.53 and using the PLC from Siemens...

This paper introduces a model reference adaptive system observer based on the non‐singular fast terminal sliding mode (NFSM‐MRASO) for the purpose of sensorless control of permanent magnet synchronous motors (PMSMs) in electric vehicle applications. Firstly, a non‐singular fast terminal sliding surface is constructed based on the output errors of the reference model and the adjustable model. This ensures that the output errors between the two models converge to zero in a finite time and effectively avoids the singularity problem in the terminal sliding mode control. In addition, a novel reaching law (NRL) is designed to replace the traditional exponential reaching law (TRL) to suppress the chattering phenomenon in the sliding mode control. Finally, the feasibility and effectiveness of the NFSM‐MRASO strategy are demonstrated through simulation results.

This paper presents a new design concept for the single treatment of X/O type lower limb rehabilitation instrument, the new design concept, modeling and simulation using SOLIDWORKS, the force analysis using ADAMS, control the use of single-chip microcomputer, the real realization of a set of rehabilitation, massage and promoting blood circulation in one of the functions of the machine, and has a very broad market application prospect.

Taking VB as a developing platform, the thesis constructs a real-time,interactive and extending virtual laboratory system.This system can make full use of network resource,reduce hard ware investing,which makes it a low-cost,high profit information-based foundation with prodigious practical signification.