A review of function blocks for process planning and control of manufacturing equipment

Manufacturing in a job-shop environment is often characterized by a large variety of products in small batch sizes, requiring real-time monitoring for dynamic distributed decision making, and adaptive control capabilities that are able to handle, in a responsive way, different kinds of uncertainty, such as changes in demand and variations in production capability and functionality. In many manufacturing systems, traditional methods, based on offline processing performed in advance, are used. These methods are not up to the standard of handling uncertainty, in the dynamically changing environment of these manufacturing systems. Using real-time manufacturing intelligence and information to perform at a maximum level, with a minimum of unscheduled downtime, would be a more effective approach to handling the negative performance impacts of uncertainty. The objective of our research is to develop methodologies for distributed, adaptive and dynamic process planning as well as machine monitoring and control for machining and assembly operations, using event-driven function blocks. The implementation of this technology is expected to increase productivity, as well as flexibility and responsiveness in a job-shop environment. This paper, in particular, presents the current status in this field and a comprehensive overview of our research work on function block-enabled process planning and execution control of manufacturing equipment.     

A hybrid approach for dynamic routing planning in an automated assembly shop

Highly turbulent environment of dynamic job-shop operations affects shop floor layout as well as manufacturing operations. Due to the dynamic nature of layout changes, essential requirements such as adaptability and responsiveness to the changes need to be considered in addition to the cost issues of material handling and machine relocation when reconfiguring a shop floor’s layout. Here, based on the source of uncertainty, the shop floor layout problem is split into two sub-problems and dealt with by two modules: re-layout and find-route. GA is used where changes cause the entire shop re-layout, while function blocks are utilised to find the best sequence of robots for the new conditions within the existing layout. This paper reports the latest development to the authors’ previous work.     

Designing function blocks for distributed process planning and adaptive control

The objective of this research is to develop methodologies and a framework for distributed process planning and adaptive control using function blocks. Facilitated by a real-time monitoring system, the proposed methodologies can be applied to integrate with functions of dynamic scheduling in a distributed environment. A function block-enabled process planning approach is proposed to handle dynamic changes during process plan generation and execution. This paper focuses mainly on distributed process planning, particularly on the development of a function block designer that can encapsulate generic process plans into function blocks for runtime execution. As function blocks can sense environmental changes on a shop floor, it is expected that a so-generated process plan can adapt itself to the shop floor environment with dynamically optimized solutions for plan execution and process monitoring.     

Capacity planning in job-shop environment

Presented here is a computerized capacity planning system for the IBM Microcomputer family. The system maintains the profile of the job shop in a data base along with data pertinent to various products that can be manufactured in the shop. Projected orders for the planning period are input to the system with their associated quantities and delivery dates. The system uses the forward and backward loading rules in generating capacity loading scenarios. User selects the best course of action which may satisfy delivery dates subject to the limitations of the work centers. Efficiency figures are provided to aid the user in his/her decision.     

Machining process sequencing with fuzzy expert system and genetic algorithms

Traditional process planning systems are usually established in a deterministic framework that can only deal with precise information. However, in a practical manufacturing environment, decision making frequently involves uncertain and imprecise information. This paper describes a fuzzy approach for solving the process selection and sequencing problem under uncertainty. The proposed approach comprises a two-stage process for machining process selection and sequencing. The two stages are called intra-feature planning and inter-feature planning, respectively. According to the feature precedence relationship of a machined part, the intra-feature planning module generates a local optimal operation sequence for each feature element. This is based on a fuzzy expert system incorporated with genetic algorithms for machining cost optimization according to the cost-tolerance relationship. Manufacturing resources such as machines, tools, and fixtures are allocated to each selected operation to form an Operation-Machine-Tool (OMT) unit in the manufacturing resources allocation module. Finally, inter-feature planning generates a global OMT sequence. A genetic algorithm with fuzzy numbers and fuzzy arithmetic is developed to solve this global sequencing problem.     

A novel energy demand modelling approach for CNC machining based on function blocks

Energy efficiency remains one of the major issues in the machining domain. Today's machining systems are confronted with a number of new challenges, such as turbulent product demand and variations in production resources. Rapid and flexible energy modelling in a distributed and collaborative machining environment emerges as a new research area. Energy demand models in such an environment need to be practical, accurate, effective, scalable and reusable. Energy analysis and optimisation cannot be carried out once for all at the beginning. Instead, it is an on-going process. In this paper, the function block technique, i.e. IEC 61499, is used for the development of energy demand models as it brings advantages such as modularity, encapsulation, extensibility and reusability. A brief review on energy modelling and research on function blocks are given in the first part. A novel energy demand modelling approach based on function blocks is then proposed and elaborated. Three types of function blocks have been developed, i.e. machine tool dependent function blocks, state transition function blocks, and service interface function blocks. The first type, as the fundamental building blocks, is divided into two sub-types, machine component function block and machining state function block. Two case studies, based on a small 3-axis milling machine and an industrial production line respectively, are presented to demonstrate the possible applications using the function block-based model. Comprehensive discussions are given thereafter, including a pilot application of a distributed process planning system and a unique energy evaluation scheme. A confidence level associated energy rating system is proposed as the first step to turn energy consumption figures into useful indicators. The energy demand model based on function blocks developed here enhances the energy modelling and their practical implementations.     

基于效率函数求解单件车间调度问题算法的完善

单件小批量生产形式下的单件车间（Job-shop)调度是生产计划中的一个重要问题，本文在文献[1]提出的求解Job-shop调度问题的动排算法及调解算法的基础上，做出了进一步的修改和完善，在调解算法中引入了交换与移动相结合的机制以提高调解效率，并在VBA For Projcet2000中实现了该算法，经分析及实验验证，利用这种算法求解Job-shop调度问题，可得到十分满意的结果。     

一种新颖的适应性工作流系统原型

纵观当前的工作流管理技术和产品，普遍存在着系统适应能力差的问题。为了解决上述问题，提出了一种动态定义过程的适应性工作流系统原型，并在实际的生产流程中验证了此原型的适应性。     

面向对象过程仿真技术中的资源规划

过程仿真是企业过程模型进行分析、验证、改进、优化和评价的实用方法。尤其在过程模型难以定量优化的情况下,过程仿真就显得更为重要。侧重于过程仿真中的资源规划问题。对过程仿真中的资源类进行定义,并描述了资源与组织、资源与功能之间的关系;在此基础上对过程仿真中的资源规划进行研究。     

一类Job- shop 车间生产计划和调度的集成优化

讨论一类Job—shop车间的生产计划和调度的集成优化问题,给出了该问题的非线性混合整数规划模型,并采用混合遗传算法进行求解。该模型利用调度约束来细化生产计划,以保证得到可行的调度解。在混合算法中,利用启发式规则来改善初始解集,并采用分段编码策略将计划和调度解映射为染色体。算例研究表明,该算法对求解该类问题具有很好的效果。     

PACS系统在医院的应用

PACS已成为医院信息系统中的一个重要组成部分。本文从医院实际情况出发,分析了PACS系统的工作流程及各模块的功能,以及实施后的带来的好处。     

作战计划生成方法研究现状与展望

作战计划质量的高低事关战争的成败,而作战行动序列生成是计划制定的关键。目前作战计划生成面临着行动状态搜索空间大,无法有效处理战场不确定因素对计划执行效果的影响,不能满足现代战争非线性、不确定性需求等问题。为此,分别从经典计划生成和作战计划生成中的理论与应用两个方面分析了国内外的研究现状,特别是针对作战计划生成问题中传统的、基于效果作战的以及不确定性的作战行动序列生成方法进行了系统及深入的阐述,进而指出当前该领域的主要研究方向,这对于现代战争中作战计划的生成具有重要指导意义。     

基于效率函数求解单件车间调度问题算法的软件实现和实例分析

单件小批量生产形式下的单件车间（Job-shop）调度是生产计划中的一个重要问题。西方在文献[1]提出的求解Job-shop调度问题的初排算法及调解算法的基础上，做出了进一步的修改和完善，在调解算法中引入了交换与移动相结合的机制以提高调解效率；在软件实现中引入了“虚工序”的概念，并在“VBA ForProject2000中实现了该算法。经分析及实验验证，利用这种算法求解Job-shop调度问题可得到十分满意的结果。     

机械制造工艺数字化建模与网络化设计工具系统的研究

结合某大型汽轮机厂网络化工艺设计与过程管理集成系统的研制,针对面向产品工艺设计、过程管理与信息资源一体化的制造业信息化集成的需要,提出了面向产品与过程管理的制造工艺集成系统的集成模型,根据用户权限的不同,在工艺设计部门,采用C/S模式,集工艺设计、资源管理、文档管理与工艺管理为一体,实现工艺设计和管理的计算机化和信息化,在工艺设计部门以外与工艺工作有关的所有部门,采用B／S模式,实现工艺信息的共享与协同处理,解决了制造业信息化工程建设中制造工艺信息平台系统构建的关键技术问题。     

现场总线与智能现场仪表设计技术

现场总线作为用于工业现场的局域网,其运行基础是智能现场总线仪表。本文根据基金会现场总线的基本,探讨了智能现场总线仪表的设计方法。     

静态容积法流量标准装置的架构

分析了静态容积法流量检定装置设计方法,重点研究了装置的压力稳定性、换向器的选择、工作量器的设计等关键技术,并对装置的相关参数进行详细的分析,提出了装置架构方案,并用大量试验数据证实了装置的可靠性,对建立一个高精度的流量标准装置具有重要意义。     

Adaptive fuzzy neuro-observer applied to low cost INS/GPS

A combined MEMS Inertial Navigation System (INS) with GPS is used to provide position and velocity data of land vehicles. Data fusion of INS and GPS measurements are commonly achieved through a conventional Extended Kalman filter (EKF). Considering the required accurate model of system together with perfect knowledge of predefined error models, the performance of the EKF is decreased due to unmodeled nonlinearities and unknown bias uncertainties of MEMS inertial sensors. Universal knowledge based approximators comprising of neural networks and fuzzy logic methods are capable of approximating the nonlinearities and the uncertainties of practical systems. First, in this paper, a new fuzzy neural network (FNN) function approximator is used to model unknown nonlinear systems. Second, the process of design and real-time implementation of an adaptive fuzzy neuro-observer (AFNO) in integrated low-cost INS/GPS positioning systems is proposed. To assess the long time performance of the proposed AFNO method, wide range tests of a real INS/GPS with a car vehicle have been performed. The unbiased estimation results of the AFNO show the superiority of the proposed method compared with the classic EKF and the adaptive neuro-observer (ANO) including a pure artificial neural network (ANN) function approximator.     

自适应搜索优化算法

自由搜索算法是一种新的群集智能优化算法,已经成功地应用于函数优化问题.针对该算法所存在的对参数敏感等问题,提出自适应搜索算法.通过自适应实时调整搜索半径、搜索步、灵敏度等参数,提高算法对环境的适应性、鲁棒性和在\"探索\"和\"开发\"之间的平衡能力.对典型函数的试验结果证明,新算法不仅降低了对参数的依赖性,而且成功率高、收敛速度快,能有效避免陷入局部次优.     

基于资源约束的CAPP系统

在分析目前的专用型 ＣＡＰＰ和通用型 ＣＡＰＰ的优缺点的基础上,建立了基于资源约束的 ＣＡＰＰ模型,该模型可在用户所建的资源子系统约束下,进行工艺评价,同时在车间环境下动态生成工艺规划和加工参数,能适应目前制造业的柔性化趋势。