Optimal Simultaneous Design and Operational Planning of Vegetable Extraction Processes

A general multiperiod linear optimization model is proposed in this study that targets the simultaneous design and operation planning decisions of a multiproduct batch plant for the production of vegetable extracts. A multiperiod environment is considered because of the market and/or seasonal fluctuations. Thereby, the model considers changes from period to period of demands, costs, prices and raw materials supplies. The objective function maximizes the net present value of the profit considering incomes, investments and resources costs, and both product and raw material inventory costs. In the plant design problem, the sequence of operations is already defined and the pursued goal is to determine both unit sizes and its configuration in the plant. Besides the usual duplication in parallel option, a novel design alternative is included which allows adding units in series to perform a given operation. The optimal design is determined by taking into account available discrete sizes of units which corresponds to the real procurement of equipments. The model is formulated by using the linear generalized disjunctive programming (LGDP). A particular plant that produces oleoresins (solvent extracts of herbs and spices) is used to illustrate the proposed approach. Nevertheless, the developed model is general and can thus be applied to any vegetable extraction process.     

Simultaneous subtour elimination model for single-stage multiproduct parallel batch scheduling with sequence dependent changeovers

In this paper a mixed-integer linear programming (MILP) model is presented to minimize makespan of single-stage multiproduct parallel batch production with sequence dependent changeovers. The computational inefficiency and suboptimal problems are addressed by the tight and rigorous formulation of the proposed model. Subtours (subcycles) are eliminated simultaneously so that the optimal solution is obtained in one step. The proposed model is tested with two examples. The results show that the model obtains the global optimal solutions with significant improvement in solution time.     

多产品间歇过程的分层次在线调度--一种数学规划与遗传算法的混合算法

In this contribution we present an online scheduling algorithm for a real world multiproduct batch plant. The overall mixed integer nonlinear programming (MINLP) problem is hierarchically structured into a mixed integer linear programming (MILP) problem first and then a reduced dimensional MINLP problem, which are optimized by mathematical programming (MP) and genetic algorithm (GA) respectively. The basis idea relies on combining MP with GA to exploit their complementary capacity. The key features of the hierarchical model are explained and illustrated with some real world cases from the multiproduct batch plants.     

A novel adaptive surrogate modeling‐based algorithm for simultaneous optimization of sequential batch process scheduling and dynamic operations

A novel adaptive surrogate modeling‐based algorithm is proposed to solve the integrated scheduling and dynamic optimization problem for sequential batch processes. The integrated optimization problem is formulated as a large scale mixed‐integer nonlinear programming (MINLP) problem. To overcome the computational challenge of solving the integrated MINLP problem, an efficient solution algorithm based on the bilevel structure of the integrated problem is proposed. Because processing times and costs of each batch are the only linking variables between the scheduling and dynamic optimization problems, surrogate models based on piece‐wise linear functions are built for the dynamic optimization problems of each batch. These surrogate models are then updated adaptively, either by adding a new sampling point based on the solution of the previous iteration, or by doubling the upper bound of total processing time for the current surrogate model. The performance of the proposed method is demonstrated through the optimization of a multiproduct sequential batch process with seven units and up to five tasks. The results show that the proposed algorithm leads to a 31% higher profit than the sequential method. The proposed method also outperforms the full space simultaneous method by reducing the computational time by more than four orders of magnitude and returning a 9.59% higher profit. © 2015 American Institute of Chemical Engineers AIChE J, 61: 4191–4209, 2015     

Multiproduct batch plants design using linear process performance models

In this contribution, a novel linear generalized disjunctive programming (LGDP) model is developed for the design of multiproduct batch plants optimizing both process variables and the structure of the plant through the use of process performance models. These models describe unit operations using explicit expressions for the size and time factors as functions of the process variables with the highest impact. To attain a linear formulation, values of the process variables as well as unit sizes are selected from a set of meaningful discrete values provided by the designer. Regarding structural alternatives, both kinds of unit duplications in series and in parallel are considered in this approach. The inclusion of the duplication in series requires different detailed models that depend on the structure selected. Thus, in a new approach for the multiproduct batch plant design, a set of potential structural alternatives for the plant is defined. © 2010 American Institute of Chemical Engineers AIChE J, 2011     

Adaptive model predictive inventory controller for multiproduct batch plant

An inventory control system was developed for multiproduct batch plants with an arbitrary number of batch processes and storage units. Customer orders are received by the plant at order intervals and in order quantities that are subject to random fluctuations. The objective of the plant operation is to minimize the total cost while maintaining inventory levels within the storage or warehouse capacity by adjusting the startup times, the quantities of raw material orders, and production batch sizes. An adaptive model predictive control algorithm was developed that uses a periodic square wave model to represent the flows of the material between the processes and the storage units. The boundedness of the control output and the convergence of the estimated parameters in implementations of the proposed algorithm were mathematically proven under the assumption that disturbances in the orders are bounded. The effectiveness of this approach was demonstrated by performing simulations. © 2015 American Institute of Chemical Engineers AIChE J, 61: 1867–1880, 2015     

A Mathematical Model of the Functioning of Multiproduct Chemical Engineering Systems

A mathematical model of the functioning of multiproduct chemical engineering systems is proposed. The model is used to solve problems of designing the main apparatuses of a system (determining the number of apparatuses in stages of the system and their main geometric sizes and operating modes). Such problems are encountered in design of multirange small-batch chemical production units and their conversion to synthesizing new products. The model proposed takes into account the possibility of division and combination of batches of raw material and intermediate products in apparatuses in certain stages of their processing. Original algorithms for solving relations of the model are developed, one of which is an algorithm for minimizing the duration of operating cycles of a system in the division and combination of batches of materials during their processing and the other of which is an algorithm for determining the product batch sizes that ensure the possibility to perform combinable stages of their synthesis in apparatuses of the same sizes. On the basis of the proposed model and algorithms for solving the set of model relations, a system for automated calculation of the number and geometric sizes of the main apparatuses of multiproduct chemical engineering systems is created. Using this automated calculation system, more than thirty production units for synthesizing chemical dyes and intermediate products are designed and converted to synthesizing new products.__________Translated from Teoreticheskie Osnovy Khimicheskoi Tekhnologii, Vol. 39, No. 4, 2005, pp. 455–465.Original Russian Text Copyright © 2005 by Malygin, Karpushkin, Borisenko.     

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.     

An efficient MILP continuous-time formulation for short-term scheduling of multiproduct continuous facilities

This paper presents a new MILP mathematical formulation for the scheduling of resource-constrained multiproduct plants involving continuous processes. In such facilities, a sequence of continuous processing steps is usually carried out to produce a significant number of final products and required intermediates. In order to reduce equipment idle time due to unbalanced stage capacities, storage tanks are available for temporary inventory of intermediates. The problem goal is to maximize the plant economic output while satisfying specified minimum product requirements. The proposed approach relies on a continuous time domain representation that accounts for sequence-dependent changeover times and storage limitations without considering additional tasks. The MILP formulation was applied to a real-world manufacturing facility producing seven intermediates and fifteen final products. Compared with previous scheduling methodologies, the proposed approach yields a much simpler problem representation with a significant saving in 0–1 variables and sequencing constraints. Moreover, it provides a more realistic and profitable production schedule at lower computational cost.     

An integrated approach to computer-aided operation of batch chemical plants

The design and implementation of a computer-based system which integrates planning and plant control of batch chemical plants is presented. Such a system is required so that the full benefits of computer-aided operation, increased production, improved product quality and reduced operating costs may be realized. A functional analysis of the operational requirements of batch plants indicate that a hierarchical and distributed system is favoured. A new operational activity, batch management, is defined which provides the necessary integration by coordinating the activities of the planning and control levels. Batch management allows the control level activities to be driven by events at the planning level such as changes in product demands. It also provides a feedback path from the control level back up to the planning level so that the inherent variability of batch processes can be accounted for and overcome. This is achieved by dynamic, on-line rescheduling. A very general implementation of this design is described. The implementation is centred around a real-time database and permits the operation of a wide range of processes including multiproduct, multipurpose plants with both serial and parallel lines, intermediate storage, shared utilities, etc. To demonstrate its effectiveness, two applications are presented, one in conjunction with an on-line, real-time control system, and the other with an off-line discrete event simulator. The significant benefits achieved in terms of improved operation are discussed.     

用于多产品间歇化工过程排序的模拟退火算法

提出了一种适用于多产品间歇化工过程排序的改进模拟退火算法 ,该算法采用了非平衡、多次退火策略及多个相邻解产生方法 .通过对无限中间储罐 (UIS)类问题的研究表明 ,同已有的方法相比 ,该方法求解精度高 ,计算速度快 ,适合于求解多产品间歇化工过程的排序问题 .     

多因素不确定条件下的间歇生产调度优化

不确定条件下的间歇生产调度优化是生产调度问题研究中具有挑战性的课题。提出了一种基于混合整数线性规划(MILP)的鲁棒优化模型,来优化不确定条件下的生产调度决策。考虑到生产过程中的操作成本和原料成本,建立了以净利润最大为调度目标的确定性数学模型。然后考虑需求、处理时间、市场价格三种不确定因素,建立可调整保守程度的鲁棒优化模型并转换成鲁棒对应模型。实例结果表明,鲁棒优化的间歇生产调度模型较确定性模型利润减少,但生产任务数量增加,设备空闲时间缩短,从而增强了调度方案的可靠性,实现了不确定条件下生产操作性和经济性的综合优化。     

Design of integrated batch processes with discrete and continuous equipment sizes

This paper presents a mathematical programming approach for the integrated design of batch processes involving multiple processing steps. Detailed dynamic models are used to describe the behaviour of individual batch operations. The mathematical formulation regards both the design (e.g. equipment items with discrete sizes) and operational characteristics (i.e. control variable profiles such as reflux ratio, cooling water flowrate) of each task as degrees-of-freedom, the values of which are selected to optimise a particular objective function (e.g. profit). The solution may be restricted by inequality constraints which hold throughout the task (e.g. reactor temperature violation) or at the end of the task (e.g. end-product purity specification). The sizes of the equipment items are treated as discrete decisions and are chosen from a selection of standard sizes. The mathematical formulation leads to a mixed integer dynamic optimisation problem and is solved using the outer approximation/augmented penalty (OA/AP) algorithm.     

Design of multipurpose production facilities: A RTN decomposition-based algorithm

A general mathematical formulation for the design of multipurpose facilities has recently been presented by Barbosa-Póvoa and Pantelides (1997). The model proposed permits a detailed consideration of the design problem taking account of trade-offs between capital costs, revenues and operational flexibility. The optimal solution involves the selection of the required processing and storage equipment items and the required levels of provision of other production resources such as utilities, manpower, cleaning and transportation equipment.In order to guarantee solution optimality, the above design formulation has to consider a large number of equipment items, out of which it will select the ones that will actually be incorporated in the plant. This may result in large mixed-integer linear programming (MILP) problems that are expensive to solve.This paper presents a decomposition approach for the solution of large batch process design problems. The approach involves the iterative solution of a master problem (representing a relaxation of the original design problem) and a design sub-problem (in which several of the design decisions are already fixed).An example illustrating the effectiveness of the proposed decomposition approach is presented.     

Production Rate‐Dependent Key Performance Indicators for a Systematic Design of Biochemical Downstream Processes

Key performance indicators have become a common tool in bioprocess development, as they allow an objective and independent rating and ranking of process alternatives screened. A disadvantage of all key performance indicators developed so far is their strong focus on costs, which makes them neglect the influence of the production rate on the profit of the process. But, since both production costs and production rate have an equally strong impact, both should be considered when decisions have to be made. Therefore, two new key performance indicators are introduced in this work, one for batch and one for continuous processing. They combine product yield, purity performance, variable manufacturing costs, and production rate to one objective. Thereby, misguided trade‐offs between these four individual measures can be replaced by one key performance indicator. This ensures a systematic development of biochemical downstream processes.     

Optimal model-based aeration control policies in a sequencing batch reactor

We present a non-linear programming formulation for the computation of optimal aeration policies in a sequencing batch reactor for wastewater streams treatment. We assume that organic matter and nitrogen are the main pollutants to be removed to meet water quality targets. The novelty of the work lies in the fact that no binary variables are required to compute the switching time between the aerobic and anoxic stages of the water treatment process leading to a simpler, robust and easier to compute optimization formulation. Moreover, because the control valve, through which air is fed to the reactor, can take either its minimum or maximum bounds as well as any fractional values between such bounds, improved optimal aeration profiles are reported. Such improved profiles mean that shorter processing times are required, compared to previous solutions, leading also to a reduction in the operation cost of the wastewater treatment process. Although the optimal operation policies were computed for a typical home wastewater stream, the optimization formulation can also be extended for the treatment of other polluted streams.     

Real-time monitoring of an industrial batch process

This paper describes the development of a real-time monitoring system for a batch process operated by Aroma and Fine Chemicals Limited. The process shares many similarities with other batch processes in that cycle times can vary considerably, instrumentation is limited and inefficient laboratory assays are required to determine the end-point of each batch. The aim of the work conducted in this study was to develop a data driven system to accurately identify the end-point of the batch. This information can then be used to reduce the overall cycle time of the process. Novel approaches based upon multivariate statistical techniques are shown to provide a soft sensor that can estimate the product quality throughout the batch and provide a long-term estimate of the likely cycle time. This system has been implemented on-line and initial results indicate that it offers potential to significantly reduce operating costs.     

Process modelling and technology evaluation in brewing

To reach an integrated sustainable production site, it is important to analyse effects of technology changes. A “brewery model” has been developed which allows process modelling of a brewing facility. Besides the comparison of specific demand figures, it allows a holistic view of the production site and most importantly the modelling of energy demand profiles. Energy demand profiles in brewing vary significantly based on the chosen technology set. Furthermore they are notably influenced by production planning, heat exchanger surfaces and heat supply management. A reduction in energy intensity in the brewhouse processes will lead to the possibility to design heat supply equipment at lower capacity. The mashing process is an important candidate in considerations for heat recovery and low temperature heat supply. New temperature profiles in mashing can improve processing time, quality of the produced wort as well as enable the integration of low temperature heat in a better way.     

多目的间歇化工过程最优设计——SA/LP算法

提出了具有多条生产路线的多目的间歇化工过程最优设计混合整数非线性规划(MINLP)模型,该模型允许同时设立同步、异步平行单元以及中间储罐,并允许设备尺寸离散变化.在结合模拟退火(SA)和线性规划(LP)的基础上提出了可求解上述MINLP问题的SA/LP算法,该算法结合了SA全局收敛性好和LP可处理连续变量与约束方程的优点.计算表明,上述模型与算法实施简便,得到了文献算例中未得到的全局最优解,且在计算速度、内存占用上都远远优于文献中的方法.     

Heat Integration in Straight‐Through Sulfur Recovery Units to Increase Net High‐Pressure Steam Production

Energy conservation is of paramount importance in oil and gas industries. Sulfur recovery units (SRUs) in oil and gas industries are required to meet the stringent environmental emission regulations, and are often viewed as production costs. They are normally net energy exporters and a considerable portion of heat is recovered as high‐pressure steam. However, SRUs processing lean acid gas streams require significant amounts of acid gas and air preheating before they enter the reaction furnace. Some portion of the generated high‐pressure steam is used in preheating these streams. This reduces the overall net high‐pressure steam generated from the SRU. Here, heat integration is used and an existing SRU facility is retrofitted such that there is an increase in net high‐pressure steam production. Seven new heat‐integrated SRU configurations are proposed, and key aspects such as net high‐pressure steam production, investment costs, and payback period for each of the new retrofitted configurations are compared.