间歇过程的故障分析和互锁控制器综合的集成

Integration amongst various decision-making processes, such as planning, design, and operation is necessary to dynamic and flexible batch production. To achieve a batch production integration, utilization of common models used for various decision-making processes is an effective approach. From this point of view, a batch system common model as described by a Petri net is proposed. In this article, a fault diagnosis technique for batch processes is presented using information about fault propagation and the possibilities of integration of fault analysis and controller synthesis are discussed on the basis of the Petri net based common models.     

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.     

基于改进多模型FDA的间歇生产过程的故障诊断

1 INTRODUCTION In recent decades, batch processes have been a wide concern in the chemical fields because of their low-volume, high-value products and capabilities of easily tracking changing market situations. Therefore, it is necessary to monitor them in order to ensure safe, decrease the production costs and enhance the quality of products. Batch processes are characterized by the precise sequencing and automation of all stages in the sequence. They convert raw materials into products …     

在线自适应批次过程监视的双滑动窗口MPCA方法

Online monitoring of chemical process performance is extremely important to ensure the safety of a chemical plant and consistently high quality of products. Multivariate statistical process control has found wide applications in process performance analysis, monitoring and fault diagnosis using existing rich historical database. In this paper, we propose a simple and straight forward multivariate statistical modeling based on a moving window MPCA （multiway principal component analysis） model along the time and batch axis for adaptive monitoring the progress of batch processes in real-time. It is an extension to minimum window MPCA and traditional MPCA. The moving window MPCA along the batch axis can copy seamlessly with variable run length and does not need to estimate any deviations of the ongoing batch from the average trajectories. It replaces an invariant fixed-model monitoring approach with adaptive updating model data structure within batch-to-batch, which overcomes the changing operation condition and slows time-varying behaviors of industrial processes. The software based on moving window MPCA has been successfully applied to the industrial polymerization reactor of polyvinyl chloride （PVC） process in the Jinxi Chemical Company of China since 1999.     

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.     

间歇生产过程鲁棒统计监控及其应用

In order to reduce the variations of the product quality in batch processes, multivariate statistical process control methods according to multi-way principal component analysis (MPCA) or multi-way projection to latent structure (MPLS) were proposed for on-line batch process monitoring. However, they are based on the decomposition of relative covariance matrix and strongly affected by outlying observations. In this paper, in view of an efficient projection pursuit algorithm, a robust statistical batch process monitoring (RSBPM) framework, which is resistant to outliers, is proposed to reduce the high demand for modeling data. The construction of robust normal operating condition model and robust control limits are discussed in detail. It is evaluated on monitoring an industrial streptomycin fermentation process and compared with the conventional MPCA. The results show that the RSBPM framework is resistant to possible outliers and the robustness is confirmed.     

A Robust Statistical Batch Process Monitoring Framework and Its Application

In order to reduce the variations of the product quality in batch processes, multivariate statistical process control methods according to multi-way principal component analysis (MPCA) or multi-way projection to latent structure (MPLS) were proposed for on-line batch process monitoring. However, they are based on the decomposition of relative covariance matrix and strongly affected by outlying observations. In this paper, in view of an efficient projection pursuit algorithm, a robust statistical batch process monitoring (RSBPM) framework, which is resistant to outliers, is proposed to reduce the high demand for modeling data. The construction of robust normal operating condition model and robust control limits are discussed in detail. It is evaluated on monitoring an industrial streptomycin fermentation process and compared with the conventional MPCA. The results show that the RSBPM framework is resistant to possible outliers and the robustness is confirmed.     

石化MES中的物流建模技术及其应用

The management and control of material flow forms the core of manufacturing execution systems （MES） in the petrochemical industry. The bottleneck in the application of MES is the ability to match the material-flow model with the production processes. A dynamic material-flow model is proposed in this paper after an analysis of the material-flow characteristics of the production process in a petrochemical industry. The main material-flow events are described, including the movement, storage, shifting, recycling, and elimination of the materials. The spatial and temporal characters of the material-flow events are described, and the material-flow model is constructed. The dynamic material-flow model introduced herein is the basis for other subsystems in the MES. In addition, it is the subsystem with the least scale in MES. The dynamic-modeling method of material flow has been applied in the development of the SinoMES model. It helps the petrochemical plant to manage the entire flow information related to tanks and equipments from the aspects of measurement, storage, movement, and the remaining balance of the material. As a result, it matches the production process by error elimination and data reconciliation. In addition, it facilitates the integration of application modules into the MES and guarantees the potential development of SinoMES in future applications.     

基于支持向量机MPLS的间歇过程故障诊断方法

1 INTRODUCTION In batch or fed-batch processes, raw materials are converted to products within a finite duration. In prac- tical production, the process commonly exhibits large variations from batch to batch due to such influencing factors as the quality fluctuation of raw materials, de- fect of equipments, contaminations, and other unpre- dicted disturbances. These variations may have an adverse effect on the final product quantity and quality. But it is generally difficult to discern th…     

Cultivation of microalgae for biodiesel production: A review on upstream and downstream processing

Fluctuating market price of fossil fuel and overwhelming emission of greenhouse gases to the atmosphere have resulted in climate change and have been a global concern in this decade.Hence,biodiesel has become an alternative option to fossil diesel as it is renewable and environmentally friendly.Nevertheless,this alternative fuel that is usually derived from terrestrial oil crops will cause shortage in food supply and deforestation if mass production is realized.In recent years,cultivation of aquatic microorganism (particularly microalgae) to produce biodiesel is considered as a practical solution due to their high growth rate and ability to synthesize large quantity of lipid within their cell.However,the development of energy and cost-efficiency of microalgae cultivation system are the main issues in producing renewable microalgae biodiesel.Of late,wastewater or organic compost has been used as the cultivation medium as it can provide sufficient nutrients to sustain microalgae growth.Microalgae cultivation method and system are vitally important as these factors undoubtedly affect the final microalgae biomass and lipid yield.In this review,the cultivation system of microalgae,nutrients demanded for microalgae production,cell harvesting and drying,microalgae oil extraction,and utilization of microalgae biomass for biodiesel production are introduced and discussed.It is anticipated to convey clearer perspectives in upstream and downstream processes in microalgae-derived biodiesel production.     

应用Aspen Batch对年产25吨鲁拉西酮原料药工艺设计优化

采取专利CN 102863437 A的工艺,设计间歇工艺过程,将Aspen Batch Process Developer软件应用于盐酸鲁拉西酮原料药车间设计的全流程模拟和优化。间歇操作具有显著的优势：生产灵活,同一设备可生产不同产品,可根据市场需要调节生产能力及变更产品。适合于小批量,高收益的精细化学品。过去的四十年里,使用计算机对化工连续化生产进行模拟和设计已经十分普及。制药工业与传统化工最大的区别是生产过程多采用间歇法操作。目前世界上应用于化工间歇生产的计算机软件有BATCHES、gPROMS和Aspen Batch Process Developer。本文所用版本为Aspen Tech V8.6,以年产25t盐酸鲁拉西酮原料药车间为例,对车间进行全流程模拟及优化。整个设计贯彻质量源于设计理念,运用元葱模型,将盐酸鲁拉西酮的生产工艺分为磺化、氨解、氢化、缩合、成盐、精烘包等6个模块。     

Anfahr- und Betriebsverhalten von exothermen Batch-Prozessen

Start-up and operation of exothermic batch processes . A survey of the general characteristics of batchwise chemical production processes shows that the possibilities of complete prediction of optimum production tactics are limited. Thus recourse is taken to simplified semi-empirical design procedures. It is demonstrated in the case of exothermic batch processes with indirect cooling that criteria can be given as to whether this production strategy is technically feasible. Given technical feasibility, these criteria can be used for design of a safe start-up and operating behaviour. The procedure is illustrated for two applications.     

多目标零等待间歇生产过程多任务调度

间歇生产过程已经成为化工生产制造技术的基础和关键,该过程生产出大量产品来满足日常生活需要。然而经济全球化使得传统的化工生产过程产业面临严重的挑战。为了保持竞争力,每个企业必须优化生产技术,加强管理。其中调度是化工企业生产管理的核心技术。针对化工过程自身的多目标和零等待等特性,研究了间歇生产过程中的多目标零等待多任务调度,并提出该问题的模型和优化方法。通过将该问题分解成两个子问题来解决：采用非延迟非秩序混合方法来解决时间表分配问题以及用带存储的完全局部搜索解决排序问题。此外多目标占优采用基于SPEA2中的策略。通过大量算例的仿真实验证明了该算法的可行性和有效性。     

Demonstrating multi-objective screening of chemical batch process alternatives during early design phases

One of the key challenges for the design of sustainable chemical processes is to incorporate such concepts in the early phases of process design. In recent years, a few frameworks have been published to this direction, focusing mainly on continuous processes. However, the wide use of batch processes for the production of “low volume high value” chemicals makes the extension of such frameworks to this production environment indispensable. In the present study a recently presented multi-stage framework for multi-objective continuous process assessment is modified to incorporate batch process design aspects (e.g., cycle times, equipment utilization) in the form of early design phase indicators. Accordingly, a Productivity Loss Index (PLI) is defined for estimating periodic costs and environmental impacts, economic and environmental indicators are adjusted and a procedure to generate a base case separation process flowsheet is implemented. The modified framework is demonstrated on the design of a production process for 4-(2-methoxyethyl)-phenol considering seven potential synthesis routes.     

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.     

Regularization‐based statistical batch process modeling for final product quality prediction

Prediction accuracy and model interpretation are two important aspects with regard to regression models. In the field of statistical modeling of chemical batch processes, most research focuses on prediction accuracy, while the importance of the latter aspect is often overlooked. In multiphase batch processes, it is possible that only a few phases are relevant to certain quality indices, while different time points belonging to the same relevant phase usually have similar contribution to the quality. The regression coefficients of batch process model should reflect such process characteristics, that is, the coefficients corresponding to the irrelevant phases should be close to zero, while the coefficients of each variable within the same phase should vary smoothly. In this study, regularization techniques are introduced to statistical modeling of chemical batch processes to achieve both accurate prediction and good interpretation. The application to an injection molding process shows the feasibility of the proposed methods. © 2014 American Institute of Chemical Engineers AIChE J, 60: 2815–2827, 2014     

OPTIMAL DESIGN AND OPERATION OF BATCH PROCESSES

The economical design of continuous chemical processes to produce commodity products has reached an advanced state of development. Modern computer tools are used routinely to simulate and optimize these processes. This is not the case, however, for the manufacture of speciality products which must be made in batch operations. The continuing shift towards the production of higher value-added specialty products by the CPI has stimulated efforts aimed at developing good computer assisted design strategies for batch processes.

This paper discusses the formulation of the problem for the optimal design and operation of batch processes. The batch problem differs from the continuous one in a number of important ways. First, batch plants do not operate at steady state. There are important trade-offs between the processing time and the severity (intensity) of processing in single units. Cycle time and performance trade-offs also exist among the various units in the process. Second, batch plants produce multiple products in many cases. There is often a competition for shared resources (labor, utilities, and equipment) among the various products. This paper presents a hierarchical solution approach for the design and optimization of a batch process. The approach is demonstrated by solving an example problem which illustrates the fundamental economic trade-offs.     

Kontinuierliche Produktion von Sophoroselipiden mit Candida bombicola ATCC 22214

Continuous production of sophoroselipids by Candida bombicola ATCC 22214. The production of sophoroselipids with Candida hombkola from renewable carbon sources has been well investigated for some years. Nevertheless, most publications deal with batch or md batch fermentations. Up to now investigations about the continuous production are very rarely to find. Latest results show, that high productivities can be reached in continuous culture which is a serious alternative to the existing non-continuous processes. In this paper common methods producing sophoroselipids are compared to continuous production processes.