Chemometrical approach in studies of membrane capacity in pulp and paper mill application

In the pulp and paper mill membrane filtration applications the volumes of processed water are huge. Due to this high and stable capacity of the membrane is required. Since the membrane capacity is a result of many different factors, finding the most suitable membrane for a certain application usually needs a considerable number of experiments, which produces huge amounts of experimental results. Traditionally experimental filtration results are examined with univariable methods. The univariable examination is time-consuming and, due to the multivariate nature of the filtration phenomena, univariable examination cannot show effectively the correlation structure between the variables in the filtration system. Thus, multivariate examination methods are needed for obtaining well-defined information about membrane performance in a certain application. In this study the experimental results from a pilot-scale paper mill filtration application were examined with multivariate methods principal component analysis (PCA) and parallel factor analysis (PARAFAC). Both methods revealed crucial information about the membrane, which was not obtained when univariable examination was used. The methods tested were evaluated to be very effective tools in the examination of membrane filtration results.     

Analyses of organic foulants in membranes fouled by pulp and paper mill effluent using solid-liquid extraction

Fouling of membranes is a serious problem in membrane technology. By characterizing the foulants in membranes it is possible to understand fouling and reduce it. However, the characterization of foulants, especially organic ones, is difficult. The purpose of this study was to find out whether there are any organic foulants such as extractives in the membranes, and if it is possible to identify them. Membranes of different materials and hydrophilicity were used in filtration of ground wood mill (GWM) circulation water during one month in an integrated pulp and paper mill, Solid—liquid extraction was employed to remove the extractives from the membranes and the characterization of them was carried out with a gas chromatograph. According to the results, there are extractives in the membranes and it is possible to characterize them. It seems that the fouling by extractives mainly comes from resin and fatty acids. In addition, some traces of lignans were found in the membranes. Moreover, the hydrophobic membranes contained more of these acids and lignans than the hydrophilic membranes.     

Multistage distributionally robust optimization for integrated production and maintenance scheduling

In chemical manufacturing processes, equipment degradation can have a significant impact on process performance or cause unit failures that result in considerable downtime. Hence, maintenance planning is an important consideration, and there have been increased efforts in scheduling production and maintenance operations jointly. In this context, one major challenge is the inherent uncertainty in predictive equipment health models. In particular, the probability distribution associated with the stochasticity in such models is often difficult to estimate and hence not known exactly. In this work, we apply a distributionally robust optimization (DRO) approach to address this problem. Specifically, the proposed formulation optimizes the worst-case expected outcome with respect to a Wasserstein ambiguity set, and we apply a decision rule approach that allows multistage mixed-integer recourse. Computational experiments, including a real-world industrial case study, are conducted, where the results demonstrate the significant benefits from binary recourse and DRO in terms of solution quality.     

Effect of physico-chemical conditions on the properties of zeolite microparticles used in pulp and paper applications

Zeolites are framework aluminosilicates that have been proposed as a replacement for bentonite in microparticle retention systems. It has been claimed in many patents that zeolite can improve sheet formation in fine paper manufacturing. However, this improvement was not observed in mechanical grades. These experimental results, and also theoretical evidence, suggest that papermaking pH plays an important role in zeolite efficiency. In consequence, the effect of pH and temperature on the chemical properties of zeolite and bentonite microparticles was determined. Streaming potential, conductivity, and pH were measured while microparticle solutions were gradually acidified to pH 5. Samples were also taken at specific pH values to measure the cationic demand. Results showed that a gradual reduction of pH caused several modifications to zeolites. The first step was the neutralization of free hydroxyl ions in solution. The second step was an irreversible exchange of the charge-compensating sodium ions by hydrogen ions on the inner and outer surface of microparticles. Finally, dealumination of the zeolites occurred. It was determined that neutralization must be completed before ion-exchange can begin. However, ion-exchange and dealumination occurred simultaneously. Between pH 7.5 and 9, zeolites had more anionic sites than bentonite (around 0.8 meq/g vs. 0.5 meq/g). The higher surface charge of zeolites might partly explain their efficiency in microparticle systems. On the other hand, under pH 7.5, the anionic charge of zeolite samples rapidly decreased while that of bentonite was stable. The effect of temperature was also studied in the 25 to 55 °C range. Generally, a temperature rise promoted a greater dissociation of the surface hydroxyl groups and an acceleration of ion-exchange and dealumination processes.     

磷化工技术评价决策支持系统开发

根据决策支持系统理论,以微软SQL Server 2005数据库管理开发系统软件和J2EE技术为开发工具,构建了磷化工技术评价决策支持系统。描述了该系统构建的基本框架、流程、功能和运行步骤,并提供了电炉制黄磷工艺实例。该系统将为磷化工技术评价提供辅助决策和评判功能。     

磷化工经济评价决策支持系统的研究与开发

将决策支持系统(DSS)应用于磷化工产业的经济评价对其科学决策和降低投资失误有重要意义,本文介绍了磷化工决策支持系统总体结构设计和模式,论述了经济评价决策支持系统在新建磷化工项目中的实现过程,并以热法磷酸工艺为例展现其功能.     

Multi-bucket optimization for integrated planning and scheduling in the perishable dairy supply chain

This paper considers a dairy industry problem on integrated planning and scheduling of set yoghurt production. A mixed integer linear programming formulation is introduced to integrate tactical and operational decisions and a heuristic approach is proposed to decompose time buckets of the decisions. The decomposition heuristic improves computational efficiency by solving big bucket planning and small bucket scheduling problems. Further, mixed integer linear programming and constraint programming methodologies are combined with the algorithm to show their complementary strengths. Numerical studies using illustrative data with high demand granularity (i.e., a large number of small-sized customer orders) demonstrate that the proposed decomposition heuristic has consistent results minimizing the total cost (i.e., on average 8.75% gap with the best lower bound value found by MILP) and, the developed hybrid approach is capable of solving real sized instances within a reasonable amount of time (i.e., on average 92% faster than MILP in CPU time).     

Iterative optimization of the economic efficiency of an industrial process within the validity area of the static plant model and its application to a Pulp Mill

Optimization of the steady state economic efficiency of an industrial process is a specific task because the decision variables of the optimization (setpoints of the control system) affect the process through the control strategy. Thus, the effects of saturation of a control system must be taken into account when the gradient of the objective function is estimated and the necessary optimality conditions are checked. In particular, because the optimality conditions cannot be checked directly in the presence of active constraints on the manipulated variables, approximations of the steady state values of the manipulated variables as functions of the setpoints (static plant model) are needed in order to be able to evaluate the optimality conditions. In this paper an iterative method for optimization of the plant profit rate is proposed avoiding the control saturation and is applied to the Pulp Mill benchmark model optimization. Three different static models describing the steady state values of the manipulated variables are constructed and used in the optimization. The results of the optimization are presented and compared against the straightforward single-step optimization of the plant economic efficiency.     

A genetic‐algorithm‐based optimal scheduling system for full‐filled tanks in the processing of starting materials for alumina production

Due to the instability of mine sources and the uncertainty of the composition of returned lye and waste liquid, there exists a significant fluctuation of raw slurry quality in the blending process of starting materials for sintering. The expected slurry was obtained through the mixing of starting materials in full‐filled tanks. In this article, an optimal scheduling model of full‐filled tanks is developed based on material balance principle and expert experiences subject to technological requirements. To solve such optimization problem, an improved genetic algorithm (IGA) is proposed, in which the intervention strategy is introduced into the random process of population initialization to obtain the well‐proportioned initial population and the probabilities of crossover and mutation are changed according to the difference between the fitness value of the best solution and the average fitness value of the better solutions as well as the difference between the fitness value of the best solution and the average fitness value of the current population to prevent premature convergence. The IGA‐based optimization system was applied to the processing of raw slurry for alumina production and the actual running results show that the composition fluctuation in mixed raw slurry decreased significantly, effectively improving the eligibility rate of the mixed raw slurry and contributing to the stabilization of the subsequent process of alumina production.     

Emerging Biodrying Technology for the Drying of Pulp and Paper Mixed Sludges

Effective sludge management is increasingly critical for pulp and paper mills due to high landfill costs and complex regulatory frameworks for options such as sludge landspreading and composting. Sludge dewatering challenges are exacerbated at many mills due to improved in-plant fiber recovery coupled with increased production of secondary sludge, leading to a mixed sludge with a high proportion of biological matter that is difficult to dewater. Various drying technologies have emerged to address this challenge of sludge management, whose objective is to increase the dryness of mixed sludge to above critical levels (≈42% dryness) for efficient and economic combustion in the boiler for steam generation. The advantages and disadvantages of these technologies are reviewed in this article, and it is found that many have significant technical uncertainties and/or questionable economics. A biodrying process, enhanced by biological heat generation under forced aeration, is introduced that has significant promise. A techno-economic analysis of the batch biodrying process at a case study mill showed an annual operating cost savings of about $2 million, including the elimination of landfilling practices and supplemental fuel requirements in the boiler. It was shown that if a biodrying residence time of less than 4 days can be achieved, payback periods of 2 years or less can result in many mills. The potential for the development of a continuous biodrying reactor and the fundamentals of its mathematical modeling are thus presented. Compared to the batch reactor configuration, it is expected that the continuous process would result in improved process flexibility and controllability, lower investment and operating costs due to shorter residence times, and an improved potential to fit into the crowed pulp and paper mill site.     

Emerging Biodrying Technology for the Drying of Pulp and Paper Mixed Sludges

Effective sludge management is increasingly critical for pulp and paper mills due to high landfill costs and complex regulatory frameworks for options such as sludge landspreading and composting. Sludge dewatering challenges are exacerbated at many mills due to improved in-plant fiber recovery coupled with increased production of secondary sludge, leading to a mixed sludge with a high proportion of biological matter that is difficult to dewater. Various drying technologies have emerged to address this challenge of sludge management, whose objective is to increase the dryness of mixed sludge to above critical levels (≈42% dryness) for efficient and economic combustion in the boiler for steam generation. The advantages and disadvantages of these technologies are reviewed in this article, and it is found that many have significant technical uncertainties and/or questionable economics. A biodrying process, enhanced by biological heat generation under forced aeration, is introduced that has significant promise. A techno-economic analysis of the batch biodrying process at a case study mill showed an annual operating cost savings of about $2 million, including the elimination of landfilling practices and supplemental fuel requirements in the boiler. It was shown that if a biodrying residence time of less than 4 days can be achieved, payback periods of 2 years or less can result in many mills. The potential for the development of a continuous biodrying reactor and the fundamentals of its mathematical modeling are thus presented. Compared to the batch reactor configuration, it is expected that the continuous process would result in improved process flexibility and controllability, lower investment and operating costs due to shorter residence times, and an improved potential to fit into the crowed pulp and paper mill site.     

多因素生产分析决策模型及在矿山提升系统中的应用

应用灰色系统GM(1,2)理论对某矿山企业提升系统中一个阶段的生产状况进行了分析,根据实际情况对其进行改进,建立了一种结合改进GM(1,2)理论和控制论相关知识的综合模型,给出了该模型建立过程及其在该企业生产决策中的应用方法,这一模型可普遍用于企业多因素生产状况分析,从而拓宽了灰色系统的应用范围.     

水泥联合粉磨系统提产降耗措施

我公司有3台水泥磨系统,由于投建时间较长,磨机运行状况较差,能耗高于行业均值。为了提高磨机运行效率,降低能耗,公司对三号磨机辊压机预粉磨系统及磨机系统进行了改造,在不增加新设备的前提下,通过优化工艺布局及工艺参数,最终实现了提高磨机台时,降低能耗的目标。     

不确定条件下炼化企业计划与调度整合策略

A strategy for the integration of production planning and scheduling in refineries is proposed.This strategy relies on rolling horizon strategy and a two-level decomposition strategy.This strategy involves an upper level multiperiod mixed integer linear programming(MILP) model and a lower level simulation system,which is extended from our previous framework for short-term scheduling problems [Luo,C.P.,Rong,G.,"Hierarchical approach for short-term scheduling in refineries",Ind.Eng.Chem.Res.,46,3656-3668(2007)].The main purpose of this extended framework is to reduce the number of variables and the size of the optimization model and,to quickly find the optimal solution for the integrated planning/scheduling problem in refineries.Uncertainties are also considered in this article.An integrated robust optimization approach is introduced to cope with uncertain parameters with both continuous and discrete probability distribution.     

PVC全自动包装生产线控制系统故障分析及处理措施

介绍了PVC包装用全自动包装生产线的特点和工艺流程,分析了控制系统常见故障,并提出了解决方法。     

A general modular framework for the integrated optimal management of an industrial gases supply-chain and its production systems

A general modular methodology for the simultaneous optimization of the supply-chain network and the production systems of a general industrial gas producer is developed and implemented in a C++ program. The formulation and solution algorithm are specifically designed to be able to work on-line and to determine the optimal assignments of production site output to customer demand in the supply-chain and the corresponding optimal operating conditions for the production plants in integrated fashion. Here, the production network is not simply modelled as a set of product sources, rather the model is detailed enough to allow effective and feasible optimization of the entire system. Moreover, the proposed approach can be easily combined with the rolling horizon technique to mitigate the uncertainties in demand. The modelling strategies, employed for the supply-chain network and the production sites, along with the solution approach, adopted for the resulting optimization problem, are detailed. BzzMath library classes are used to meet the computational efficiency requirements for on-line applications. The effectiveness of the proposed methodology is demonstrated on a case study involving a portion of the real supply-chain and network of production facilities of Linde Gas Italia S.r.l.