Dynamic cellular manufacturing systems design��a comprehensive model

This paper addresses the dynamic cell formation problem (DCF). In dynamic environment, the product demand and mix changes in each period of a multiperiod planning horizon. It causes need of reconfiguration of cells to respond to the product demand and mix change in each period. This paper proposes a mixed-integer nonlinear programming model to design the dynamic cellular manufacturing systems (DCMSs) under dynamic environment. The proposed model, to the best of the author??s knowledge, is the most comprehensive model to date with more integrated approach to the DCMSs. The proposed DCMS model integrates concurrently the important manufacturing attributes in existing models in a single model such as machine breakdown effect in terms of machine repair cost effect and production time loss cost effect to incorporate reliability modeling; production planning in terms of part inventory holding, part internal production cost, and part outsourcing; process batch size; transfer batch size for intracell travel; transfer batch size for intercell travel; lot splitting; alternative process plan, and routing and sequence of operation; multiple copies of identical copies; machine capacity, cutting tooling requirements, work load balancing, and machine in different cells constraint; machine in same cell constraint; and machine procurements and multiple period dynamic cell reconfiguration. Further, the objective of the proposed model is to minimize the sum of various costs such as intracell movement costs; intercell movement costs and machine procurement costs; setup cost; cutting tool consumption costs; machine operation costs; production planning-related costs such as internal part production cost, part holding costs, and subcontracting costs; system reconfiguration costs; and machine breakdown repair cost, production time loss cost due to machine breakdown, machine maintenance overheads, etc. ,in an integrated manner. Nonlinear terms of objective functions are transformed into linear terms to make mixed-integer linear programming model. The proposed model has been demonstrated with several problems, and results have been presented accordingly.     

A novel hybrid method for supply chain optimization with capacity constraint and shipping option

In a modern market, supply chain network design is considered as a strategic decision that provides the proper platform for cost management and increases the competitive edge of enterprise. In a five-tier supply chain, there are several facilities such as suppliers, manufacturers, warehouses, distribution centers, and retailers or customers. For product transportation from one facility to another, different types of options may be used. These options have variety price and the manager should do the best assignment to reduce the total cost. In this paper, we formulated an integer programming model for a five-tier supply chain with capacitated facility and multiple transportation option with fixed lead time. We also proposed a novel meta-heuristic solution methodology that combines the Taguchi's feature with artificial immune approach in order to solve the proposed model. The performance of the proposed solution methodology has been examined against a set of numeric instances and the obtained results are compared with those provided by hybrid genetic algorithm and Taguchi and artificial immune system. Results indicate that this methodology can make better results than previous solutions effectively.     

面向混联机床的机械系统容错重构规划方法研究

提出了一种机械系统可重构的混联机床,研究了混联机床机械系统的容错重构策略,提出了基于机构类型演化的机械系统重构容错新方法,给出了球铰演化为虎克铰的实施方案.导出了故障和非故障状态下混联机床的位置反解算法,在ADAMS平台中进行了仿真分析和研究,得到了容错重构前后自旋角的变化曲线以及各驱动腿的长度和工作台位移的变化曲线.仿真结果表明,利用混联机床的机械系统可重构性能可以提高混联机床的可靠性和安全性.     

敏捷制造模式下制造单元重构技术研究

为了实现敏捷制造环境下异地分布资源的优化组合，分析了敏捷制造系统构建中设备间运输工件的时间成本、异地管理的额外成本以及制造资源多样性造成的多种可行工艺路径方案等多种因素，提出了敏捷制造系统的构建模型，并由此给出了以制造总成本最小为目标函数的敏捷制造单元重构数学模型，提出了敏捷制造系统构建的实现算法。最后，通过具体实例验证了该模型的有效性。     

基础装备制造及高档集成数控机床研究进展

为解决航空航天制造领域面临的关键问题以及提高机床行业的服务能力,机床行业提出建设航空航天制造领域高档数控机床创新能力平台。总结了创新平台的基础装备制造及高档数控机床的四个方面研究进展,包括电主轴单元技术（高速主轴刀柄刀具系统动力分析、数字化仿真和样机模态验证分析）、机床设计（直线轴进给系统刚柔耦合机电耦合动力学、多轴联动与高速五坐标混联加工装备、摆动/回转进给系统的机电耦合动力学模型验证分析、MTC1000镗铣磨复合加工中心结构创新设计）、机床控制（高速启停残留振动抑制技术验证分析）和机床验证（航空航天结构件高速加工现场的数据采集、映射与存储技术分析）。最后展望了基础装备制造和高档数控机床的发展方向。     

Bidding-based multi-agent system for integrated process planning and scheduling: a data-mining and hybrid tabu-SA algorithm-oriented approach

This paper conceptualizes a bidding-based multi-agent system for solving integrated process-planning and scheduling problem. The proposed architecture consists of various autonomous agents capable of communicating (bidding) with each other and making decisions based on their knowledge. Moreover, in contrast to the traditional model of integrated process-planning and scheduling problem, a new paradigm has been conceptualized by considering tool cost as a dynamic quantity rather than a constant. Tool cost is assumed to comprise tool-using cost and its repairing cost. The repairing cost is considered to depend on the tool-breaking probability, which is predicted by the data-mining agent equipped with the virtues of C-fuzzy decision tree. When a job arrives at the shop floor, the component agent announces a bid for one feature at a time to all the machine agents. Among the machine agents capable of producing the first feature, one comes forward to become a “leader”, and groups other machine agents for the processing of remaining features of the job. Once all features are assigned to the appropriate machines, the leader then sends this allocation information to the optimization agent. The optimization agent finds optimal/near-optimal process plans and schedules via the hybrid tabu-SA algorithm.     

Effect of reconfiguration costs on planning for capacity scalability in reconfigurable manufacturing systems

In a globally competitive market for products, manufacturers are faced with an increasing need to improve their flexibility, reliability, and responsiveness to meet the demands of their customers. Reconfigurable manufacturing systems (RMS) have become an important manufacturing paradigm, because they broadly encompass the ability to react efficiently to this environment by providing the exact capacity and functionality needed when needed. This paper studies how such new systems can manage their capacity scalability planning in a cost effective manner. An approach for modeling capacity scalability planning is proposed. The development of the model is based on set theory and the regeneration point theorem which is mapped to the reconfigurable manufacturing paradigm as the capacity scalability points of that system. The cost function of the model incorporates both the physical capacity cost based on capacity size and costs associated with the reconfiguration process which referred to as the scalability penalty cost and scalability effort cost. A dynamic programming (DP) approach is manipulated for the development of optimal capacity scalability plans. The effect of the reconfiguration costs on the capacity scalability planning horizon and overall cost is investigated. The results showed the relation between deciding on the optimal capacity scalability planning horizon and the different reconfiguration costs. Results also highlighted the fact that decreasing costs of reconfiguration will lead to cost effective implementation of reconfigurable manufacturing systems.     

Dynamic cell formation and the worker assignment problem: a new model

In this paper a new model is developed to deal with a simultaneous dynamic cell formation and worker assignment problem (SDCWP). Part routing flexibility and machine flexibility and also promotion of workers from one skill level to another are considered. The proposed model is formulated as a single objective nonlinear integer programming which is converted to a linear one. The objective function consists of two separate components. The first part of the objective function is related to machine-based costs such as production cost, intercell material handling cost, machine costs in the planning horizon. The second part is related to human issues and consists of hiring cost, firing cost, training cost and salary. It is the first time that worker assignment and dynamic cell formation are considered simultaneously. To verify the performance of the proposed model, some numerical examples are presented. Computational and sensitivity analysis results imply the significance of SDCWP.     

Design of a five-axis ultra-precision micro-milling machine—UltraMill. Part 2: integrated dynamic modelling, design optimisation and analysis

Using computer models to predict the dynamic performance of ultra-precision machine tools can help manufacturers to substantially reduce the lead time and cost of developing new machines. However, the use of electronic drives on such machines is becoming widespread, the machine dynamic performance depending not only on the mechanical structure and components but also on the control system and electronic drives. Bench-top ultra-precision machine tools are highly desirable for the micro-manufacturing of high-accuracy micro-mechanical components. However, the development is still at the nascent stage and hence lacks standardised guidelines. Part 2 of this two-part paper proposes an integrated approach, which permits analysis and optimisation of the entire machine dynamic performance at the early design stage. Based on the proposed approach, the modelling and simulation process of a novel five-axis bench-top ultra-precision micro-milling machine tool—UltraMill—is presented. The modelling and simulation cover the dynamics of the machine structure, the moving components, the control system and the machining process and are used to predict the entire machine performance of two typical configurations.     

Manufacturing e-quality through integrated web-enabled computer vision and robotics

This paper investigates the development of a Web-based quality control system with the use of Internet-based computer machine vision. Such a system allows designers located far from the production facility to monitor, control, and program the quality inspection process as the product design evolves. Quality control tasks are performed and monitored remotely through the Web where Internet-based machine vision sensors inspect part dimensions and tolerance while Internet-enabled robots perform the necessary robotic operations. The remote quality monitoring system—which lets the user monitor the part status including data, image, and video through the Internet—is built using Java. The use of Java allows for interconnection and data transfer between the different components of the Web-based quality system and the robots. The ability to access and control quality control devices via the Web benefits the current manufacturing environment in the following ways: ubiquitous access to the production floor, remote control/programming/monitoring capability, and integration of production equipment into information networks for improving efficiency and product quality.     

Design principles of reconfigurable machines

Reconfigurable machines form a new class of machines that are designed around a specific part family of products and allow rapid change in their structure. They are designed to allow changes in machine configuration according to changes in production requirements. The reconfiguration may be related to changes in machine functionality or its scalability, i.e., the change in production volumes or speed of operation. Reconfigurable machines represent a new class of machines that bridges the gap between the high flexibility and high cost of totally flexible machines and the low flexibility and low cost of fully dedicated machines. The design principles of reconfigurable machines follow a similar philosophy, which was derived for reconfigurable manufacturing systems, and present an approach for the design of machines to be used mainly in high-volume production lines. This paper introduces design principles for reconfigurable machines, which may be applied in different fields of manufacturing. Based on these design principles, three types of reconfigurable machines were designed for various types of production operations such as: machining, inspection and assembly. This paper shows how the suggested design principles were utilized in the design of several full-scale machine prototypes and tested experimentally.     

A review of intelligent approaches for designing dynamic and robust layouts in flexible manufacturing systems

Facility layout problem is associated with the arrangement of facilities in a plant. It is a critical issue in the early stages of designing a manufacturing system because it affects the total manufacturing cost significantly. Dynamic and robust layouts are flexible enough to cope with fluctuations and uncertainties in product demands in volatile environment of flexible manufacturing systems. Since the facility layout is a hard combinatorial optimization problem, intelligent approaches are the most appropriate methods for solving the large size of this problem in reasonable computational time. In this paper, first of all, dynamic and robust layouts are surveyed. After a quick look of different mathematical models, including quadratic assignment, quadratic set covering, mixed integer programming, and graph theoretic models, the various solution methods especially intelligent approaches along with their advantages and disadvantages are surveyed. Finally, after review of hybrid algorithms, the conclusion of this paper is reported.     

Optimization of the multi-objective dynamic cell formation problem using a scatter search approach

This paper addresses the dynamic cell formation (DCF) problem with multiple conflicting objectives. Recent researches have mainly focus on single-objective cell formation procedures that deals with the identification of part families and associated machine groups for constant demands. However, varying market demands and fluctuations of the business environment have caused cellular manufacturing systems to operate under dynamic conditions. Thus, the optimal configuration of manufacturing cells in each period is different and the reconfiguration of cells is required. This paper proposes a nonlinear multi-objective mathematical model of the DCF problem by giving weighing to three conflicting objectives including the machine relocation cost in the process of reconfiguring cells, the utilization rate of machine capacity, and the total number of intercell moves over the entire planning horizon. To solve the nonlinear multi-objective model, a scatter search approach is developed, which redesigns the common components of scatter search and incorporates diversification generator, global criterion method, local search method, and other improvement mechanisms to provide a wide exploration of the search space through intensification and diversification. The proposed approach is compared with the commercial solver CPLEX on 10 test problems, some of which are large dimensions. Computational results have demonstrated the effectiveness of the scatter search approach.     

Performance Analysis of Intelligent Robust Facility Layout Design

Design of a robust production facility layout with minimum handling cost (MHC) presents an appropriate approach to tackle facility layout problems in a dynamic volatile environment, in which product demands randomly change in each planning period. The objective of the design is to find the robust facility layout with minimum total material handling cost over the entire multi-period planning horizon. This paper proposes a new mathematical model for designing robust machine layout in the stochastic dynamic environment of manufacturing systems using quadratic assignment problem (QAP) formulation. In this investigation, product demands are assumed to be normally distributed random variables with known expected value, variance, and covariance that randomly change from period to period. The proposed model was verified and validated using randomly generated numerical data and benchmark examples. The effect of dependent product demands and varying interest rate on the total cost function of the proposed model has also been investigated. Sensitivity analysis on the proposed model has been performed. Dynamic programming and simulated annealing optimization algorithms were used in solving the modeled example problems.     

混联虚拟轴研抛机床的多柔体动力学研究

为了在自由曲面的弹性研抛中 ,获得稳定的动力学特性和加工效果 ,开发了一种由“3轴并联 + 2轴串联”构成的新型 5自由度混联虚拟轴研抛机床。采用柔性多体系统动力学方法 ,建立了基于Lagrange方程的空间刚 柔耦合动力学模型 ;考虑研抛机床整体的刚性运动与各支链弹性变形间的相互作用及耦合 ,将机床的各个支链和平台看作独立子结构 ,建立各自的动力学方程 ,根据子结构之间的约束关系建立了系统约束动力学方程 ;通过动力学仿真分析 ,获得了较稳定的动力学特性     

Cost based scheduling in a job shop environment

Scheduling is one of the most important issues in operations planning of a manufacturing system. In this paper a new scheduling strategy based on machine cost considerations has been proposed. A scheduling factor based on initial cost of a machine and its running cost has been developed. A scanning procedure has been implemented which prioritizes eligible workstations for each setup of a job based on the scheduling factor. Two measures of performance—idleness factor and idleness cost factor—have been developed. Computer simulation has been used to investigate the impact of various decision parameters on operating behavior of the system.     

五轴数控加工仿真研究

针对DMC60TR五轴数控机床,介绍使用Vericut数控仿真软件构建数控仿真平台进行研究的过程,在构建DMC60TR数控机床五轴虚拟加工系统的基础上,通过对加工仿真过程的结果分析及观察动态切削过程,来检查干涉、过切、碰撞和超程等问题,及时发现工艺问题,能进一步提高零件的加工效率和机床的利用率,达到提高产品质量的目的。     

基于可重构的轮辋自动加工机床

针对轮辋产品在材质、规格、编网参数、窝孔尺寸及窝孔组数等方面的系列化,市场对轮辋产品的个性化需求,进行产品族的成组特性分析,提出多级重构、无级重构和有级重构等新概念,综合应用调整、更换、集成及创新等重构策略,按照三级重构机理科学划分模块、创新总体结构,成功研制基于轮辋产品族的可重构自动加工机床.该可重构机床已投放市场并正常生产,其加工产品精度高、质量稳定.实践证明,该可重构机床可适应不同材质、不同规格的轮辋混流加工,重构快捷、成本低,设备和模块得到充分利用,可快速而经济地响应市场需求变化.该机床的成功研制验证可重构策略和可重构方案的可行性,必将有力促进可重构技术的深入研究和应用.     

基于遗传算法的动态连续型设备布局方法

在企业未来产品需求可预测的情况下,对具有多个计划期的车间内动态设备布局问题进行了研究.将动态设备布局中设备重置费用简化为设备移动成本与产能损失成本,结合静态设备布局问题连续模型以及动态设备布局问题离散模型的研究方法,构建了针对不等面积设备的动态多期布局问题的连续模型,并设计了改进型的遗传算法对模型进行了求解.此算法具有新颖的编码策略以及自适应选择交叉算子,具有良好的寻优能力.最后通过对一个3×8动态连续型设备布局问题的实例验证,证明了模型与方法的可行性.     

Estimation and forecasting of machine health condition using ARMA/GARCH model

This paper proposes the hybrid model of autoregressive moving average (ARMA) and generalized autoregressive conditional heteroscedasticity (GARCH) to estimate and forecast the machine state based on vibration signal. The main idea in this study is to employ the linear ARMA model and the nonlinear GARCH model to explain the wear and fault condition of machine, respectively. The successful outcomes of the ARMA/GARCH prediction model can give obvious explanation for future states of machine, which enhance the worth of machine condition monitoring as well as condition-based maintenance in practical applications. The advance of the proposed model is verified in empirical results as applying for a real system of a methane compressor in a petrochemical plant.