金属材料智能制造中的数字化制程优化研究

文章探讨了数字化制程优化在金属材料智能制造中的应用。论述了数字化工艺在金属材料制造领域的应用,阐述了其基本理念,及生产效益与品质间的互动效应。其次,深度剖析了数字化制程优化各项技术及策略,包括制程数据解析及智能算法优化运用,涵盖了未来的探索和研究领域。最后,探讨了数字化制程在金属材料智能制造领域的发展前景和挑战,包括发展动向与运用前景,同时剖析了技术应用所遭遇的困境与限制,以及对执行力和持续性发展的评估。文章为金属材料智能制造领域的数字化制程优化提供了理论支撑与实践借鉴。

通过ECID技术实现半导体测试流程优化

本文介绍了如何通过程序有效地解读ECID文件,提取有用信息,并通过ECID数据解决半导体测试中无效复测问题的方法。

压油装置常见故障处理及优化改造

乌江水电开发有限责任公司构皮滩发电厂调速系统压油装置自投产使用以来故障率高,多次发生渗漏、油泵震动过大、油泵无法正常加/卸载等情况,同时油泵运行方式不合理,无法满足经济运行的要求。针对以上情况,从设备密封改造、控制程序优化等方面进行完善提升。大大提高了压油装置的经济性,同时完全避免了因设备缺陷导致的渗漏情况,具有一定的推广价值。

集成电路制造工艺的质量管理分析

阐述集成电路制造中的工艺状况,探讨集成电路制造工艺的质量管理的优化策略,包括晶圆表面的缺陷和杂质的清洗工艺,制程参数的稳定和优化、制程控制系统的统计过程控制、设备的精度和稳定性控制。

轻烃罐区稳高压控制系统优化升级改造

针对罐区稳高压控制系统存在的故障频发,运行不稳定,进行了系统可靠性分析,从提高系统可靠性方面,提出了设备升级改造提高稳定性,优化PLC控制程序的方案。

邯钢生产线电气控制功能改造创新实践

邯郸钢铁集团公司作为河钢集团的核心企业,在创新驱动下基础设施建设和工艺技术水平持续提高。邯郸钢铁集团设备动力部深挖重点设备和工艺电气自动化控制中存在的问题并认真分析其成因,针对“中板线辊缝压下控制”“型钢高压水除磷控制”“连铸大包位置控制”等电气自动化控制问题开展了改造创新实践,完善产线电气功能,优化控制程序,保证生产安全稳定顺行,取得了良好效果。

浅谈低电压下保持电解槽能量平衡的措施

结合240kA铝电解槽低电压运行实践,分析了影响电解槽能量平衡的因素,总结了保持低电压下电解槽能量平衡的几点措施。

手机触控侧键供应商全过程管理分析

供应商管理是在产品设计、试运行直至量产阶段对供应商的产品进行监测,管控并管理的一个过程,目标是保证供应商的各个阶段生产出的产品符合客户标准。在这一过程中,供应商厂内准备的管理系统,控制文件,操作人员,文件记录,设备维护等需符合管控要求,从前端制程到最终出货,管理人员要不断管理供应商使其持续生产出符合客户要求的产品。本文主要介绍一种新型触控技术产品在手机上的成功应用,并对此过程中对供应商的管理模式进行分析。

A New Strategy of Integrated Control and On-line Optimization on High-purity Distillation Process

For high-purity distillation processes,it is difficult to achieve a good direct product quality control using traditional proportional-integral-differential(PID)control or multivariable predictive control technique due to some difficulties,such as long response time,many un-measurable disturbances,and the reliability and precision issues of product quality soft-sensors.In this paper,based on the first principle analysis and dynamic simulation of a distillation process,a new predictive control scheme is proposed by using the split ratio of distillate flow rate to that of bottoms as an essential controlled variable.Correspondingly,a new strategy with integrated control and on-line optimization is developed,which consists of model predictive control of the split ratio,surrogate model based on radial basis function neural network for optimization,and modified differential evolution optimization algorithm. With the strategy,the process achieves its steady state quickly,so more profit can be obtained.The proposed strategy has been successfully applied to a gas separation plant for more than three years,which shows that the strategy is feasible and effective.

A closed-loop particle swarm optimizer for multivariable process controller design

Design of general multivariable process controllers is an attractive and practical alternative to optimizing design by evolutionary algorithms (EAs) since it can be formulated as an optimization problem. A closed-loop particle swarm optimization (CLPSO) algorithm is proposed by mapping PSO elements into the closed-loop system based on control theories. At each time step, a proportional integral (PI) controller is used to calculate an updated inertia weight for each particle in swarms from its last fitness. With this modification, limitations caused by a uniform inertia weight for the whole population are avoided, and the particles have enough diversity. After the effectiveness, efficiency and robustness are tested by benchmark functions, CLPSO is applied to design a multivariable proportional-integral-derivative (PID) controller for a solvent dehydration tower in a chemical plant and has improved its performances.

Optimizing Control of Bio-dissimilation Process of Glycerol to 1,3-Propanedlol

An iterative optimization strategy is proposed and applied to the steady state optimizing control of the bio-dissimilation process of glycerol to 1,3-propanediol in the presence of model-plant mismatch and input constraints. The scheme is based on the Augmented Integrated System Optimization and Parameter Estimation （AI- SOPE） technique, but a linearization of some performance function in the modified model-based optimization problem of AISOPE is introduced to overcome the difficulty of determining an appropriate penalty parameter. When carrying out the iterative optimization, the penalty coefficient is set to a larger value at the current iteration than at the previous iteration, which can promote the evolution rate of the iterative optimization. Simulation studies illustrate the potential ofthe approach presented for the optimizing control of the bioTdissimilation process of glycerol to 1,3-propanediol. The effects of measurement noise, measured and unmeasured disturbances on the proposed algorithm are also investigated.

Novel Control Vector Parameterization Method with Differential Evolution Algorithm and Its Application in Dynamic Optimization of Chemical Processes

Two general approaches are adopted in solving dynamic optimization problems in chemical processes, namely, the analytical and numerical methods. The numerical method, which is based on heuristic algorithms, has been widely used. An approach that combines differential evolution （DE） algorithm and control vector parameteri- zation （CVP） is proposed in this paper. In the proposed CVP, control variables are approximated with polynomials based on state variables and time in the entire time interval. Region reduction strategy is used in DE to reduce the width of the search region, which improves the computing efficiency. The results of the case studies demonstrate the feasibility and efficiency of the oroposed methods.

Study on Preparation Process of Effervescent Tablets Made from EGCG of Tea

[ Objectivel The study aimed to discuss the preparation process of Epigallocatechin-3-gallate （EGCG） effervescent tablets. [ Method] Various raw materials were dried for different time at 50℃, and then the sticking degree of EGCG effervescent tablets was reviewed. Hereafter, the formula of EGCG effervescent tablets was optimized by orthogonal test. [ Result] Effervescent tablets without sticking were smooth after being dried for 150 rain. The optimal formula of EGCG effervescent tablets was composed of 4% EGCG, 45% citric acid and sodium carbonate （Citric acid： Sodium carbonate = 1.6：1 ）, 20% lactose, 4% L-leucine, 4% sodium cyclamate and 23% orange powder. [Condusion] The prepared EGCG effervescent tablets without sticking has a good effervescence effect and taste.

A Priori and A Posteriori Error Estimates of Streamline Diffusion Finite Element Method for Optimal Control Problem Governed by Convection Dominated Diffusion Equation

In this paper,we investigate a streamline diffusion finite element approxi- mation scheme for the constrained optimal control problem governed by linear con- vection dominated diffusion equations.We prove the existence and uniqueness of the discretized scheme.Then a priori and a posteriori error estimates are derived for the state,the co-state and the control.Three numerical examples are presented to illustrate our theoretical results.

Multi-domain modeling and simulation of proportional solenoid valve

A multi-domain nonlinear dynamic model of a proportional solenoid valve was presented.The electro-magnetic,mechanical and fluid subsystems of the valve were investigated,including their interactions.Governing equations of the valve were derived in the form of nonlinear state equations.By comparing the simulated and measured data,the simulation model is validated with a deviation less than 15%,which can be used for the structural design and control algorithm optimization of proportional solenoid valves.

Exploiting Additive Manufacturing Infill in Topology Optimization for Improved Buckling Load

Additive manufacturing （AM） permits the fabrication of functionally optimized components with high geometrical complexity. The opportunity of using porous infill as an integrated part of the manufactur- ing process is an example of a unique AM feature. Automated design methods are still incapable of fully exploiting this design freedom. In this work, we show how the so-called coating approach to topology optimization provides a means for designing infill-based components that possess a strongly improved buckling load and, as a result, improved structural stability. The suggested approach thereby addresses an important inadequacy of the standard minimum compliance topology optimization approach, in which buckling is rarely accounted for; rather, a satisfactory buckling load is usually assured through a post-processing step that may lead to sub-optimal components. The present work compares the stan- dard and coating approaches to topology optimization for the MBB beam benchmark case. The opti- mized structures are additively manufactured using a filamentary technique. This experimental study validates the numerical model used in the coating approach. Depending on the properties of the infill material, the buckling load may be more than four times higher than that of solid structures optimized under the same conditions.

A Comparison of Arithmetic Operations for Dynamic Process Optimization Approach

A comparison of arithmetic operations of two dynamic process optimization approaches called quasi-sequential approach and reduced Sequential Quadratic Programming(rSQP)simultaneous approach with respect to equality constrained optimization problems is presented.Through the detail comparison of arithmetic operations,it is concluded that the average iteration number within differential algebraic equations(DAEs)integration of quasi-sequential approach could be regarded as a criterion.One formula is given to calculate the threshold value of average iteration number.If the average iteration number is less than the threshold value,quasi-sequential approach takes advantage of rSQP simultaneous approach which is more suitable contrarily.Two optimal control problems are given to demonstrate the usage of threshold value.For optimal control problems whose objective is to stay near desired operating point,the iteration number is usually small.Therefore,quasi-sequential approach seems more suitable for such problems.

Multi-objective optimization of rolling schedule based on cost function for tandem cold mill

In terms of tandem cold mill productivity and product quality, a multi-objective optimization model of rolling schedule based on cost fimction was proposed to determine the stand reductions, inter-stand tensions and rolling speeds for a specified product. The proposed schedule optimization model consists of several single cost fi.mctions, which take rolling force, motor power, inter-stand tension and stand reduction into consideration. The cost function, which can evaluate how far the rolling parameters are from the ideal values, was minimized using the Nelder-Mead simplex method. The proposed rolling schedule optimization method has been applied successfully to the 5-stand tandem cold mill in Tangsteel, and the results from a case study show that the proposed method is superior to those based on empirical formulae.

Technology and Practice of Stabiliing Oil Production and Controlling Water Cut in Kalamkas Oilfield in Central Asia

In this paper, by in-depth geological research of Kalamkas Oilfield in Central Asia, the geological body has been re-ascertained; combined with fine study of reservoir engineering, based on the understanding of the distribution of remaining oil horizontal wells have been given full play to stabilizing oil production and controlling water cut, reducing the producing pressure drop, improving well productivity and other advantages, and the development and deployment has been optimized; horizontal wells have been applied to solve problems such as old well casing damages, shutting down wells, low-productivity and low- efficiency wells, and high water cut wells to improve the utilization rate of old wells; through separate layer system improved injection production pattern, adjustment wells have been optimized and deployed, and part measures wells have been preferably selected to tap the residual oil improve the degree of reserves control realize the stabilization of oil production and control of water cut in an old oilfield, and further improve the development effects.

Influence of Design Margin on Operation Optimization and Control Performance of Chemical Processes

Operation optimization is an effective method to explore potential economic benefits for existing plants. The m.aximum potential benefit from operationoptimization is determined by the distances between current operating point and process constraints, which is related to the margins of design variables. Because of various ciisturbances in chemical processes, some distances must be reserved for fluctuations of process variables and the optimum operating point is not on some process constraints. Thus the benefit of steady-state optimization can not be fully achied（ed while that of dynamic optimization can be really achieved. In this study, the steady-state optimizationand dynamic optimization are used, and the potential benefit-is divided into achievable benefit for profit and unachievable benefit for control. The fluid catalytic cracking unit （FCCU） is used for case study. With the analysis on how the margins of design variables influence the economic benefit and control performance, the bottlenecks of process design are found and appropriate control structure can be selected.