六角打包带制作机

六角打包制作机的设计是针对钢管厂六角包装带制作不能满足生产现场对打包带需求而设计的，在本设备制作后，六角包装带的制作完全满足了要求。本设备设计主要内容是实现制作工艺的自动化来替换原有的人工制作工艺，实现生产效率的提高，满足生产需要。     

综采跟机自动化系统分析与建模

采用电液控制系统的综采或综放工作面,按照采煤工艺的要求,根据采煤机的牵引位置对工作面三机进行自动控制。利用机电一体化技术,制定液压支架护帮板收伸、自动喷雾、移架和刮板运输机移动等自动化动作规则,建立跟机自动化离散系统模型。为采用自动化技术的采煤工作面研究了一种新的、先进的半截深采煤工艺,并进行了工艺的计算机分析设计。     

基于PCS7的铜钴回收冗余控制系统设计

针对新型铜钴回收工艺仍然处于人工手动操作、自动化程度低的问题,该文在西门子PCS7过程控制系统下设计铜钴回收冗余控制系统对整个生产流程进行自动化监控,针对铜钴回收浓密机工艺机理复杂,操作环境恶劣,具有大惯性、非线性以及来料性质波动频繁等缺点,分析浓密机的结构,设计浓密机的参数自整定模糊PID控制.通过在青海某矿业集团50万吨铜钴回收项目的实际应用证明,该系统能很好地满足控制要求.浓密机运行安全可靠,提高了综合回收效率,减轻了劳动强度,实现了安全稳定的自动化生产.     

自动化控制技术在机床上下料中的应用分析

为了适应大批量重复性工件加工工艺以及恶劣工作环境,随着科学技术发展以及企业对设备自动化程度要求提高,越来越多的自动化技术被应用于机加车间。本文分析了基于工业机器人的机床上下料自动化控制技术应用,通过工业机器人与相机的配合,并以PLC为控制核心,实现各加工机床的相互协作。自动化控制技术的使用为机加企业提供了重复定位精度高、可靠性高、生产柔性化及自动化程度高的设备,使人力从生产岗位解脱出来,能够提高工件生产质量,全面提升工件加工生产效率。     

立体仓库巷道堆垛机控制系统设计

为了改进立体仓库巷道堆垛机的控制系统性能,设计制作了自动化立体仓库和三自由度单立柱巷道堆垛机实体模型。在此基础上,提出了基于ARM微处理器的立体仓库巷道堆垛机控制方案。详细讨论了控制系统的整体结构和硬件电路设计,阐述了控制系统的软件设计过程。实际运行效果表明,该控制方案提高了巷道堆垛机的运行可靠性和准确性,较好地满足了自动化仓储系统的作业需求,是一种新颖的巷道堆垛机控制方案。     

制药厂污水处理自动控制系统的实现

根据制药厂对污水处理的工艺要求,采用PC机和PLC组成网络控制。为提高系统可靠性,用两台工控机作为上位机,PLC作为下位机,控制现场设备运行。上位机与PLC之间采用MPI和工业以太网通信,从站与CPU之间用PROFIBUS总线通信。介绍了一种简便实用的PLC编程方式。本系统解决了制药厂设备分散,难以控制的难题,大大提高了污水处理的自动化水平。     

综采工作面中部跟机自动化控制的数学模型

针对综采工作面的双向割煤生产作业特点,分析了采煤机、液压支架、刮板输送机联合运转时的协调控制过程,根据采煤生产作业中刮板输送机弯曲段形成原理,提出了刮板输送机弯曲段形成的数学模型;在该模型基础上,分析了工作面中部液压支架跟机自动化作业的工艺过程,提出了综采工作面中部跟机自动化控制数学模型;根据该综采工作面中部跟机自动化控制数学模型,对某煤矿3107综采工作面相关参数进行了计算,并总结了3107综采工作面中部跟机自动化生产的经验。应用结果表明,综采工作面中部跟机自动化控制的数学模型与跟机自动化工艺过程相吻合,为进一步实现智能化综采工作面提供了理论基础。     

基于单片机和VB的玻璃拉丝测控系统

针对中小工厂拉丝工艺较低的自动化程度,介绍了一种用AT89S52,PIC16F628A单片机控制的和用Visual Basic设计的实时监控界面的玻璃拉丝测控系统。叙述了该系统的软硬件组成,着重介绍了上位机,以及下位机与它之间的通信。经现场运用表明,系统运行情况良好,满足了所要求的功能和精度,且使用维护方便。     

基于单片机和VB的玻璃拉丝测控系统

针对中小工厂拉丝工艺较低的自动化程度,介绍了一种用AT89S52,PIC16F628A单片机控制的和用Visual Basic设计的实时监控界面的玻璃拉丝测控系统。叙述了该系统的软硬件组成,着重介绍了上位机,以及下位机与它之间的通信。经现场运用表明,系统运行情况良好,满足了所要求的功能和精度,且使用维护方便。     

伴舞机器人（上）

在这一年中,我们将通过完成彩星工艺盒、循迹小车、跳舞小车、变速小车、搬运机器人、掌上FLASH等8个制作,来学习单片机系统的设计与制作。读者跟着学习完成这8个项目的制作,就基本掌握了单片机的软硬件设计思想和方法,学会单片机的汇编语言和C语言编程。读者掌握了这些知识和技能,就可以胜任单片机系统开发、小型自动化产品开发和智能产品开发等岗位的基本要求,还可以从事自动化设备的维修工作。     

Distributed adaptive control of production scheduling and machine capacity

This paper considers modeling and simulation of a unified control system that uses a continuous control-theoretic approach for distributed production scheduling at the shop floor and machine capacity control at the CNC level. Specifically, a distributed production scheduling method is unified with a distributed machine capacity control to generate realistic schedules considering the available capacity of production resources. In this distributed control system, machine capacity is adaptively controlled based on current physical conditions of the production resources and changes in production demands at the shop-floor level as well. The proposed system considers a multi-attribute objective that consists of production rate and product quality, production cost, and mean-squared deviation of job completions about due dates. The results obtained from the computational experiments show that the proposed system can improve the system performance through fully utilizing machine capacity while reducing production costs, production delays, missed deliveries, and customer dissatisfaction.     

Computational aspects of an extended EMQ model with variable production rate

The paper considers a generalized economic manufacturing quantity (EMQ) model with stochastic machine breakdown and repair in which the time to machine failure, corrective and preventive repair times are all assumed to be random variables. The model is formulated under general failure and general repair time distributions, treating the machine production rate (speed) as a decision variable. As the stress condition of the machine changes with the production rate, the failure rate is assumed to be dependent on the production rate. The model is further extended to the case where certain safety stocks are hold in inventory to protect against possible stockout during machine repair. The solution procedure and computational algorithms of the associated constrained optimization problems are provided. Numerical examples are taken to determine the optimal production policies by the proposed algorithms and examine the sensitivity of the model parameters.Several economic manufacturing quantity (EMQ) models for unreliable manufacturing systems have been developed in the literature even for general failure and general repair (corrective) time distributions. In these studies, preventive repair has not been considered in a general way and efforts have been made to derive the production control and maintenance policy for inflexible manufacturing systems, where the machine capacity is pre-determined. The purpose of this article is to formulate a generalized EMQ model for a flexible unreliable manufacturing system in which (i) the time to machine failure and repair (corrective and preventive) times follow general probability distributions and (ii) the machine failure rate is dependent on the production rate. Consideration of a variable production rate makes the model hard to analyze completely. So, attempt has also been made to get into its computational aspects by developing solution algorithms.     

Optimal lot sizing in an unreliable two-stage serial production–inventory system

This paper deals with a two‐stage lot sizing problem in an unreliable production environment in which the machine at the first stage (stage 1) is failure‐prone while the machine at the final stage (stage 2) is failure‐free. The process goods are obtained in batches by manufacturing and are transferred continuously from stage 1 to stage 2 where the finished goods are produced and then shipped out to customers. If the machine at stage 1 breaks down then the production of the interrupted lot is not resumed. Instead, a new production cycle is initiated after machine repair. The model is formulated assuming that the production rate of the machine at stage 1 is greater than that at stage 2 and the time to machine failure and repair time are arbitrarily distributed. Specific formulation of the model under exponential failure and exponential repair time distributions is derived and a procedure for finding the optimal production policy is presented. The dependence of the optimal production policy on the model parameters is also examined with numerical examples.     

基于复杂网络的生产系统瓶颈簇识别方法

在生产过程中,瓶颈会制约生产系统的有效产出。针对单瓶颈的识别方法难以识别出生产系统中可能同时存在多个瓶颈的问题,提出了Ⅰ、Ⅱ、Ⅲ级瓶颈簇的识别方法。同时,为应对机器的评价属性值是不确定值的情况,采用了区间型式描述机器的评价属性。但区间型描述会带来较大的计算量。为此引入复杂网络,构建了生产系统的有向加权网络模型。通过分析网络的拓扑特性,筛选出候选瓶颈机器群后再进行分析计算,以减少区间型描述带来的较大计算量。再对候选瓶颈机器群从机器利用率、机器平均活跃率和单机器总能耗三方面进行综合评价及排序,最后采用模糊C均值算法划分出Ⅰ、Ⅱ、Ⅲ级瓶颈簇。     

Fuzzy Bayesian reliability and availability analysis of production systems

To have effective production planning and control, it is necessary to calculate the reliability and availability of a production system as a whole. Considering only machine reliability in the calculations would most likely result unmet due dates. In this study, a new modelling approach for determining the reliability and availability of a production system is proposed by considering all the components of the system and their hierarchy in the system structure. Components of a production system are defined as production processes; components of the processes are defined as sub-processes. In this hierarchical structure we could model all kinds of failures such as material and supply, management and personnel, and machine and equipment. In the analysis, a fuzzy Bayesian method is used to quantify the uncertainties in the production environment. The suggested modelling approach is illustrated on an example. In the example, also a separate reliability and availability analysis is conducted which only considered machine failures, and the results of both analyses are compared.     

Modelling the startup of machine tools for energy efficient multi-sleep control policies

Energy efficient control strategies have been of recent interest in literature as promising measures to reduce the energy consumed by production equipment during interruptions of part flow. A general time-based control policy is analyzed. Machine idle times are assumed stochastic and the expected value of the energy consumed per produced part is reduced while assuring a certain target of expected production rate. The startup time required to resume the service depends on the time period the machine stays in a low power consumption state. Since the startup is often related to one or more machine components, the optimal policy might be to partially switch the machine. Therefore, a policy acting at component level is also analyzed where the duration of the startup depends on the set of machine components that are switched off. The policy is compared to state-of-the-art policies and discussed for a set of simulated numerical cases representing several production environments.     

Stochastic manufacturing system with process deterioration and machine breakdown

This paper presents a realistic manufacturing inventory model with process deterioration and machine breakdown. In economic manufacturing quantity model, process usually starts with ‘in-control’ state and produces items of good quality. After some random point of time, process may deteriorate and shift to ‘out-of-control’ state due to occurrence of assignable cause. From that point, process produces some percentage of non-conforming items. Further process deterioration after machine shift may result in machine breakdown at any random time during the production period. If machine breakdown occurs during the production period, then corrective (emergency) repair is performed immediately otherwise preventive (regular) repair is performed at the end of production period. The proposed model is formulated assuming that the time required for production facility shifting from ‘in-control’ state to ‘out-of-control’ state, time when machine breaks down, corrective and preventive repairing time and demand of items follows probability distribution. We have derived analytically the optimal production time which minimises the total expected production cost annually for machine breakdown and no machine breakdown cases. The solution procedure is illustrated with the help of numerical examples for different probability distributions. Sensitivity of the optimal solution with respect to different parameters are also analysed.     

Design of robust cellular manufacturing system for dynamic part population considering multiple processing routes using genetic algorithm

In this paper, a comprehensive mathematical model is proposed for designing robust machine cells for dynamic part production. The proposed model incorporates machine cell configuration design problem bridged with the machines allocation problem, the dynamic production problem and the part routing problem. Multiple process plans for each part and alternatives process routes for each of those plans are considered. The design of robust cell configurations is based on the selected best part process route from user specified multiple process routes for each part type considering average product demand during the planning horizon. The dynamic part demand can be satisfied from internal production having limited capacity and/or through subcontracting part operation without affecting the machine cell configuration in successive period segments of the planning horizon. A genetic algorithm based heuristic is proposed to solve the model for minimization of the overall cost considering various manufacturing aspects such as production volume, multiple process route, machine capacity, material handling and subcontracting part operation.     

Data-Enabled Modeling and Analysis of Multistage Manufacturing Systems with Quality Rework Loops

In a multistage serial production line, multiple inspection stations and repair processes are typically involved to ensure high product quality. Quality rework is the activity to repair or repeat the work on the defect parts during manufacturing processes. The rework process after each inspection can add cost and cycle time to the normal process and impose negative impact on the throughput. This paper studies real-time performance of multistage serial manufacturing systems with quality rework loops and machine random failures. A production line with multiple quality rework loops is first unify by segmenting it into a set of serially connected quality rework loops. An event-based data-enabled mathematical model is developed to evaluate real-time production rate of each machine for such a system. In addition, the system properties are analyzed and permanent production loss due to quality rework loops and random machine failures are identified respectively. The permanent production loss attribution to each disruption event and machine can be used as real-time performance indicators to diagnose production system inefficiency. The mathematical model and system performance identification methodology are studied analytically and validated through numerical case studies.     

Integrated production scheduling and maintenance policy for robustness in a single machine

This paper addresses the problem of finding robust production and maintenance schedules for a single machine with failure uncertainty. Both production and maintenance activities occupy the machine׳s capacity, while production depletes the machine׳s reliability and maintenance restores its reliability. Thus, we propose a proactive joint model which simultaneously determines the production scheduling and maintenance policy to optimize the robustness of schedules. Then, a three-Phase heuristic algorithm is devised to solve the mathematic model. Computational results indicate that the performance of solution can be significantly improved using our algorithm compared with the solutions by the traditional way. Furthermore, the balance of quality robustness and solution robustness and the impact of jobs׳ due dates are explored in detail.