A heuristic design method for batch water-using networks of multiple contaminants with regeneration unit

This work develops a heuristic method for the design of batch water-using networks of multiple contaminants with regeneration unit based on the concepts of concentration potential. A water-using network involving regeneration unit can be formed by adding the regenerated stream(s) into the network involving reuse only. In the design procedure of the network operated in a single batch mode, time is taken as the primary factor and concentration potentials as the secondary one. For the networks operated in a repeated mode, the design procedure is similar to that for continuous processes, besides designing the storage tanks with the rules proposed. Continuous regeneration unit is selected in this work. With the proposed method, the network structure corresponding to the minimum freshwater consumption can be obtained. It is shown that the method proposed in this article is simple, effective and has clear engineering meaning.     

A two-stage approach for the synthesis of inter-plant water networks involving continuous and batch units

This paper presents a mathematical optimization model for inter-plant water network (IPWN) synthesis, where process units operate in mixed continuous and batch modes. The current developed model consists of a two-stage approach, and is dedicated to the special case where there are more continuous than batch units. In the first stage, all batch units are treated as continuous units by using auxiliary water storage tanks, and a continuously operated IPWN is synthesized to minimize the fresh water consumption. Subject to the determined IPWN flow rates, the water storage policy for the batch units is determined in the second stage to minimize the total storage capacity. Alternatively, the formulations of both stages can be combined and solved simultaneously to minimize the IPWN cost. Two modified literature examples are used to illustrate the proposed approach.     

MILP-based initialization strategies for the optimal design of water-using networks

The optimal design of water-using systems involves necessarily the exploitation of all possible water reuse and recycling alternatives. The general problem can be formulated as a non-convex nonlinear program (NLP), but due to the presence of bilinear terms, it may be difficult for local optimization solvers to attain global optimal solutions. To overcome this difficulty, this paper presents two mixed integer linear programming (MILP)-based procedures to generate a few structurally different starting points for the NLP. In both, the problem is decomposed into calculation stages by assuming that the water streams progress in series through the water-using units, with the binary variables selecting which unit belongs to a certain stage. Their main difference concerns the way fixed flowrate units are handled, either separately or in conjunction with a fixed load operation, since the former comprise a linear subsystem. The two algorithms are compared to a closely related LP-based method taken from the literature and to the one employed by the global optimization solver BARON. The results from a large set of example problems confirm their effectiveness in avoiding local solutions despite the small number of starting points. In contrast to the previous method they are easily scalable and, for some of the larger problems, could find better solutions than BARON with significantly fewer computational resources. The results have also shown that the option of tackling one unit at a time is the most favorable.     

Multiobjective batch process design aiming at robust performances

The most common batch design approach in practice and literature is a deterministic one. However, given the uncertainties prevailing in early stages of process design, a deterministically calculated productivity is not sufficient to select one of the large number of optional designs. Therefore, we propose a Tabu Search multiobjective optimization framework, which allows to approximate the Pareto-optimal set of designs while considering uncertain variables in the initial recipe. As a novel technique, we include performance robustness as a separate objective function within the multiobjective optimization alongside with productivity of a design, thus obtaining not only designs with high productivity or solely robust designs, but both high productivity and robust designs in one set of solutions. We examined several robustness criteria as a possible quantification of performance deviations under uncertain recipe variables. The implementation of a Tabu Search framework in combination with Monte-Carlo simulation and Latin Hypercube sampling provides a huge flexibility in the problem specification, in particular in the definition of parameter uncertainties. As a result we successfully demonstrate that metaheuristic optimization techniques are capable to approximate the Pareto-optimal set under uncertainty and are able to capture potentially antagonistic solution qualities such as high productivity and robustness by multiobjective optimization. With the help of this approach, parameters can be identified that have to be put into the focus of process research and development efforts in order to obtain high performance batch process designs.     

Mathematical modeling for simultaneous design of plants and supply chain in the batch process industry

Most supply chain design models have focused on the integration problem, where links among nodes must be settled in order to allow an efficient operation of the whole system. At this level, all the problem elements are modeled like black boxes, and the optimal solution determines the nodes allocation and their capacity, and links among nodes. In this work, a new approach is proposed where decisions about plant design are simultaneously made with operational and planning decisions on the supply chain. Thus, tradeoffs between the plant structure and the network design are assessed. The model considers unit duplications and the allocation of storage tanks for plant design. Using different sets of discrete sizes for batch units and tanks, a mixed integer linear programming model (MILP) is attained. The proposed formulation is compared with other non-integrated approaches in order to illustrate the advantages of the presented simultaneous approach.     

间歇化工过程热集成研究进展

间歇化工过程热集成问题的研究能够促进过程系统的可持续发展并且提高产业经济性和技术竞争力,顺应了化工发展大环境。本文介绍了以系统综合优化为目标的间歇化工过程热集成研究的发展现状,整理了早期研究的三大通用图解模型,并讨论和比较了在建模求解过程中常见算法。总结了当前研究的重点在换热网络设计优化、热储罐系统和考虑调度的热集成三个方面,并评述了与之相关的进展、瓶颈和研究意义。指出了热集成问题已成为当前间歇化工过程的研究热点,其中热集成和生产调度的协同优化十分必要,能够从系统全局的角度上给出优化方案。但由于间歇化工过程中存在较多的不确定性和约束条件,增加了热集成的研究难度,因此对间歇化工过程优化设计提出了更高的要求。     

A model-based control framework for industrial batch crystallization processes

Dynamic optimization is applied for throughput maximization of a semi-industrial batch crystallization process. The control strategy is based on a non-linear moment model. The dynamic model, consisting of a set of differential and algebraic equations, is optimized using the simultaneous optimization approach in which all the state and input trajectories are parameterized. The resulting problem is subsequently solved by a non-linear programming algorithm.     

Optimal design of batch mass exchange networks with multipurpose exchange units

A novel mathematical model for simultaneous optimization of batch mass exchange networks with multipurpose mass exchange units that can be shared by more than one match in different periods is presented in this work. It can be shown that both utility cost and capital investment can be reduced simultaneously with the use of multipurpose mass exchangers and mass storage tanks. Specifically, state-space superstructure that does not contain any structural simplification is proposed to capture the entire characteristics of the network configuration and a mixed-integer nonlinear optimization model is then formulated accordingly to generate the optimal batch operating policies and the corresponding flowsheet. Two examples are presented in this paper to demonstrate the validity and advantages of the proposed approach.     

Development of a batch manager for dynamic scheduling and process management in multiproduct batch processes

A batch manager is developed for the dynamic scheduling and on-line management of process operations. The developed system consists of a process monitoring module and a dynamic scheduling module. When a deviation from the initial schedule is detected in a process monitoring module, dynamic scheduling is performed in the dynamic scheduling module and the initial schedule is adjusted to the proper schedule by using rescheduling algorithms presented in this paper. The adjusted schedule is shown in the process monitoring module. The dynamic scheduler in the batch manager copes with several unexpected process events of batch process operations by adjusting the EST (Earliest Start Time) of equipment, redetermining the batch path and reassigning tasks to equipment. This study focuses on the implementation of a batch manager with on-line dynamic scheduling for batch process management. Examples of fodder production batch processes illustrate the efficiency of the algorithms. This paper was supported by nondirected research fund, Korea Research Foundation, 1997.     

A unified graphical method for integration of hydrogen networks with purification reuse

Introducing purifiers into hydrogen network can enhance the recovery and reuse of hydrogen in refineries, further reducing the consumption of fresh hydrogen. Based on previous graphical methods, this work proposes a simple and unified graphical method for integration of hydrogen networks with purification processes. Scenarios with different hydrogen concentrations of purified product can be analyzed by the unified procedure. As a result, the maximum hydrogen saved by purification reuse can be identified and the corresponding purification process can be optimized. The proposed method is easy and non-iterative, and it is valid to purification processes with any feed concentration. A conventional hydrogen network is analyzed to test the effectiveness of the proposed method.     

最佳间歇水循环网络的合成和时序安排

This work develops an optimization-based methodology for the design and scheduling of batch water recycle networks. This task requires the identification of network configuration, fresh-water usage, recycle assignments from sources to sinks, wastewater discharge, and a scheduling scheme. A new source-tank-sink representation is developed to allow for storage and dispatch tanks. The problem is solved in stages by first eliminating scheduling constraints and determining minimum usage of fresh water and wastewater discharge. An iterative procedure is formulated to minimize the total annual cost of the system by trading off capital versus operating costs. The work overcomes limitations in previous literature work including restricted recycle within the same cycle, lumped balances that may not lead to feasible solutions, and unrealistic objective functions. A case study is solved to illustrate the usefulness of the devised procedure.     

Robustness of reinforced gradient-type iterative learning control for batch processes with Gaussian noise☆

In this paper, a reinforced gradient-type iterative learning control profile is proposed by making use of system matrices and a proper learning step to improve the tracking performance of batch processes disturbed by exter-nal Gaussian white noise. The robustness is analyzed and the range of the step is specified by means of statistical technique and matrix theory. Compared with the conventional one, the proposed algorithm is more efficient to resist external noise. Numerical simulations of an injection molding process il ustrate that the proposed scheme is feasible and effective.     

Synthesis of mass exchange network for batch processes—Part II: Minimum units target and batch network design

The first part of this series of papers (Chem. Eng. Sci. 59(5) (2004) 1009) presented a methodology for identifying the minimum utility targets for a mass exchange network (MEN) for a batch process. This paper describes the methodology for setting the minimum number of mass exchange units target and a procedure for designing a maximum mass recovery network that features the minimum utility targets. The time-grid diagram and the overall time-grid diagram that include the time dimension in network design have been introduced to provide a better representation of the mass exchange network for a batch process. The systematic network design procedure also includes a technique to simplify and evolve the preliminary batch MEN to reduce the number of mass exchangers to the minimum.     

A graphical approach to process synthesis and its application to steam reforming

It is common practice in chemical engineering to design processes sequentially. The type of product desired determines the choice of the feed materials that are introduced into the reactor networks. These in turn lead into the separation networks. The flows of heat and work are the final part of the sequence to be considered, with the application of heat exchanger networks, and any deficiency or excess in these flows is usually compensated for with the use of utilities. Although the ongoing research into reactor, separation, and heat exchanger optimization is of indubitable value, an aspect that is often overlooked in conventional research is the question: How do changes to one of the elements in the sequence affect the others? Most process designers do not address such matters until the next optimization of the sequence begins. The result of this sequential approach to design is that processes may contain a few very efficient units, but may also have others that are highly inefficient. A graphical technique that incorporates the flows of heat and work into the design of the process at a very early stage is proposed. The technique can be used to prepare flow sheets that represent a synthesized version of the elements that make up the complete process, rendering each component highly efficient. This new design tool uses the thermodynamic properties of enthalpy (representative of process heat requirements) and Gibbs free energy (representative of process work requirements) to develop process flow sheets that operate as close to reversibly as possible, and can be used as a foundation for more detailed refinements to achieve the best possible result. A case was described in a previous paper in which the graphical technique was applied to gasification. The application of the technique to the production of syngas by the steam reforming of natural gas is detailed. We show that the steam reforming process can be operated with increased reversibility and can actually consume carbon dioxide, thus representing a process with a carbon efficiency of greater than 100%, if the way in which all the process units interact with one another is used to utmost advantage. © 2013 American Institute of Chemical Engineers AIChE J, 59: 3714–3729, 2013     

A survey on applications of optimization-based integrating process design and control for chemical processes

Process design and control are closely related to each other in chemical engineering activities. Traditionally, process design and control system design are carried out in sequence. However, the integration of process design and control (IPDC) can bring greater economic benefits and process dynamic performance than traditional sequential design methods. This is true, particularly for modern chemical processes, in which various process units become more interacting and compact owing to the widespread use of heat integration and recycled streams, and the resulted impacts between process design and control begin to significantly influence both the capital and operational costs. Recently, considerable studies about the IPDC for chemical processes have been reported in published literature. The purpose of the paper is to survey the applications of optimization-based integrating process design and control for chemical processes. Firstly, attention has been focused on the applications of IPDC to different process units, for example, chemical reactors and separation columns. Then, the survey is extended to the applications of IPDC to plant-wide chemical processes. Finally, the future research challenges in the application of IPDC to chemical processes have been briefly discussed.     

Comparison of global optimization algorithms for the design of water-using networks

We address a special class of bilinear process network problems with global optimization algorithms iterating between a lower bound provided by a mixed-integer linear programming (MILP) formulation and an upper bound given by the solution of the original nonlinear problem (NLP) with a local solver. Two conceptually different relaxation approaches are tested, piecewise McCormick envelopes and multiparametric disaggregation, each considered in two variants according to the choice of variables to partition/parameterize. The four complete MILP formulations are derived from disjunctive programming models followed by convex hull reformulations. The results on a set of test problems from the literature show that the algorithm relying on multiparametric disaggregation with parameterization of the concentrations is the best performer, primarily due to a logarithmic as opposed to linear increase in problem size with the number of partitions. The algorithms are also compared to the commercial solvers BARON and GloMIQO through performance profiles.     

Iterative learning control for the systematic design of supersaturation controlled batch cooling crystallisation processes

The paper presents an approach to improve the product quality from batch-to-batch by exploiting the repetitive nature of batch processes to update the operating trajectories using process knowledge obtained from previous runs. The data based methodology is focused on using the linear time varying (LTV) perturbation model in an iterative learning control (ILC) framework to provide a convergent batch-to-batch improvement of the process performance indicator. The major contribution of this work is the development of a novel hierarchical ILC (HILC) scheme for systematic design of the supersaturation controller (SSC) of seeded batch cooling crystallizers. The HILC is used to determine the required supersaturation setpoint for the SSC and the corresponding temperature trajectory required to produce crystals with desired end-point property. The performance and robustness of these approaches are evaluated through simulation case studies. These results demonstrate the potential of the ILC approaches for controlling batch processes without rigorous process models.     

Spatial batch optimal design based on self-learning Gaussian process models for LPCVD processes

Low pressure chemical vapor deposition (LPCVD) is one of themost important processes during semiconductor manufacturing. However, the spatial distribution of internal temperature and extremely few samples makes it hard to build a good-quality model of this batch process. Besides, due to the properties of this process, the reliability of the model must be taken into consideration when optimizing the MVs. In this work, an optimal design strategy based on the self-learning Gaussian processmodel (GPM)is proposed to control this kind of spatial batch process. The GPMis utilized as the internalmodel to predict the thicknesses of thin films on all spatial-distributed wafers using the limited data. Unlike the conventional model based design, the uncertainties of predictions provided by GPM are taken into consideration to guide the optimal design of manipulated variables so that the designing can be more prudent. Besides, the GPM is also actively enhanced using as little data as possible based on the predictive uncertainties. The effectiveness of the proposed strategy is successfully demonstrated in an LPCVD process.     

数学规划与图形方法相结合设计热集成用水网络

将数学规划法与图形方法相结合探究单杂质用水网络与换热网络的集成问题。首先构建混合整数非线性规划模型（MINLP）,在最小公用工程消耗下优化流股参数未知情况下的分离系统组合曲线面积,得到了最为节能、换热面积最小的用水网络结构。在此基础上,提出了新的分离系统组合曲线演化步骤和规则,可以得到换热单元数目较小的换热网络结构。算例表明,与现有的基于分离系统的热集成用水网络设计方法相比,在最小化公用工程用量的同时可以进一步降低换热器数目与总换热面积。