Batch Plants Research Articles

Sustainable scheduling of batch processes under economic and environmental criteria with MINLP models and algorithms

We address the bi-criterion optimization of batch scheduling problems with economic and environmental concerns. The economic objective is expressed in terms of productivity, which is the profit rate with respect to the makespan. The environmental objective is evaluated by means of environmental impact per functional unit based on the life cycle assessment methodology. The bi-criterion optimization model is solved with the ε-constraint method. Each instance is formulated as a mixed-integer linear fractional program (MILFP), which is a special class of non-convex mixed-integer nonlinear programs. In order to globally optimize the resulting MILFPs effectively, we employ the tailored reformulation-linearization method and Dinkelbach's algorithm. The optimal solutions lead to a Pareto frontier that reveals the tradeoff between productivity and environmental impact per functional unit. To illustrate the application, we present two case studies on the short-term scheduling of multiproduct and multipurpose batch plants.

Simulation-based Concrete Truck-Mixers Fleet Size Determination for On-Site Batch Plant Operation

Resource management depends on the particulars of the operational setting within which the project resources are being deployed. This paper analyses the operations of an on-site batch plant and the concrete supply process with the aid of simulation-based modeling. The objective of the study is the determination of the concrete truck fleet size that fits best the project needs. The model building process is described and key production parameters are identified. Data are collected to define activity durations and alternative scenarios are being examined by the use of sensitivity analysis. Simulation outputs are validated against the actual records and the practical implications of the deployed truck fleet size is examined against utilization and productivity criteria. The research findings indicate that the model- generated information aids construction managers in making informed decisions regarding the resource management strategy that is going to be implemented on site.

Hybrid Bilevel-Lagrangean Decomposition Scheme for the Integration of Planning and Scheduling of a Network of Batch Plants

Motivated by a real-world industrial problem, this work deals with the integration of planning and scheduling in the operation of a network of batch plants. The network consists of single-stage, multiproduct batch plants located in different sites, which can exchange intermediate products in order to blend them to obtain finished products. The time horizon is given and divided into multiple time periods, at the end of which, the customer demands have to be exactly satisfied. The planning model is a simplified and aggregate formulation derived from the detailed precedence-based scheduling formulation. Traveling Salesman Problem (TSP) constraints are incorporated at the planning level in order to predict the sequence-dependent changeovers between groups of products, within and across time periods, without requiring the detailed timing of operations, which is performed at the scheduling level. In an effort to avoid solving the full-space, rigorous scheduling model, especially for large problem sizes, two dec...

Manual Design Strategies for Multicontaminant Water-Using Networks in Batch Processes

Simple design heuristics are developed in this work to manually generate batch water-using networks with multiple contaminants. The performance indices used for analyzing the continuous systems, i.e., concentration potential of demand (CPD) and concentration potential of source (CPS), are adopted to guide the synthesis steps. Specifically, if the batch plant is operated in cyclic mode, these concentration indices are treated as the primary criteria and the time priority as a secondary issue to match the water demands and sources sequentially. On the other hand, the precedence order of the concentration and time considerations is reversed if it is only necessary to schedule a single campaign. Both the required capacities and the number of buffer tanks in storage facilities can also be determined with the proposed procedures. Finally, two examples are presented at the end of this paper to demonstrate the effectiveness of the proposed manual approach.

Modelling and solving for ready-mixed concrete scheduling problems with time dependence

In this paper, we present a formulation for the ready-mixed concrete scheduling problems with time-dependent travel time. Traffic congestion is a major problem for the business of delivering RMC. It may lead to late deliveries of RMC to construction sites, and because RMC is perishable, late deliveries also mean large additional costs for both batch plants and the construction companies. Additional costs caused by traffic congestion can be reduced by taking predictable traffic congestion into account in the process of scheduling. For this purpose we develop a model with consideration of traffic congestion of RMC which uses a heuristic approach based on local search algorithm to solve. A detailed case study based on industrial data is used to illustrate the potential of the proposed approach.

Reacted and Activated Rubber

Traditionally, asphalt rubber (AR) mixtures have been difficult to produce. Their production requires specialized plants and equipment, which has resulted in their high cost to manufacture. In part this difficulty is due to the need to produce AR binder by blending it at high temperatures for a significant period of time (typically at about 190°C for 45 min to 1 h). The complexities in the process have caused AR mixes to be significantly more expensive to produce than conventional paving mixtures. A new technology that produces a reacted and activated rubber (RAR), which is an elastomeric asphalt extender, has been developed by hot blending and activation of a rubber granulate with a selected asphalt binder and activated mineral binder stabilizer. RAR achieves results comparable to those of other types of polymer modified binders (PMBs). However, a principal advantage of RAR is that it can be added easily to any hot-mix asphalt manufacturing facility with systems designed to feed particulate material into a batch plant (pugmill) or drum mix plant. This paper describes how RAR is produced from raw constituent materials. Various binder tests contrast performance with typical paving grades and PMBs used in the United States. The implementation of RAR in various types of asphalt mixtures is discussed, and demonstrative examples of test results are provided. Tests on mixtures in wheel tracking and fatigue demonstrate how the binder performance tests translate into mixture performance. In all cases evaluated, the RAR mixtures outperformed nonmodified and even conventional rubber modified equivalent materials.

Petri-net modelling for batch production

Timed Petri nets can be used for the modelling and analysis of a wide range of concurrent discrete-event systems, e.g. batch production systems. The present paper describes how to do so while starting from the information about the structure of a production facility and about the products usually given in production-data management systems. We describe a method for using these data to algorithmically build a Petri-net model. The method was used to study the multi-product batch plant and to identify bottleneck situations.

複数ジョブをもつ離散型並列生産システムのための動作モデルの提案

A formal model named Expanded-Timed-State-Chart (ETSC) for expressing the complex behavior of a discrete production system (DPS), where multiple jobs are simultaneously carried out in parallel, was proposed by expanding Timed-State-Chart model. Making use of the model, event-driven simulation of DPS in formal fashion can conveniently be carried out, and so the verification method based on Model-Checking becomes applicable to DPS. In order to illustrate the usefulness of the model, computational experiments were carried out for verifying the validity of operations given to a target DPS, that is a multi-purpose chemical batch plant given by Japan Batch Forum. Some practical assumptions to reduce the “reachable-tree” to a restricted one have been introduced here in order to avoid the difficulty of combinatorial explosion, that intrinsically appears in the generation of Kripke-Structure of original DES.

Speed-up Benders decomposition using maximum density cut (MDC) generation

The classical implementation of Benders decomposition in some cases results in low density Benders cuts. Covering Cut Bundle (CCB) generation addresses this issue with a novel way generating a bundle of cuts which could cover more decision variables of the Benders master problem than the classical Benders cut. Our motivation to improve further CCB generation led to a new cut generation strategy. This strategy is referred to as the Maximum Density Cut (MDC) generation strategy. MDC is based on the observation that in some cases CCB generation is computational expensive to cover all decision variables of the master problem than to cover part of them. Thus MDC strategy addresses this issue by generating the cut that involves the rest of the decision variables of the master problem which are not covered in the Benders cut and/or in the CCB. MDC strategy can be applied as a complimentary step to the CCB generation as well as a standalone strategy. In this work the approach is applied to two case studies: the scheduling of crude oil and the scheduling of multi-product, multi-purpose batch plants. In both cases, MDC strategy significant decreases the number of iterations of the Benders decomposition algorithm, leading to improved CPU solution times.

Ammoximation of Cyclohexanone to Cyclohexanone Oxime Catalyzed by Titanium Silicalite-1 Zeolite in Three-phase System

An innovative green process of producing ɛ-caprolactam was proposed by integrating ammoximation and Beckmann rearrangement effectively. As a first part of the new process, TS-1 molecular sieve-catalyzed synthesis of cyclohexanone oxime from cyclohexanone, ammonia and hydrogen peroxide was carried out in a batch plant. Cyclohexane was used as the solvent in the three-phase reaction system. The influences of essential process parameters on ammoximation were investigated. Under the reaction conditions as catalyst content of 2.5% (by mass); H2O2/yclohexanone molar ratio of 1.10; NH3/cyclohexanone molar ratio of 2.20; reaction temperature of 343 K; reaction time of 5 h, high conversion of cyclohexanone and selectivity to oxime (both>99%) were obtained. Thus, the three-phase ammoximation process showed equal catalytic activity as TS-1 but much more convenient and simpler for the separation of catalyst in comparison to the industrial two-phase system with t-butanol used as solvent.

Physical Properties of 50MPa and 80MPa Ternary High Strength Concretes before and after Concrete Pumping

At the Korea Land and Housing Corporation(LH), concretes with high design strength of 50 MPa and 80 MPa that are composed only of ordinary Portland cement, blast furnace slag, and fly ash are developed. To determine whether the developed high strength concretes have the same properties when they are produced in batch plant(B/P) condition in the ready mixed concrete plant, and as existing high strength concretes, field tests are performed and material properties are evaluated. To investigate the material properties of the high strength concretes before and after pumping, compressive strength, flowability, air content, hydration temperature, pumping and compactability are evaluated. In field tests, before and after pumping, flowability satisfied the relevant criteria. In terms of air content, while it was slightly decreased after pumping, it satisfied the requirements. Hydration temperature criteria were satisfied, and compactability was excellent as well. The study found that the developed ternary high strength concretes have the same properties as existing high strength concretes. They can also be useful for the construction of high-rise buildings, as they are economical.

Model-Based Identification and Analysis of the Energy Saving Potential in Batch Chemical Processes

Optimization of energy consumption for reducing the relevant costs and environmental impacts is constantly gaining attention in chemical batch production. Existing methodologies focus on heat integration considering scheduling constraints and typically result in trade-offs between capital investment and operational costs. However, in multipurpose batch plants, even the allocation of energy flows and the consistent operation according to production recipes pose a great challenge due to batch-to-batch variability and lack of energy utility consumption meters. This paper utilizes a bottom-up modeling approach for energy utility consumption and proposes a method for model-based identification of the energy saving potential in chemical batch plants. The bottom-up models can accurately track the energy utility consumption at various production levels and are used as soft sensors for energy efficiency analysis studies. In this context, a set of energy key performance indicators (EKPIs) is proposed for quantifying efficiency in energy use, and an energy saving potential index (ESPI) based on historical plant performance serves as a shortcut method in the case of missing or inaccurate production recipes. The methodology is applied to an industrial multipurpose batch plant for specialty chemicals, exemplifying the obtained efficiency results and targeting energy saving potential for steam consumption.

Estimation and Analysis of Energy Utilities Consumption in Batch Chemical Industry through Thermal Losses Modeling

A systematic approach for the estimation of energy utility consumption in chemical batch plants is presented and validated. This approach is based on bottom-up modeling of energy use and its conversion in usual energy carriers like steam, cooling water and brine, including estimation of thermal losses. The modeling involves a detailed energy balance of each unit operation using dynamic plant data. Thermal losses are determined using an empirical parametric equation for each equipment and utility. The method was applied to one monoproduct and one multiproduct building of a chemical batch plant comprising 20 main equipments (reactor vessels, heat exchangers and dryers) for the production of 5 specialty chemicals and intermediates over a period of 2 months. For fitting the parameters of the empirical thermal losses models it was crucial to determine the real energy consumption for the investigated equipments. In the lack of installed flowmeters it was tested whether this task can be performed through calibration of the valves controlling the utility distribution based on valve opening. A direct and an indirect calibration method were applied both providing satisfactory level of accuracy. Validation of the bottom-up models was performed at different aggregation levels, including equipment specific unit operations, production lines and overall building energy consumption. The results indicated that for all types of energy utility, equipment and unit operation the consumption could be estimated with a relative error between 5% and 35% depending on the aggregation level. These results can motivate plant managers and process engineers to consider model-based estimation and analysis of energy utilities for monitoring and optimization purposes in industrial practice.

Flexible maintenance within a continuous-time state-task network framework

Preventative maintenance is common in industry and aids in sustaining reliable process operations. If maintenance is executed within the production schedule, it imposes restrictions on the shared resources of the manufacturing facility. In multipurpose batch plants, these restrictions can affect many product pathways and have a significant impact on plant profitability. The combined optimization of process maintenance and production scheduling should therefore exploit the inherent flexibility of such plants and provide solutions with the highest profitability. This paper presents a mathematical model capable of addressing the combined scheduling of maintenance and production tasks within a continuous-time state-task network based framework. Multiple maintenance types are addressed within the framework. The proposed formulation is illustrated on an adaptation of a well cited literature problem, and the benefit of combined maintenance and production scheduling highlighted.

A disjunctive programming model and a rolling horizon algorithm for optimal multiperiod capacity expansion in a multiproduct batch plant

This paper addresses a multiperiod mixed integer nonlinear programming problem for the capacity expansion of multiproduct batch plants. Given a certain batch plant with its current configuration, product recipes, and growing production targets, modular expansions are wanted so that new demand can be met. Unlike most work for the batch retrofit problem, a multiperiod disjunctive model is presented, such that long term investments and expansions can be planned out in advance. To solve the model we propose a rolling horizon algorithm that further exploits the advantages of a disjunctive programming model. Empirical work shows that the rolling horizon algorithm is very effective on finding near optimal solutions to large instances with a considerable number of time periods. Furthermore, the solution found by the proposed algorithm can be used as a starting solution for the direct method to the original problem delivering a global optimal solution.

Rule-Based Scheduling of Single-Stage Multiproduct Batch Plants with Parallel Units

A new rule-based model for single-stage multiproduct scheduling problem (SMSP) in batch plants with parallel units is proposed. The scheduling problem is decomposed into two subproblems of order assignment and order sequencing. A group of order assignment rules are introduced to select suitable units for customer orders. While flexible constraint handling strategies are proposed to eliminate the constraints of forbidden units and unit release times and convert the hard constraint of forbidden sequences to a soft one, leading to any arbitrary order sequence can be synthesized into a legal schedule. The line-up competition algorithm (LUCA) is presented to obtain optimal order sequence and order assignment rule, which can minimize makespan, total tardiness, or total cost. Through comparative study, the proposed approach has demonstrated its effectiveness for solving a large size SMSP.

A novel hybrid differential evolution approach to scheduling of large-scale zero-wait batch processes with setup times

Due to their significance both in theory and industrial application, zero-wait scheduling problems (ZWSPs) of batch plants have received more and more attentions. However, how to tackle large-scale ZWSPs with setup times is still a challenging problem. This paper presents a novel hybrid permutation-based differential evolution (HPDE) for this purpose. More specifically, ZWSPs are formulated as asymmetrical traveling salesman problems (ATSP). To deal with ATSP model effectively, a permutation-based DE (PDE) algorithm and fast complex heuristic (FCH) local search scheme are proposed. Furthermore, HPDE, a hybrid approach of PDE and FCH local search, is proposed. The performances of HPDE are illustrated based on extensive experiments and comparisons with recently developed approaches in literature. The results demonstrate that HPDE reaches high-quality solutions in short computational time. Furthermore, it requires fewer user-defined parameters, rendering it applicable to real-life large-scale ZWSPs with setup times.

A tighter cut generation strategy for acceleration of Benders decomposition

This paper presents a novel strategy for speeding up the classical Benders decomposition for large-scale mixed integer linear programming problems. The proposed method is particularly useful when the optimality cut is difficult to obtain. A ratio of distances from a feasible point to an infeasible point and a feasibility cut is used as a metric to determine the tightest constraint for the region located by the feasible point, thus improving the convergence rate. Application of the proposed approach to a multi-product batch plant scheduling problem shows substantial improvement both in the computational time and the number of iterations.

Study on Temperature Control Method of Yeywa Hydropower Station RCC Dam Construction

Yeywa hydropower station RCC dam is located in the torrid zone of Asian, During the construction period, it meet Technical problem of temperature control in hot season. We can utilize the peculiarity of RCC that has a slow temperature rise due to hydration heat and a low early strength, according to analyse the blending and concreting procedure of RCC, adopt comprehensive and effective temperature control method, such as confirm concrete mix, control the temperature of raw material and RCC out of the batch plant, prevent temperature rise during transporting and concreting, setting joint to avoid structural crack and temperature crack. From Yeywa hydropower station RCC dam construction finished to now, no dangerous crack is detected, It accumulate experiences for RCC dam construction in high temperature place.

A Mixed Integer Linear Programming model for simultaneous design and scheduling of flowshop plants

Models representing batch plants, especially flowshop facilities where all the products require the same processing sequence, have received much attention in the last decades. In particular, plant design and production scheduling have been addressed as disconnected problems due to the tremendous combinatory complexity associated to their simultaneous optimization. This paper develops a model for both design and scheduling of flowshop batch plants considering mixed product campaign and parallel unit duplication. Thus, a realistic formulation is attained, where industrial and commercial aspects are jointly taken into account. The proposed approach is formulated as a Mixed Integer Linear Programming model that determines the number of units per stages, unit and batch sizes and batch sequencing in each unit in order to fulfill the demand requirements at minimum investment cost. A set of novel constraints is proposed where the number of batches of each product in the campaign is an optimization variable. The approach performance is evaluated through several numerical examples.