润滑脂生产自动组态生产线控制研究与设计

为了解决现有润滑脂单元操作设备"一对多"或"多对一"生产线灵活多变,易发生因人工连接生产线操作失误,导致物料转移错误造成浪费等问题。提出润滑脂自动组态生产线控制方案,该方案采用批号控制策略,实现批号自动传递,保证物料只能在生产相同批号产品的单元设备之间进行传递,防止组合生产线失误,提高生产线连接的可靠性和生产效率。     

混流生产线物料索取系统的设计及实现

为完善和优化制造企业生产物流配送管理模式,结合JIT精益物流管理思想,提出了一种通过对混流生产线上短缺物料发送需求指令驱动物料配送的配料模式.设计并实现了一种基于B/S和C/S混合模式的物料索取系统,该文对系统的模型建立、功能实现以及关键技术进行了详细的阐述.该物料索取系统已应用于某企业装配生产线,试运行结果表明物料配送效率得到显著提高.     

基于FNN的水泥回转窑分解炉温度控制

在水泥工业中,窑尾分解炉温度是一个重要的工艺参数,它的稳定对整条水泥生产线的稳产、高产和节能具有重大影响.用建立对象模型的传统控制方法实现对分解炉温度的控制非常困难,因此提出了一种基于模糊神经网络的温度控制方法,将模糊控制技术与神经网络技术相结合,用神经网络表示模糊控制规则,采用神经网络来实现模糊推理,利用神经网络的学习能力来达到模糊隶属函数和模糊规则的目的.Matlab仿真试验结果表明,模糊神经网络用于回转窑分解炉温度控制可以取得比较好的控制效果.这一点在水泥厂实际生产应用中也得到了验证.     

基于云台的变域论模糊PID算法研究

为了使云台能够快速的响应环境变化从而达到动态平衡目的,提出变域论模糊PID控制算法实现调平过程中动态特性控制设计。该系统以ARM920T为控制单元,采用模糊PID算法对云台进行控制。利用MATLAB对模糊PID算法进行了仿真分析,最后对变论域、模糊及传统算法的效果进行比较：在保证动态稳定性的前提下,模糊PID算法比常规PID算法能够有效的提高响应速度。     

基于模糊控制的水泥生产线配料控制系统

在水泥生产线配料自动控制系统中,引入模糊控制策略,构建二维模糊控制器,以下料量偏差e的积分和偏差变化率作为输入量,以给定值作为输出量,对下料量进行无偏差控制.经过MATLAB仿真并应用于实际工程项目中,表明模糊配料控制系统优于PID控制系统,对水泥生产的质量提供了可靠保证,具有明显的经济效益.     

电压畸变条件下三相三线有源电力滤波器的T-S模糊∞控制

有源电力滤波器(APF)是解决电力系统谐波治理的有效方法,由于电源电压存在畸变影响了APF的补偿参考电流的检测精度并影响补偿的效果.本文采用T-S模糊控制的方法对三相三线APF进行建模,将电源电压的畸变成分作为理想情况的干扰,在保性能的前提下给定性能指标,实现T-S模糊H∞控制控制性能.在满足稳定性的要求条件下,设计的T-S模糊H∞状态反馈控制器使APF在电源电压畸变的情况下,将电源电流补偿为正弦特性,满足了APF谐波综合补偿的控制要求.仿真结果验证了所建T-S模糊模型的有效性,展示出所设计的H∞控制器的有效性能.补偿电流可以准确的检测,在电源电压非正弦条件下可以进行有效的控制.     

模糊自适应PID控制在注塑机料筒温度控制中的应用

针对某塑胶厂混合混色送料注塑成型组装生产线的生产要求,在注塑机料筒温度控制中采用模糊自适应PID控制替代原有的温度控制系统,使PID参数能够进行在线修正。仿真结果表明,模糊自适应PID控制更好地解决料筒温度控制中的多变量、强耦合、大滞后、时变等复杂情况,提高了注塑机料筒温度控制的稳定性和精确性。     

Sugeno模糊模型的辨识与控制

提出了一种新的Sugeno模糊模型辨识算法和对非线性系统进行并行化设计的方 法.在Sugeno模糊模型辨识中,应用模糊聚类方法可将其前提结构和结论参数的辨识分开进 行,减少了计算量;对于非线性系统的控制,Sugeno模糊模型实际上是动态系统的局部线性 化,可采用并行设计的方法设计控制器,然后通过模糊推理得到全局控制量.最后通过倒立摆 系统的控制说明了本文算法的有效性.     

微创手术导管机器人系统变论域模糊PID控制

在微创血管手术导管机器人系统控制机器人送导管问题的研究中,为克服手动送管的缺陷,要求导管机器人系统能够快速响应、抗干扰能力强以及对目标轨迹的实时跟踪.传统模糊PID控制由于其精度与响应速度之间的矛盾,限制了在微创手术中的应用.提出采用变论域模糊PID控制,引入伸缩因子,在不降低响应速度的前提下改善模糊PID控制精度,进一步改善系统位置跟踪精度以及在主从微创手术中的实用性.仿真结果表明,所提出的变论域模糊PID控制对系统具有快速准确的跟踪性能和较强的鲁棒性能,证实了变论域模糊PID控制在主从微刨手术中的优越性与实用性.     

电压畸变条件下三相三线有源电力滤波器的T–S模糊H∞控制

有源电力滤波器(APF)是解决电力系统谐波治理的有效方法, 由于电源电压存在畸变影响了APF的补偿参考电流的检测精度并影响补偿的效果. 本文采用T–S模糊控制的方法对三相三线APF进行建模, 将电源电压的畸变成分作为理想情况的干扰, 在保性能的前提下给定性能指标, 实现T–S模糊H∞控制性能. 在满足稳定性的要求条件下, 设计的T–S模糊H∞状态反馈控制器使APF在电源电压畸变的情况下, 将电源电流补偿为正弦特性, 满足了APF谐波综合补偿的控制要求. 仿真结果验证了所建T–S模糊模型的有效性, 展示出所设计的H∞控制器的有效性能. 补偿电流可以准确的检测, 在电源电压非正弦条件下可以进行有效的控制.     

价格波动下的生产-库存控制研究

研究原材料价格波动下多级生产-库存系统的控制问题.所有的原材料价格、半成品加工成本、成品的生产成本、库存费用率和产品的需求率都随时间变动,为此,分析了最优采购、加工、生产决策的必要和充分条件,得到了在某些假设条件下的最优生产-库存策略为JIT(Just-in-time)采购、加工、生产策略,或者为在最开始阶段以最大能力进行采购、加工、生产活动的Bang-Bang策略.     

A two-stage hybrid manufacturing model with controllable make-to-order production rates

As an effective strategy to facilitate delivering customized products within short lead time, hybrid manufacturing via a two-stage process has received attention from academia and industry. In this paper, we study a two-stage hybrid manufacturing system in which semifinished products are manufactured in a make-to-stock fashion in the first stage and end-products are produced from semifinished goods in a make-to-order (MTO) mode in the second stage. The rate of MTO production can be controlled within given limits, depending on the status of the system. The primary goal of this paper is to study a policy for coordinating order admission, MTO production rate, and inventory replenishment controls. Formulating the problem as a Markov decision process model, we characterize the structure of optimal control policies to maximize the long-run average profit. Using a numerical experiment, we study how the flexibility in MTO production rate affects the optimal policy and the optimal profit. We also examine the effect of the number of alternative MTO production rates on the optimal profit. We propose three heuristic policies implementable for general cases. The first heuristic describes two linear switching functions for admission and production controls and a selection rule for MTO production rate control. The second heuristic specifies fixed thresholds for the control decisions using the local information. The third heuristic presents linear switching functions that approximate the optimal threshold curves. Unlike second and third heuristics, the first heuristic does not require a grid search to determine the control parameters. We implement numerical studies to examine the marginal impact of system parameters and the effect of the number of alternative MTO production rates on the performance of the heuristics. Compared to the optimal policy, the average percentage performance of the first and third heuristics is less than 1% for both numerical studies. On the other hand, the average percentage performance of the second heuristic is larger than 3%, and it exceeds 10% for a set of particular problem examples.     

Inventory Minimization and Production Scheduling: the Case of a Large Hong Kong Company

The background of this study is a rather classical but complex inventory control/production planning/line scheduling problem of a major soft-drink company in Hong Kong. The issue that stands out for this many-product high-sales manufacturer is the storage space of its central warehouse, which often finds itself in the state of overflow or near capacity with finished goods and work-in-process inventory. This phenomenon can create immediate interruptions of production, capital tie-ups and subsequent potential of lost sales. Another obviously important concern is the meeting of forecast demands. A mathematical modelling approach that entails techniques of multi-period aggregate optimization is proposed to tackle the overall problem. The dual objectives are to achieve better production planning and line scheduling in order to minimize inventory build-up and maximize demand satisfaction. Numerical results for a sample problem are reported as an illustration to this proposed two-phase approach.     

变质品生产、库存控制与预防维修联合建模与优化

针对产品变质带来库存损耗的问题,在经济生产批量模型的基础上加入零库存时间,提出新的库存控制策略.该策略以预防维修周期和零库存时间为联合决策变量,利用更新定理建立了单位时间内总成本的期望模型.为了提高对此期望的计算速度,设计基于矩阵运算的蒙特卡罗仿真算法,并与遗传算法结合,大大提高了模型的优化速度.通过比较研究,验证了仿真算法的显著优势,并通过敏感性分析明确了相关参数的变化对最优策略的影响.     

基于马尔科夫决策过程的ATO系统独立组件与产品双需求最优决策研究

研究多维组件, 单一产品的双需求型面向订单装配(Assemble-to-order, ATO)系统. 产品需求为延期交货型, 当其不被满足时将产生缺货等待成本; 而独立组件需求为销售损失型, 其不被满足时将产生缺货损失成本. 该问题可以抽象成一个动态马尔科夫决策过程(Markov decision process, MDP), 通过对双需求模型求解得到状态依赖型最优策略, 即任一组件的最优生产--库存策略由系统内其他组件的库存水平决定. 研究解决了多需求复杂ATO系统的生产和库存优化控制问题. 提出在一定条件下, 组件的基础库存值可以等价于最终产品需求的库存配给值. 组件的基础库存值与库存配给值随系统内其他组件库存的增加而增加, 而产品需求的库存配给值随系统组件库存和产品缺货量的增加而减少. 最后通过数值实验分析缺货量及组件库存对最优策略结构的影响, 并得到了相应的企业生产实践的管理启示.     

Effect of product mix on multi-product pull control

Product mix influences the performance of pull production control strategy in multi-product manufacturing systems. The complexity of product mix on the performance of a manufacturing system is primarily based on the characteristics of the demand and production control strategies. Demands are mainly characterised by volume and product-type while production control strategy is characterised by material release time, part flow, inventory control and throughput times. In multi-product systems, pull production control strategy operates dedicated or shared Kanban allocation policy. This paper examines the performance of the Generalised Kanban Control Strategy (GKCS), Extended Kanban Control Strategy (EKCS) and Basestock Kanban-CONWIP (BK-CONWIP) control strategy operating Shared Kanban Allocation Policies (S-KAP) or Dedicated Kanban Allocation Policies (D-KAP) for a healthcare parallel/serial assembly line with setup times. A simulation based multi-objective optimisation technique was adopted to examine the effect of different product mixes on the strategies and policies. A ranking and selection technique for multiple systems was used to screen the performance of the strategies. It was shown that product mix variability in a system influence the inventory levels of the pull control strategies examined. However, the performances of the strategies vary with strategies operating S-KAP having better inventory control than strategies operating D-KAP. Similarly, BK-CONWIP outperformed its alternatives.     

产品随机缺陷生产系统有限时域最优生产控制

针对合格产品产量呈随机分布的单设备单产品类型不可靠生产系统,假设所生产合格产品的产量占所生产产品总量比例的概率分布已知,且产品质量检测消耗时间与生产控制时域相比较小.本文通过对目标函数的离散化,在离散空间上对生产控制策略进行寻优,得到基于当前状态下的最优生产控制策略,该策略可解析表示为合格产品产量分布、成本惩罚系数c~ (c~-)、当前状态及产品质量检测时间的函数.与同类文献所得结果相比较,该控制策略克服了文献[8]结论有可能导致系统状态发散的缺点,并且最优控制策略表达式更简洁,所得结论对实际工程应用而言有显著意义.     

Modeling an international co-operative global complementary production system

This paper aims to design a production planning and control system to realize high productivity and low inventory in the international cooperative global complementary production system for mutual country's development.     

Selecting the optimal shift numbers using fuzzy control model: a paint factory’s facility application

Number of shifts is one of the most important criteria for the production planners to minimize the production costs. The first measurement of the facility, where we executed the application, is optimizing the manpower rotation in B12 production, a special kind of chemical, which is used for paint binders. Seasonal variations in demand of B12 add more importance to the number of shifts in the facility. The purpose of this article is to optimize the shift periods subject to raw material, shipping date, inventory and demand constraints. The model is developed for a paint factory’s reactor facility. The production system has a raw material inventory, a reactor, and a finished goods inventory. We use fuzzy control to optimize the number of shifts under the constraints, given before.     

A tabu search procedure for coordinating production,inventory and distribution routing problems

This paper addresses the problem of optimally coordinating a production‐distribution system over a multi‐period finite horizon, where a facility production produces several items that are distributed to a set of customers by a fleet of homogeneous vehicles. The demand for each item at each customer is known over the horizon. The production planning determines how much to produce of each item in every period, while the distribution planning defines when customers should be visited, the amount of each item that should be delivered to customers and the vehicle routes. The objective is to minimize the sum of production and inventory costs at the facility, inventory costs at the customers and distribution costs. We also consider a related problem of inventory routing, where a supplier receives or produces known quantities of items in each period and has to solve the distribution problem. We propose a tabu search procedure for solving such problems, and this approach is compared with vendor managed policies proposed in the literature, in which the facility knows the inventory levels of the customers and determines the replenishment policies.