间歇化工过程和模型优化调度

Chemical batch processes have become significant in chemical manufacturing.In these processes,large numbers of chemical products are produced to satisfy human demands in daily life.Recently,economy globalization has resulted in growing worldwide competitions in traditional chemical process industry.In order to keep competitive in the global marketplace,each company must optimize its production management and set up a reactive system for market fluctuation.Scheduling is the core of production management in chemical processes.The goal of this paper is to review the recent developments in this challenging area.Classifications of batch scheduling problems and optimization methods are introduced.A comparison of six typical models is shown in a general benchmark example from the literature.Finally,challenges and applications in future research are discussed.     

Integration of a Gas Fired Steam Power Plant with a Total Site Utility Using a New Cogeneration Targeting Procedure

A steam power plant can work as a dual purpose plant for simultaneous production of steam and elec-trical power. In this paper we seek the optimum integration of a steam power plant as a source and a site utility sys-tem as a sink of steam and power. Estimation for the cogeneration potential prior to the design of a central utility system for site utility systems is vital to the targets for site fuel demand as well as heat and power production. In this regard, a new cogeneration targeting procedure is proposed for integration of a steam power plant and a site utility consisting of a process plant. The new methodology seeks the optimal integration based on a new cogenera-tion targeting scheme. In addition, a modified site utility grand composite curve （SUGCC） diagram is proposed and compared to the original SUGCC. A gas fired steam power plant and a process site utility is considered in a case study. The applicability of the developed procedure is tested against other design methods （STAR？ and Thermoflex software） through a case study. The proposed method gives comparable results, and the targeting method is used for optimal integration of steam levels. Identifying optimal conditions of steam levels for integration is important in the design of utility systems, as the selection of steam levels in a steam power plant and site utility for integration greatly influences the potential for cogeneration and energy recovery. The integration of steam levels of the steam power plant and the site utility system in the case study demonstrates the usefulness of the method for reducing the overall energy consumption for the site.     

Decision support for the development,simulation and optimization of dynamic process models

Simulation is besides experimentation the major method for designing,analyzing and optimizing chemical processes.The ability of simulations to reflect real process behavior strongly depends on model quality.Validation and adaption of process models are usually based on available plant data.Using such a model in various simulation and optimization studies can support the process designer in his task.Beneath steady state models there is also a growing demand for dynamic models either to adapt faster to changing conditions or to reflect batch operation.In this contribution challenges of extending an existing decision support framework for steady state models to dynamic models will be discussed and the resulting opportunities will be demonstrated for distillation and reactor examples.     

Chromosomal Engineering of Escherichia coli for Efficient Production of Coenzyme Q10

The plasmid-expression system is routinely plagued by potential plasmid instability. Chromosomal in-tegration is one powerful approach to overcome the problem. Herein we report a plasmid-free hyper-producer E. coli strain for coenzyme Q10 production. A series of integration expression vectors, pxKC3T5b and pxKT5b, were constructed for chemically inducible chromosomal evolution （multiple copy integration） and replicon-free and markerless chromosomal integration （single copy integration）, respectively. A coenzyme Q10 hyper-producer Es-cherichia coli TBW20134 was constructed by applying chemically inducible chromosomal evolution, replicon-free and markerless chromosomal integration as well as deletion of menaquinone biosynthetic pathway. The engineered E. coli TBW20134 produced 10.7 mg per gram of dry cell mass （DCM） of coenzyme Q10 when supplemented with 0.075 g·L^-1 of 4-hydroxy benzoic acid;this yield is unprecedented in E. coli and close to that of the commercial producer Agrobacterium tumefaciens. With this strain, the coenzyme Q10 production capacity was very stable after 30 sequential transfers and no antibiotics were required during the fermentation process. The strategy presented may be useful as a general approach for construction of stable production strains synthesizing natural products where various copy numbers for different genes are concerned.     

Consequence Identification for Maloperation in Batch Process

Batch processes are important in chemical industry, in which operators usually play a major role and hazards may arise by their inadvertent acts. In this paper, based on hazard and operability study and concept of qualitative simulation, an automatic method for adverse consequence identification for potential maloperation is proposed. The qualitative model for production process is expressed by a novel directed graph. Possible operation deviations from normal operating procedure are identified systematically by using a group of guidewords. The proposed algorithm is used for qualitative simulation of batch processes to identify the effects of maloperations. The method is illustrated with a simple batch process and a batch reaction process. The results show that batch processes can be simulated qualitatively and hazards can be identified for operating procedures including maloperations. After analysis for possible plant maloperations, some measures can be taken to avoid maloperations or reduce losses resulted from maloperations.     

考虑初始操作温度影响的间歇放热反应系统动态柔性分析

It is shown in this article that by changing the initial operation condition of the batch processes, the dynamic performance of the system can be varied largely, especially for the initial operational temperature of the exothermic reaction. The initial operation condition is often ignored in the designing batch processes for flexibility against disturbances or parameter variations. When the initial condition is not rigid as in the case of a batch reactor, where the initial reaction temperature is quite arbitrary, optimization can also be applied to determine the ＂best＂ initial condition to use. Problems for dynamic flexibility analysis of exothermic reaction including initial temperature and process operation can be formulated as dynamic optimization problems. Formulations are derived when the initial conditions are considered or not. When the initial conditions are considered, the initial condition can be transferred into control variables in the first optimal step. The solution of the dynamic optimization is on the basis of Rugge-Kutta integration algorithm and decomposition search algorithm. This method, as illustrated and tested with two highly nonlinear process problems, enables the determination of the optimal level. The dynamic performance is improved by the proposed method in the two exothermic reaction examples.     

一类连续/间歇过程的迭代学习模型预测控制

An iterative learning model predictive control (ILMPC) technique is applied to a class of continuous/batch processes. Such processes are characterized by the operations of batch processes generating periodic strong disturbances to the continuous processes and traditional regulatory controllers are unable to eliminate these periodic disturbances. ILMPC integrates the feature of iterative learning control (ILC) handling repetitive signal and the flexibility of model predictive control (MPC). By on-line monitoring the operation status of batch processes, an event-driven iterative learning algorithm for batch repetitive disturbances is initiated and the soft constraints are adjusted timely as the feasible region is away from the desired operating zone. The results of an industrial appli-cation show that the proposed ILMPC method is effective for a class of continuous/batch processes.     

生物燃料工厂的能源与水资源的优化(英文)

In this paper we address the topic of energy and water optimization in the production of bioethanol from corn and switchgrass. We show that in order for these manufacturing processes to be attractive, there is a need to go beyond traditional heat integration and water recycling techniques. Thus, we propose a strategy based on mathematical programming techniques to model and optimize the structure of the processes, and perform heat integration including the use of multi-effect distillation columns and integrated water networks to show that the energy efficiency and water consumption in bioethanol plants can be significantly improved. Specifically, under some circumstances energy can even be produced and the water consumption can be reduced below the values required for the production of gasoline.     

反应过程中的污染削减方法

To implement the strategy of pollution prevention in the development of reaction processes, studying the effects of reaction conditions such as temperature, pressure and concentration as well as various engineering factors, such as back- mixing, heat and mass transfer, on environmental performance of the reaction processes is very important. In this paper, potential environmental impact balance, proposed in the waste reduction algorithm, and PEI rate equation are recommended as a useful tool to be used to carry out this work. The application of the method is illustrated with the reaction of allyl chloride production.     

ZW多产品间歇过程调度及在线调整

针对多产品间歇过程调度提出了分层递阶的Petri网建模方法，利用赋时Petri和Petri网的简化技术描述不同层次的生产问题，具有很强的模型描述能力。另外，在调度决策层可以方便地集成优化策略和在线调整算法，使问题求解更加灵活。     

Scheduling of a mixed batch/continuous sugar milling plant using Petri nets

Scheduling of processes in mixed batch/continuous plants, due to their hybrid nature, can become very complex. This paper presents the Timed Hybrid Petri net (THPN) as a suitable tool for modelling and scheduling of hybrid systems. One of the major benefits over traditional methods is a significant reduction in complexity during problem formulation. A sugar milling plant containing both batch and continuous processing units is used to illustrate the application of the proposed scheduling algorithm.     

Petri-net based scheduling strategy for semiconductor manufacturing processes

Semiconductor manufacturing is a highly automated and capital-intensive industrial process. The operating cost of a wafer processing plant is in general closely related to the design and management of its process flows. Traditionally, the task of production scheduling is performed manually on the basis of past experiences. There are thus real incentives to develop a systematic approach to construct a mathematical programming model in order to reduce the chance of human errors and to ensure operational efficiency in implementing the resulting schedules. To this end, the Petri nets are adopted in this work to accurately model the semiconductor manufacturing activities. The token movements in a Petri net are represented with the well-established scheduling model for batch chemical processes, and the optimal schedule of the given semiconductor process can then be determined accordingly. The feasibility and effectiveness of this scheduling strategy is demonstrated in the present paper with three examples, i.e., the final test process, the re-entrant flow process, and the photolithography-etching process.     

基于核Fisher包络分析的间歇过程故障诊断

随着间歇过程越来越受重视,其过程监控和故障诊断技术也成为研究热点。以核Fisher判别分析为基础,提出了基于核Fisher的正常工况与故障包络面模型,给出了基于该模型的在线故障诊断流程。此方法利用了Fisher判别分析对类别的划分特点,分别针对正常工况数据和各故障类型数据建立包络曲面模型。与多向Fisher判别分析相比,该方法按批次方向将数据展开,能够解决生产周期不一致问题,在线故障诊断时也不需要预报完整的生产轨迹,并且加入核函数来处理复杂的非线性。最后在青霉素发酵过程的仿真平台上对该方法进行测试,与改进多向Fisher判别分析方法进行对比,该方法获得了满意的诊断效果：能够及早诊断出故障的发生,并在有效识别已有故障的同时还具有对新故障的自学习能力。     

基于TPN模型的间歇过程GA优化调度方法研究

为了建立间歇工业过程的优化调度策略,研究了采用TPN(赋时Petri网)建立其生产调度模型的方法,并提出了基于GA(遗传算法)对此TPN调度模型进行优化的技术。论文引入了一个青霉素发酵间歇过程的仿真平台,以此为实例对象,讨论了TPN调度建模及GA优化的具体步骤,给出了满意的优化调度计算结果。     

Optimal production sequence and processing schedules of multiproduct batch processes for heat integration and minimum equipment costs

The production sequence and the processing schedules of multiproduct batch processes can be changed for maximum heat recovery and minimum equipment costs between batch streams. However, the modified production sequence and processing schedule may increase the production cycle time, which causes the bigger equipment sizes required in batch processes. In this study, the required equipment sizes, the production sequence and the processing times of the multiproduct batch processes are mathematically formulated for maximum heat integration and low equipment costs in a mixed integer nonlinear programming. The optimal solution of this formulation was obtained by GAMS/DICOPT programming solver. Examples are presented to show the capabilities of the model.     

一种新的间歇过程故障诊断策略

间歇过程的在线故障诊断近年来受到了越来越多的关注,目前比较通用的方法主要是多变量统计的方法。然而在实际过程尤其是多阶段的间歇过程中故障诊断效果往往不够理想,误诊率比较高。为解决上述问题,本文基于动态轨迹分析（DLA）和在线的动态时间规整方法（DTW）,将二者的优点有效地结合在一起提出了一种在线故障诊断策略,提高了故障诊断效率和准确性。青霉素发酵过程的在线故障诊断应用实例表明该方法具有比较好的诊断效果。     

基于图模型的间歇过程误操作风险辨识

提出了一套基于图模型的建模方法,该模型以Petri网和符号有向图（SDG）为基础将模型分为上部和下部,加入操作点、控制库所、判断模块等模型元素,并结合间歇过程的特点,提出了关联变量、目标变量检查表、操作点检查表和关联变量检查表等概念。根据误开误关、过早过晚、步骤添加删除等误操作,对模型进行验证。验证结果表明,该模型解决了先前方法难以描述具体操作的缺陷,并且模型结构简单,具有整体性。不仅能够方便地描述3种不同类型的误操作,还能有效地对误操作进行风险辨识,具有一定的适用性。     

Quality‐relevant fault diagnosis with concurrent phase partition and analysis of relative changes for multiphase batch processes

Multiplicity of phases as indicated by changes of process characteristics is an inherent nature of many batch processes for both normal and fault cases. To more efficiently perform online fault diagnosis via reconstruction for multiphase batch processes, the phase nature and the relationship between normal and fault cases within each phase should be deeply addressed. This article proposes a quality‐relevant fault diagnosis strategy with concurrent phase partition and analysis of relative changes for multiphase batch processes. First, a concurrent phase partition algorithm is developed. The basic idea is to track the changes of process characteristics at normal and fault statuses jointly so that multiple sequential modeling phases are identified simultaneously for both normal and fault cases. Then, the relative changes from the normal status to each fault case are analyzed in each phase to reveal the specific fault effects more efficiently. The fault effects are decomposed in two different monitoring subspaces, principal subspace, and residual subspace, by capturing their different roles in removing out‐of‐control signals. The significant increases relative to the normal case are judged to be responsible for the concerned alarm monitoring statistics in each phase. The others are composed of general variations that are deemed to still follow normal rules and thus insignificant to remove alarm monitoring statistics. Those alarm‐responsible fault deviations are then used to develop reconstruction models which can more efficiently recover the fault‐free part for online fault diagnosis. The proposed algorithm is illustrated with a typical multiphase batch process with one normal case and three fault cases. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2048–2062, 2014     

一种不等长的多模态间歇过程故障检测方法

提出一种不等长的多模态间歇过程故障检测方法。首先,运用局部加权算法对不等长批次数据进行预处理。在训练样本中确定不等长数据的最大可保留长度,利用k近邻信息,通过加权重构出不等长批次缺失的数据点。其次,对等长的训练集构造局部近邻标准化矩阵,运用K-means算法进行模态聚类,使用局部离群因子方法确定第一控制限,并剔除离群样本。最后,对各个模态建立MPCA模型并确定第二控制限。根据各个模态控制限的匹配系数计算统一的统计量和控制限,在统一的控制限下进行多模态故障检测。将提出方法应用于半导体工业过程,仿真结果表明,与传统的故障检测算法相比,本文算法提高了故障检测率,验证了该方法的有效性。