Scheduling Multiproduct Chemical Batch Processes using Matrix Representation

Batch process plants are usually designed for the production of specialty and fine chemicals such as paint, food and pharmaceutical to meet specific product requirements as set by current market demand. Batch process plants can be operated as single product in which only one product is produced and multiple products which allow production of more than one product using same batch facility. The economics of the batch process heavily depends on efficient scheduling of the different tasks involved in manufacturing the range of products. The main objective of scheduling is generally to minimize completion time known as the makespan of the batch process. Product sequencing, which is used to set order of products to be produced, has a direct impact on the makespan particularly in the multiple products case. Another effect on makespan is observed for different transfer policies used to transfer the product intermediates between process stages. The generally adopted intermediate transfer policies are (i) zero wait (ZW), (ii) no intermediate storage (NIS), (iii) unlimited intermediate storage (UIS) and (iv) finite intermediate storage (FIS). In the past, the determination of makespan for each transfer policy has been done using a number of mathematical and heuristics approaches. Although these approaches are very efficient and are currently being applied in many chemical process industries but most of them end up with the solution in terms of complex mathematical models that usually lack user interactions for having insights of the scheduling procedure. This motivated the current work to develop relatively simple and interactive alternate approaches to determine makespan. The proposed approach uses matrix to represent the batch process recipe. The matrix is then solved to determine the makespan of a selected production sequence. Rearrangement of the matrix rows according to the varied production sequences possible for the specified batch process recipes enables the makespan to be determined for each sequence. Designer is then provided with the production sequence options with its corresponding makespan from which a selection could be made according to the process requirements

Heat integration of multipurpose batch plants through multiple heat storage vessels

Master of Science in Engineering by research: “A dissertation submitted to the Faculty of Engineering and Built Environment, University of the Witwatersrand, Johannesburg, in fulfillment of the requirements for the degree of Master of Science in Engineering.” Johannesburg, 05 February 2018In most industrial processes, energy is an integral part of the production process; therefore, energy consumption has become an intensified area in chemical engineering research. Extensive work has been done on energy optimisation in continuous operations; unlike in batch operations because it was believed that due to the small scale nature of batch plants, small amounts of energy is consumed. Certain industries such as the brewing and dairy industries have shown to be as energy intensive as continuous processes. It is, therefore, necessary for energy minimisation techniques to be developed specifically for batch processes in which the inherent features of batch operations such as time and scheduling are taken into account accordingly. This can be achieved through process integration techniques where energy consumption can be reduced while economic feasibility is still maintained. Most of the work done on energy minimisation either focuses on direct heat integration, where cold and hot units operating simultaneously are integrated, or indirect heat integration, where units are integrated with heat storage. The schedules used in these models are, in most cases, predetermined which leads to suboptimal results. This work is aimed at minimising energy consumption in multipurpose batch plants by using direct heat integration together with multiple heat storage vessels through mathematical programming. The proposed approach does not use a predetermined scheduling framework. The focus lies on the heat storage vessels and the optimal number of heat storage vessels together with their design parameters, namely size and the temperature at which the vessels are initially maintained, are determined. The formulation developed is in the form of a mixed integer non-linear program (MINLP) due to the presence of both continuous and integer variables, as well as non-linear constraints governing the problem. Two illustrative examples are applied to the formulation in which the optimal number of multiple heat storage vessels is not known beforehand. The results rendered from the model show a decrease in the external utilities, in the form of cooling water and steam, compared to the base case where no integration is considered and the case where only one heat storage vessel is used.MT 201

Dynamic hybrid simulation of batch processes driven by a scheduling module

Simulation is now a CAPE tool widely used by practicing engineers for process design and control. In particular, it allows various offline analyses to improve system performance such as productivity, energy efficiency, waste reduction, etc. In this framework, we have developed the dynamic hybrid simulation environment PrODHyS whose particularity is to provide general and reusable object-oriented components dedicated to the modeling of devices and operations found in chemical processes. Unlike continuous processes, the dynamic simulation of batch processes requires the execution of control recipes to achieve a set of production orders. For these reasons, PrODHyS is coupled to a scheduling module (ProSched) based on a MILP mathematical model in order to initialize various operational parameters and to ensure a proper completion of the simulation. This paper focuses on the procedure used to generate the simulation model corresponding to the realization of a scenario described through a particular scheduling

Wastewater minimization in multipurpose batch processes using mathematical modelling

A dissertation submitted to the Faculty of Engineering and the Built Environment, University of the Witwatersrand, in fulfillment of the requirements for the degree of Master of Science in Engineering May 2018The increase in the degradation of water sources and stringent environmental regulations have greatly motivated industries to explore means of utilizing water efficiently. Batch processes are known to generate highly contaminated wastewater that is toxic to the environment. A holistic approach to design which emphasizes the unity of the process, process integration (PI), can be used to reduce both the wastewater generated and the level of contamination while maintaining the profitability of the chemical plant. Process integration techniques for wastewater minimization in batch processes include water reuse, recycle and regeneration. Most mathematical formulations for wastewater minimization in multipurpose batch processes presented in literature determine the amount of water required for washing operations by only looking at the task that has just occurred in a unit. However, the nature of the succeeding task can influence the amount of water required for the washing operation between consecutive tasks in a processing unit. In paint manufacturing, for example, more water will be required for the washing operation if the production of white paint follows the production of black paint and less water will be required if the black paint follows the white paint. The amount of wastewater generated in batch processes can, therefore, be reduced by simply synthesizing a sequence of tasks that will generate the least amount of wastewater. Presented in this work are wastewater minimization formulations for multipurpose batch processes which explore sequence dependent changeover opportunities for water minimization simultaneously with direct and indirect water reuse and recycle opportunities. The presence of continuous and integer variables, as well as bilinear terms, rendered the model a Mixed Integer Nonlinear Program (MINLP). The developed MINLP model was validated using two single contaminant illustrative examples and a multiple contaminant example. A global optimization solver, Branch and Reduce Optimization Navigator (BARON), was used to solve the optimization problems on a General Algebraic Modeling System (GAMS) platform. Exploring multiple water saving opportunities simultaneously has proven to be computationally intensive but can result in significant water savings. For instance, two different scenarios saved 65% and 61% in freshwater use respectively.MT 201

An effective MILP-based decomposition algorithm for the scheduling and redesign of flexible job-shop plants

This paper presents a decomposition algorithm for the integrated scheduling and redesign problem of a multistage batch plant dealing with multipurpose units and heterogeneous recipes. First, the procedure solves the scheduling problem considering the existing plant configuration with the main goal of minimizing the makespan. Then, a second objective of minimizing the number of units utilized without worsen the makespan achieved in the first stage is considered. The units released can be reallocated to other compatible processing stages in order to minimize the initial makespan value. In order to tackle large industrial examples, both scheduling and redesign problems are solved through a decomposition algorithm, which has a MILP model as its core. The procedure is tested on several realistic instances, demonstrating its robustness and applicability.Fil: Basán, Natalia Paola. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: Coccola, Mariana Evangelina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; ArgentinaFil: del Valle, Alejandro García. Universidad da Coruña; EspañaFil: Mendez, Carlos Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Instituto de Desarrollo Tecnológico para la Industria Química. Universidad Nacional del Litoral. Instituto de Desarrollo Tecnológico para la Industria Química; Argentin

A Petri Nets-based Scheduling Methodology forMultipurpose Batch Plants.

This article presents an optimization methodology of batch production processes assembled by shared resources which rely on a mapping of state-events into time-events allowing in this way the straightforward use of a well consolidated scheduling policies developed for manufacturing systems. A technique to generate the timed Petri net representation from a continuous dynamic representation (Differential-Algebraic Equations systems (DAEs)) of the production system is presented together with the main characteristics of a Petri nets-based tool implemented for optimization purposes. This paper describes also how the implemented tool generates the coverability tree and how it can be pruned by a general purpose heuristic. An example of a distillation process with two shared batch resources is used to illustrate the optimization methodology proposed

Optimal synthesis of storageless batch plants using the process intermediate storage operational policy

A novel operational policy, the Process Intermediate Storage (PIS) operational policy, is introduced and used to synthesize, schedule and design multipurpose batch plants. The model is based on the State Sequence Network (SSN) and non-uniform discretization of the time horizon of interest model developed by Majozi&Zhu (2001). Two cases are studied to determine the effectiveness of the operational policy. A plant without dedicated intermediate storage is considered in the first case. In this case the throughput is maximized with and without the use of the PIS operational policy. The use of the PIS operational policy results in a 50% improvement in the throughout. The second case is used to determine the minimum amount of intermediate storage while maintaining the throughput achieved with infinite intermediate storage. This resulted in a 33% reduction in the amount of dedicated intermediate storage. The models developed for both cases are MILP models. A design model is then developed to exploit the attributes of the PIS operational policy. The design model is a MINLP due to the capital cost objective function. This model is applied to a literature example and an industrial case study and in both cases results in improved flowsheets and reduced capital cost.Dissertation (MEng)--University of Pretoria, 2008.Chemical Engineeringunrestricte

Scheduling of heat integrated multipurpose batch Processes

A systematic mathematical framework for scheduling the operation of multipurpose batch plants involving heat-integrated unit operations is presented. The approach advocated takes direct account of the trade-offs between maximal exploitation of heat-integration and others scheduling objectives and constraints. In this paper, heat transfer takes place directly between the fluids undergoing processing in the heat integrated unit operations, and therefore a degree of time overlap of these operations must be ensured. The modelling is based on the ERTN formalism and a discrete time MILP formulation