热轧圆钢的轧制批量计划优化模型与算法

针对热轧圆钢的轧制批量计划编制问题,以热轧圆钢的需求为导向,综合考虑热轧和加热炉阶段的工艺要求,建立了以最小化钢坯余料浪费惩罚和相邻钢坯间跳跃惩罚为目标的数学模型,并基于约束满足技术设计求解算法.算法通过变量选择和值选择规则对待轧制钢坯进行选择、分组和序列生成操作;通过约束传播技术缩减搜索空间,并划分轧制单元;同时,将装箱启发式Best Fit Decreasing (BFD)嵌入到算法中,以优化钢坯余料浪费惩罚和钢坯属性跳跃惩罚.基于实际生产数据的仿真实验表明了模型和算法的可行性和有效性.     

基于蒙特卡洛树搜索的智能天车倒垛优化方法

智能天车倒垛优化是提高钢卷库堆场利用率的重要手段,同时对提升钢铁仓库物流效率具有重要意义。针对该问题,建立最小倒垛次数为目标的天车作业负荷数学模型。在对模型求解过程中,借鉴了 Alpha Go-Zero中树搜索方法,设计了蒙特卡洛钢卷搜索树(MCRST)。为了提升搜索树的收敛速度和结果的准确性,将树的置信度上界(UCT)改为快速动作值估计(RAVE),同时引入绝对剪枝策略避免节点盲目扩展。通过不同规模算例实验,将改进算法与原树搜索和粒子群算法(PSO)进行比较,证明了该算法在大规模问题上的优越性;同时该算法也考虑了订单钢卷出库顺序和出库量等因素,验证了算法的适用性。     

基于万有引力算法的铝热连轧规程优化设计

提出了以预防打滑和平衡4个机架功率为目的的多目标函数,建立了一种基于支持向量回归机的轧制力模型来取代传统数学模型,有效地提高了轧制力预报的精度。同时采用万有引力算法对轧制规程进行优化,该算法不仅能够防止陷入局部极值点而且避免了盲目搜索,大大提高了进化速度。该规程应用在河南某厂“1+4”铝热连轧改造现场的精轧部分,轧制规程效果理想。     

基于遗传算法的热轧生产过程多目标优化

针对热轧生产过程中的板坯出库策略问题,建立了旨在减少板坯倒垛量和板坯温降程度的多目标模型;针对问题的特点,提出了基于遗传算法的求解算法.算法能够根据目标的重要性调节加权参数的大小,以便根据应用中的实际情况调整优化的重点;通过在迭代过程中引入启发式变异算子,来提高算法的收敛速度.最后通过数值实验验证了算法的可行性和有效性.     

露天矿山企业长期生产计划模型与优化算法

为了降低露天矿山企业矿产品市场销售价格及地质品位波动对长期生产计划编制的影响,首先将露天矿山生产计划周期内的矿床块体价值选取、矿岩采剥生产量以及生产成本归结为生产计划优化问题,建立了露天矿山企业长期生产计划模型。该模型以长期生产计划周期内的块体净现值最大为目标,综合考虑了企业开采处理能力、块体空间开采顺序、开采深度位置、矿石品位波动、矿产资源回收率和随机规划等约束条件;其次采用改进鸽群搜索算子的粒子群优化算法求解生产计划模型,利用Beta反向学习策略对算法种群进行初始化,同时提出线性变异和非线性变异策略优化鸽群组合搜索算子,提高算法的全局收敛速度和求解精度;最后采用随机概率搜索策略和低品位矿石处理策略,分别对矿坑内部的块体开采深度位置和矿石品位小于指定值的回采率进行优化计算。以某大型金属铜矿山为案例,结果表明该算法要比标准的粒子群算法、鸽群算法结果优于96%左右,算法的求解速度提高了50%以上,且该模型与优化算法可综合权衡露天矿山企业矿产品销售价格和地质品位波动对长期生产计划编制带来的影响。     

基于遗传禁忌算法考虑转运约束的并行机批量调度问题研究

在多品种混流生产车间里，广泛存在着各种批量的任务在多台并行机上调度优化问题。这种并行机批量调度需要考虑批量大小设置、加工顺序优化、设备充分利用等多种要素，是一类典型NP-hard问题，且当任务加工完后还需要考虑转运过程时，问题将变得更加复杂。为了减少并行机生产过程中任务拖期和在制品积压，寻求更好的生产调度方案，针对典型并行机生产和转运场景，以最小化加权完工时间及拖期工件的惩罚费用、作业切换成本、库存成本之和为优化目标，设计了基于启发式规则的仿真程序与遗传禁忌算法相结合的优化算法，研究单工序不相关并行机调度环境下车间批量调度的最优调度方案，再通过案例验证了本文优化算法的有效性。结果表明，优化算法得出的并行机批量调度方案使得作业切换次数和拖期订单大大减少，减少在制品库存的同时提高了转运资源的利用率。     

考虑疲劳效应的伤员应急手术调度模型及算法

为了解决城市突发事件应急救援中批量应急手术的调度问题,并考虑医生长时间连续手术对手术持续时间和挽救病人生命的成功率带来的恶化效应,提出了三阶段批量手术调度模型,将应急手术调度看作是存在并行机的流水车间调度问题。利用改进的飞蛾扑火算法对应急手术模型进行求解,并通过实证来测试模型和算法的有效性。为了验证算法的性能,将经典飞蛾扑火算法、粒子群算法和布谷鸟算法与其对比,取20次运行结果,得知最大手术完成时间均值中改进的飞蛾扑火算法为最小,调度模型给出的调度方案中,3个救治阶段在时间维度上保持连贯。仿真结果表明,改进的飞蛾扑火算法能很好地求解批量手术调度模型,获得较好的调度结果。     

基于改进蚁群算法的一类运输能力约束的生产-运输批量问题求解

针对生产与运输两个过程的联合决策,通过分析一类生产-运输批量优化问题,建立的混合0-1整数规划模型整合了多产品多阶段能力约束批量生产和产品运输。其中运输成本由运输工具使用数量决定,当企业内部运输能力不能满足运输需求时可将运输外包,但需支付更高的运输成本。根据此问题的特点,构造改进蚁群算法求解,令其信息素和启发信息都存在0和1两种状态下的不同取值,通过转移概率确定0-1生产准备矩阵,进一步得到生产矩阵和运输计划。仿真实验结果表明在生产批量决策的同时考虑运输,可以减少运输成本,令总费用最小,通过将实验结果与其他优化算法比较,所构造的蚁群算法寻优概率是100%,平均进化10代,平均耗时小于1 s,稳定性和求解效率均高于其他算法,是求解这类问题一种有效与适用的算法。     

面向批量订单包装的物流箱规格优化问题研究

目的 针对面向仓储物流环境下多型号多批量产品的订单包装问题,提出一种预制物流箱规格优化模型及算法。方法 对产品订单建立订单分包规则,确定分包方案,以订单包装材料总成本最小为优化目标建立物流箱规格优化模型。针对该模型提出一种改进模拟退火算法,通过贪婪策略求解最优分包方案,降低模型计算复杂度,设计一种新型解更新算子,以提高算法寻优能力,设计一种自适应步长策略,以平衡算法前期全局搜索与后期局部搜索的能力。结果 通过实例证明,文中提出的算法相较于其他算法,具有更强的求解能力,与实例企业仓储包装现状相比,同批订单降低了17%的包装材料成本。结论 该方法可用于解决产品种类多、尺寸差异大、动态更新等应用场景下的系列运输包装纸箱规格优化问题,为企业物流运输管理提供了一种有效的包装优化思路和解决方法。     

多目标快速群搜索优化算法及在模型修正中的应用

为解决群搜索算法在求解多目标优化问题时易陷于局部最优或过早收敛,限制其在复杂结构模型修正中的应用问题,提出改进的群搜索优化算法-多目标快速群搜索优化算法(MQGSO)。采用LPS搜索方法对发现者进行迭代更新,能使发现者更快到达最优位置,提升寻优效率;对追随者增加速度更新机制,考虑其自身历史最优信息以保证收敛精度,并在算法后期采用交叉变异策略增加追随者个体多样性,避免陷入局部最优;在游荡者迭代更新中引入分量变异控制策略,增加其搜索的随机性,提高算法的全局寻优性能。通过7个典型多目标优化测试函数及某发射台有限元模型修正实例,对算法性能进行验证分析。结果表明,与已有MPSO(Multi-objective Particle Swarm Optimization)及MBFO(Multi-objective Bacterial Foraging Optimization)两种算法相比,所提MQGSO算法搜索性能更强、收敛速度更快、计算精度更高,不失为求解复杂多目标优化问题的有效方法。     

Modelling and a genetic algorithm solution for the slab stack shuffling problem when implementing steel rolling schedules

Iron and steel production is a multistage process. A slab yard serves as a storage buffer between the continuous casting stage and the steel rolling mill. Slabs from continuous casting are stacked in the yard to await rolling. When implementing the rolling production schedule, slabs need to be picked up from the slab yard one by one according to the scheduled rolling sequence, heated in the heating furnace and then rolled. There are usually a number of suitable candidate slabs in the yard satisfying the requirement for each rolling item. In general, these candidate slabs are not at the most convenient positions in the stacks. To pick up a required slab, the slabs above it need to be shuffled. To save slab-handling cost and prevent the handling cranes from becoming a bottleneck, slabs for a rolling schedule must be selected from among the candidate slabs so that the total number of slabs shuffled is minimized. The paper studies the slab stack-shuffling problem using the hot strip rolling mill in Shanghai Baoshan Iron and Steel Complex as an application background. We first formulate the problem using an integer-programming model and then develop a modified genetic algorithm to solve it. Genetic codes and genetic operators are specially designed to ensure the feasibility of solutions and to speed up the solution process. The algorithm is implemented and compared with the existing algorithm that the mill has been using. Experiments on randomly generated problems show that the proposed new method reduces the number of slab shuffles by 11.19% on average.     

Prevention of Scum Formation and Entrapment in High Carbon Steel Billets

Gradual build-up of scum over the liquid steel surface in the mould gives rise to entrapped exogenous inclusions and slag patch in the cast billets. The problem is more commonly observed during the open stream casting of continuous casting of high carbon (C > 0.6 mass%) steel billets. This problem has been quite commonly observed at Tata Steel during its billet casting. Present work aimed at eliminating the problem of scum formation during open stream billet casting of high carbon steel billets. This work involved experiments in the laboratory as well as in the plant. In addition, based on liquid steel composition thermodynamic calculations were carried out for predicting the possible oxide inclusions in Mn-Si deoxidised steels. Water model experiments were carried out in a full-scale billet caster physical model for investigating the influence of tundish outlet nozzle alignment on the entrapment of scum as slag patch over the billet surface. Based on these, cause of scum formation and its exact mechanism of entrapment in cast billets were established. Finally, countermeasures were recommended to the plant. Adequacy of the proposed countermeasures was established through a series of trials in the plant before implementation. Improvement obtained from the implementation over a period of time has been reported in the paper.

     

连铸坯中心偏析和疏松缺陷在轧制过程中的形态演化

连铸坯的中心偏析和疏松缺陷形态经轧制后会发生演化,合理选择轧制压缩比可以达到减轻或消除铸坯缺陷的效果。利用宏观检验、硬度测试、金相检验和密度测定等方法对典型的合金钢和普碳钢两种300mm厚连铸坯经不同压缩比轧制后其中心偏析和疏松缺陷的形态演化进行了分析。结果表明：在常规轧制工艺下,当轧制压缩比小于4时,连铸坯仅在板厚的上、下1／3厚度位置发生明显塑性变形,中心部位的偏析和疏松缺陷形态不会发生变化。压缩比达到5以上时,1．5级的中心疏松缺陷才得以轧合,但1．5级的中心偏析缺陷只能适度减轻。     

大塑性变形的AM60镁合金半固态等温处理研究

为了制备晶粒细小且球化程度高的的AM60镁合金半固态坯料,对铸态和等径道角挤压态的AM60镁合金半固态等温处理过程进行了研究.借助金相显微镜对AM60镁合金铸坯和等径道角挤压后的铸坯在半固态等温处理中的微观组织演变进行了观察.研究结果表明:对于AM60镁合金,直接等温处理获得的半固坯晶粒很粗大,其平均晶粒尺寸都在100μm以上,晶粒球化效果不理想,很难获得合格的半固态坯;新SIMA法是一种非常理想制备AM60镁合金半固态坯的方法,利用该方法制备的AM60半固态坯的微观组织晶粒十分细小,平均晶粒尺寸在8～22μm,晶粒球化程度高;随着保温时间的延长,新SIMA法制备的AM60半固态坯的微观组织出现长大现象;随着等温处理温度的升高,固相晶粒的平均尺寸先增加后减小,晶粒球化程度越来越高.     

Effect of Al-6063 Billet Quality on the Service Life of Hot Extrusion Die: Metallurgical and Statistical Investigation

The current paper presents results about the effect of Al-6063 billet quality on the service life of AISI-H13 hot extrusion dies based on microstructural and statistical investigation. In the first half of the paper, secondary (remelt) billet cast in-house at local extrusion plant is compared with two sources of primary (smelter) billet by applying different material characterization techniques including optical microscopy, hardness measurement, x-ray diffraction (XRD) analysis, and energy-dispersive spectroscopy (EDS). The second half of the paper evaluates the performance of primary and secondary billet types based on statistical analysis of data collected on 53 hollow-profile dies from a local commercial extrusion setup. It was observed that the secondary billet has a comparatively coarse grain structure, nonhomogeneous distribution of secondary phases, and high hardness that can be associated with poor casting and homogenization practice. Statistical analysis covers overall analysis of collected data followed by detailed study of percentagewise use of billet quality in terms of die profile complexity/extrusion ratio. Analysis has shown that dies extruding a high percentage of secondary billets are more susceptible to early die failure on overall basis. For more complex dies with high extrusion ratio, average die life further reduces with increased percentage of secondary billet usage. Regression models are also proposed for prediction of die life in terms of secondary billet usage and extrusion ratio. Considering results of present microstructural and statistical analysis, some suggestions during in-house billet preparation of secondary billets have been formulated to prevent early die failure.     

新型圆坯结晶器铜管结构模拟优化设计

为优化设计新型圆坯结晶器铜管结构,提高结晶器寿命和铸坯质量,利用商业有限元软件ANSYSTM建立二维连铸结晶器内钢水凝固传热及弹塑性应力有限元瞬态分析模型,铸坯传热边界采用与气隙相关的热流密度修正函数,建立与温度相关的热物性参数、力学性能和屈服函数,并利用多场间接耦合的方式对不同工况下的4种圆坯在结晶器内的凝固收缩变形过程进行数值模拟.结果表明,钢种和工况条件对铸坯边界凝固收缩过程影响显著,6瓣模型为4种计算模型的最优形状,依据铸坯边界凝固收缩曲线和新型结晶器设计准则,新型结晶器铜管结构设计采用凸型花瓣状内腔和大锥度设计.     

A robust optimization approach for integrated steel production and batch delivery scheduling with uncertain rolling times and deterioration effect

Efficient collaboration between various sub-processes of steel production is of considerable significance, which directly affects a product’s production cycle and energy consumption. However, current collaborative optimisation models and methods in steel production are still limited: (1) Most of the current collaborative manufacturing problems in steel production focus on obtaining joint schedule between steel-making and continuous casting (SCC), and the works considering continuous casting and hot rolling (CCHR) are very few. (2) The processing time is assumed as a constant in most of the existing SCC scheduling models. However, the rolling time of a product in hot rolling operation is actually uncertain and deteriorating. (3) Exact algorithms cannot be applied to solve the complicated collaborative optimisation problems because of their high complexities. To address these problems, we propose an integrated CCHR and batch delivery scheduling model where interval rolling time and linear deterioration effect are considered. With the concept of min–max regret value, we formulate the collaborative optimisation problem as a robust optimisation problem. Instead of using the exact algorithm, we develop an Improved Variable Neighborhood Search (IVNS) algorithm incorporated a novel population update mechanism and neighbourhood structures to solve the robust optimisation problem. Moreover, we develop an exact algorithm that combines CPLEX solver and two dynamic programming algorithms to obtain the maximum regret value of a given rolling sequence. The results of computational experiments show the excellent performance of the proposed algorithms.

Abbreviations: IVNS: improved variable neighbourhood search; TOPSIS: technique for order of preference by similarity to ideal solution; PUM-TOPSIS: population update mechanism based on TOPSIS; DP: dynamic programming; NSs-PUC: neighbourhood structures based on the parameterised uniform crossover; SNRT: shortest normal rolling time; SNRT-DP: DP algorithm based on SNRT rule; BRKGA: biased random-key genetic algorithm; SCC: steelmaking and continuous casting; MINP: mixed integer nonlinear programme; CCHR: continuous casting and hot rolling; PSO: particle swarm optimisation; GA: genetic algorithm; VNS-HS: variable neighbourhood search and harmony search; HPSO?+?GA: hybrid PSO and GA; SA: simulated annealing; B&B: branch-and-bound; TPSO: two-phase soft optimisation; TSAUN: tabued simulated annealing with united-scenario neighbourhood; VNS: variable neighbourhood search; ABC: artificial bee colony; PRVNS: population-based reduced variable neighbourhood search; NS1: neighbourhood structure 1; NS2: neighbourhood structure 2; DE: differential evolution; WSR: Wilcoxon signed-rank test; ENS: exchange neighbourhood structure; IVNS-ENS: IVNS with ENS; RPI: relative percentage increase; ARPI: average RPI; SD: standard deviation.     

Computational Intelligence-Based Process Optimization for Tandem Cold Rolling

The requirements for the manufacturers of steel have been increased in many respects in recent years. Harsh competition among manufacturers demands a continuous reduction of production costs and improvement of product quality. The work presented herein describes maximizing rolling mill throughput and minimizing processing costs and crop losses by computational intelligence-based process modeling and optimization. In this article, an intelligent searching mechanism is introduced to optimize the rolling schedule by assessing rolling constraints and the combined cost function of tension, shape, and power distribution. The optimization results have been compared with current rolling practices based on empirical models. It is shown that the proposed model can significantly reduce the power distribution cost, maximize the safe level of strip tension, and obtain good strip shape. The proposed model is generic for complex engineering problem optimization, and is capable of multiple-objective problem solving.     

Computer-aided roll pass design for continuous billet mill

A mathematical model has been developed for computing the geometrical dimensions of square-diamond square pass sequence for a continuous billet mill. The model is based on derivation of shape and size factor from the geometry of the pass taking into account pass filling, pass rounding etc. Using these factors and a basic equation of spread for flat rolling, a governing equation incorporating angle of diamond and reduction in consecutive passes has been formulated. Newton’s substitution method has been used to solve the equation. With known reduction between consecutive passes, geometrical dimension of square and diamond passes are computed. A model has been used to calculate pass design of a finishing train of a continuous billet mill producing 60 mm square billet from 120 mm square bloom. The elongation values have been optimized by varying the apex angle of diamond. A close agreement between computed and actual values shows the validity of the model.     

空心管坯软接触电磁连铸技术研究

提出空心管坯软接触电磁连铸方法,以Sn-3.5%Pb合金为模拟金属,采用激光实测的方法研究了不同电源功率下弯月面形状,并进行了空心管坯软接触电磁连铸实验.研究表明:施加中频电磁场,管坯型腔内熔体形成具有一定高度的悬浮液柱;功率增加,弯月面隆起高度增加,金属熔体与外结晶器之间的接触角增大,接触点位置降低,对金属熔体与内结晶器之间的接触角影响不大,与内结晶器的接触点上升;与普通连铸空心管坯相比,软接触电磁连铸空心管坯的表面质量光洁,凝固组织得到显著细化.