Real-time software methodologies: Are they suitable for developing Manufacturing control software?

Computer-Integrated Manufacturing (CIM) systems may be classified as real-time systems. Hence, the applicability of methodologies that are developed for specifying, designing, implementing, testing, and evolving real-time software is investigated in this article.The paper highlights the activities of the software development process. Among these activities, a great emphasis is placed on automating the software requirements specification activity, and a set of formal models and languages for specifying these requirements is presented. Moreover, a synopsis of the real-time software methodologies that have been implemented by the academic and industrial communities is presented together with a critique of the strengths and weaknesses of these methodologies.The possible use of the real-time methodologies in developing the control software of efficient and dependable manufacturing systems is explored. In these systems, efficiency is achieved by increasing the level of concurrency of the operations of a plan, and by scheduling the execution of these operations with the intent of maximizing the utilization of the devices of their systems. On the other hand, dependability requires monitoring the operations of these systems. This monitoring activity facilitates the detection of faults that may occur when executing the scheduled operations of a plan, recovering from these faults, and, whenever feasible, resuming the original schedule of the system.The paper concludes that the set of surveyed methodologies may be used to develop the real-time control software of efficient and dependable manufacturing systems. However, an integrated approach to planning, scheduling, and monitoring the operations of these systems will significantly enhance their utility, and no such approach is supported by any of these methodologies.     

制造软件互操作性模型

为了把握制造软件互操作性的本质,正确理解互操作性与软件集成之间的区别和联系,进而寻求恰当的技术和方法来解决制造软件互操作问题,以语义互操作性的定义为基础,给出了制造软件互操作性的定义,分析了互操作性和系统集成的区别和联系。针对制造软件领域在目前的系统集成中遇到的困难,分析了制造软件互操作性需要解决的问题,建立了制造软件互操作性模型,并对其支撑技术进行了分析。基于该模型采用模型驱动架构的软件开发方法,进行了计算机辅助工艺规划系统和计算机辅助夹具设计系统的互操作性研究,对制造软件互操作性模型进行了初步验证。研究表明,采用层次化的制造软件互操作性模型能够针对产品信息逐步实现不同级别的数据交换和共享,是实现制造软件互操作性的有效途径。     

流程工业生产计划与调度系统的组态平台技术

由于流程工业生产计划与调度软件系统开发过程复杂、可重用性差,提出了一种流程工业生产计划与调度系统开发的组态平台技术方法.该方法以图形化组态的方式对系统进行设计和开发,并可以链接各种定制的算法,达到快速生成系统软件的目的.以此方法为基础,研制出了用于开发流程工业生产计划与调度软件系统的组态平台软件.实际应用结果表明,该组态平台软件使用简单、通用性强,可以有效提高流程工业生产计划与调度系统的开发效率.     

基于PCI-208卡的SCARA机器人控制系统的研究

随着SCARA机器人在工业装配线的应用越来越广泛,工业环境对其控制系统的要求也越来越高,所以开放式机器人控制系统的设计迫在眉睫。本文就是在这种要求的前提下,针对SCARA机器人进行了控制系统的设计与研究。首先是选择开放性的硬件平台,这种平台可以根据需要更换不同的硬件设备。其次是在控制系统的应用软件的开发。这个部分我们对其进行了系统架构与功能模块的开发。该软件体系有相当的柔性,使其可以在不同软硬件平台上移植,而且可以根据需要进行扩展。最后探讨了本控制系统方案的优点以及需要改进的地方。     

工艺设计与车间作业计划优化运行模式的研究

工艺设计与车间作业计划是制造系统中的两个重要环节，实现二者的优化运行具有很大的实际意义。本文详细分析了工艺设计与车间作业计划之间的联系和区别，研究了串行模式下二者之间存在的问题和目前的解决方法，基于分布式工艺设计的任务划分思想，考虑了并行工程的要求和特点，提出一种工艺设计与车间作业计划的优化运行模式。     

An effective multi-objective genetic algorithm based on immune principle and external archive for multi-objective integrated process planning and scheduling

Process planning and scheduling are two major sub-systems in a modern manufacturing system. In traditional manufacturing system, they were regarded as the separate tasks to perform sequentially. However, considering their complementarity, integrating process planning and scheduling can further improve the performance of a manufacturing system. Meanwhile, the multiple objectives are needed to be considered during the realistic decision-making process in a manufacturing system. Based on the above requirements from the real manufacturing system, developing effective methods to deal with the multi-objective integrated process planning and scheduling (MOIPPS) problem becomes more and more important. Therefore, this research proposes a multi-objective genetic algorithm based on immune principle and external archive (MOGA-IE) to solve the MOIPPS problem. In MOGA-IE, the fast non-dominated sorting approach used in NSGA-II is utilized as the fitness assignment scheme and the immune principle is exploited to maintain the diversity of the population and prevent the premature condition. Moreover, the external archive is employed to store and maintain the Pareto solutions during the evolutionary process. Effective genetic operators are also designed for MOIPPS. To test the performance of the proposed algorithm, three different scale instances have been employed. And the proposed method is also compared with other previous algorithms in literature. The results show that the proposed algorithm has achieved good improvement and outperforms the other algorithms.     

Production engineering-oriented virtual factory: a planning cell-based approach to manufacturing systems design

In the traditional process of designing a manufacturing system, a sequential approach treats each of the design steps individually, without considering the requirements of concurrent design activities. The lack of systematic and concurrent consideration of the interactive impact of design decisions leads to repeated and excessive changes in the design and process. To resolve this problem, this research develops a production engineering-oriented virtual factory – a planning cell-based manufacturing systems design approach. The manufacturing systems design process based on a planning cell is reengineered according to the concept of concurrent engineering. The process modeling of a production engineering-oriented virtual factory is proposed at generic and particular levels. An illustrative example of an engine assembly plant demonstrates the effectiveness of the new approach.     

Agent technology for collaborative process planning: a review

Agent technology has been considered as a promising approach for developing process planning systems and optimizing process plans in a distributed environment. A number of researchers have attempted to use agent technology in process planning for the purpose of integrating systems, tools and algorithms which are geographically distributed. In this paper, the historical background of agent technology is systematically reviewed. A comprehensive review of agent technology and its applications in manufacturing is presented including the applications of agent in scheduling, control, and enterprise integration and supply chain management. The focus of the paper is on how agent technology can be further developed in the support of collaborative process planning as well as its future research issues and directions in process planning. The current research directions in computer aided process planning (CAPP) and issues in traditional CAPP approaches are also discussed. Three agent-based approaches for process planning are presented. Finally, the key issues in developing agent-based collaborative process planning systems are summarized.     

Production engineering-oriented virtual factory: a planning cell-based approach to manufacturing systems design

In the traditional process of designing a manufacturing system, a sequential approach treats each of the design steps individually, without considering the requirements of concurrent design activities. The lack of systematic and concurrent consideration of the interactive impact of design decisions leads to repeated and excessive changes in the design and process. To resolve this problem, this research develops a production engineering-oriented virtual factory — a planning cell-based manufacturing systems design approach. The manufacturing systems design process based on a planning cell is reengineered according to the concept of concurrent engineering. The process modeling of a production engineering-oriented virtual factory is proposed at generic and particular levels. An illustrative example of an engine assembly plant demonstrates the effectiveness of the new approach.     

A pattern-directed approach to flexible manufacturing: A framework for intelligent scheduling, learning, and control

The planning, scheduling, and control of manufacturing systems can all be viewed as problem-solving activities. In flexible manufacturing systems (FMSs), the computer program carrying out these problem-solving activities must additionally be able to handle the shorter lead time, the flexibility of job routing, the multiprocessing environment, the dynamic changing states, and the versatility of machines. This article presents an artificial intelligence (AI) method to perform manufacturing problem solving. Since the method is driven by manufacturing scenarios represented by symbolic patterns, it is referred to as pattern-directed. The method is based on three AI techniques. The first is the pattern-directed inference technique to capture the dynamic nature of FMSs. The second is the nonlinear planning technique to construct schedules and assign resources. The third is the inductive learning method to generate the pattern-directed heuristics. This article focuses on solving the FMS scheduling problem.In addition, this article reports the computation results to evaluate the utility of various heuristic functions, to identify important design parameters, and to analyze the resulting computational performance in using the pattern-directed approach for manufacturing problem-solving tasks such as scheduling.     

Declarative approach to cyclic steady state space refinement: periodic process scheduling

Problems of cyclic scheduling are usually observed in flexible manufacturing systems which produce multitype parts where the automated guided vehicle system plays the role of a material handling system, as well as in various other multimodal transportation systems where goods and/or passenger itinerary planning plays a pivotal role. The schedulability analysis of the processes executed in the so-called systems of concurrent cyclic processes (SCCPs) can be executed within a declarative modeling framework. Consequently, the considered SCCP scheduling problem can be seen as a constraint satisfaction problem. Such a representation provides a unified way for evaluating the performance of local cyclic processes as well as of multimodal processes supported by them. Here, the crucial issue is that of a control procedure (e.g., a set of dispatching rules), which would guarantee the cyclic behavior of the SCCP. In this context, we discuss the sufficient conditions guaranteeing the schedulability of both local and multimodal cyclic processes, and we propose a recursive approach in designing them.     

Discrete lot sizing and scheduling problem under batch processing constraints in the semiconductor manufacturing

Highly advanced technology products are manufactured on the series of equipment having various characteristics and requirements. The deposition process of organic light emitting diode, for example, is performed in chambers for a long manufacturing time, while various product devices belonging to the same family can be processed in sequence before the preventive maintenance schedule or the refill of chemical gas required. The deposition process plays as a bottleneck, and its productivity of the schedule is critical to the upstream low-temperature poly silicon process and the downstream encapsulation and module processes as well. The batch family scheduling problem is formulated using the mixed-integer programming (MIP) in consideration of the family setups, lot sizing, supplementary mask tools requirements, and material exhaustion requirements. It is shown that the planning and scheduling decisions can be made simultaneously in an integrated model, and that it can be implemented in the actual manufacturing line. Through the optimized model analysis, the capacity can be enhanced by 20～30 % without losing the throughput and demand satisfaction as well.     

Production activity control: A practical approach to scheduling

There is a widely perceived gap within the domain of scheduling for manufacturing systems, namely, many of the methods employed by production supervisors are quite different from those developed by researchers. In a sense, this inconsistency highlights the important fact that much scheduling research has failed to win approval where it matters most, namely, within the manufacturing system.In this article, we argue for a practical approach to scheduling for manufacturing systems, one that we believe can narrow, and possibly bridge, the gap between theory and practice. This approach is based upon a well-defined and modular architecture for scheduling, termedproduction activity control. This architecture is the foundation of our proposed solution to scheduling, since it provides a coherent blueprint for the synthesis of information technology and scheduling strategies. The result of this synthesis is a design tool for production activity control, which allows for detailed and disciplined experimentation with a range of scheduling strategies in a controlled and simulated environment. Due to the unique modular property of the design tool, these strategies may then be implemented live in a flexible manufacturing facility, hence narrowing the gap between scheduling theory and manufacturing practice. Our overall approach is tested through an appropriate implementation in a modern electronics assembly plant.     

Integrated model for production planning and scheduling in a supply chain using benchmarked genetic algorithm

Production planning and scheduling is one of the core functions in manufacturing systems. Furthermore, this task is drawing even more attention in supply chain environments as problems become harder and more complicated. Most of the traditional approaches to production planning and scheduling have adopted a multi-phased, hierarchical and decompositional approach. This traditional approach does not guarantee a feasible production schedule. And even when capacity constraints are satisfied, it may generate an expensive schedule. In order to overcome the limitations of the traditional approach, several previous studies tried to integrate the production planning and scheduling problems. However, these studies also have some limitations, due to their intrinsic characteristics and the method for incorporating the hierarchical product structure into the scheduling model. In this paper we present a new integrated model for production planning and scheduling for multi-item and multi-level production. Unlike previous lot sizing approaches, detailed scheduling constraints and practical planning criteria are incorporated into our model. We present a mathematical formulation, propose a heuristic solution procedure, and demonstrate the performance of our model by comparing the experimental results with those of a traditional approach and optimal solution.     

An integrated planning approach for a nanodeposition manufacturing process

This paper deals with the planning problem in a nanodeposition manufacturing process, in which a toolbit that consists of a multilayer grid of micro/nanofluidic channels is used to deposit nanoscale liquid materials to desired positions on workparts to form solid patterns. The objective is to obtain a planning procedure that achieves efficient throughput for the studied nanodeposition manufacturing systems. We break down the studied problem into several sub-problems as design pattern decomposition, nanopore assignment, liquid material routing in the multilayer grid fluidic network, and toolbit path planning. Efficient algorithms are proposed to solve these sub-problems individually, and then finally integrated into a framework that systematically plans the nanodeposition manufacturing process. A software tool that plans, simulates, and controls the nanodeposition manufacturing process by implementing the proposed algorithms is reported in this paper.     

Daily planning and scheduling system for the EDS process in a semiconductor manufacturing facility

Operations management in a complex manufacturing environment is practiced hierarchically: production planning and scheduling in sequence since the integrated approach is not efficient and practical. Production targets and allocation to the equipment are determined in the planning procedure by considering the only the critical factors, and the detailed scheduling is determined with more information needed to accomplish the production targets provided in the planning step. There is always, therefore, a gap between the planning and scheduling procedure, and some control parameters or factors are used to control those gaps. In this paper an approach connecting two procedures is suggested, which can be applied in the EDS (electrical die sorting) or the probe process in the semiconductor manufacturing. The EDS process requires very flexible operation management since the manufacturing processing time is relatively short and the supply of upstream fabrication and the demand of downstream assembly have to be met simultaneously. Daily planning and scheduling procedure are modeled to minimize the tester change-over within the daily target. Because of the relatively long setup change-over time, daily planning and scheduling have to be performed so that the time needed for the device and probe card change is minimized as possible. Mathematical programming is suggested for the problem, and the modified model is developed which can be solved in a practical computational time on a daily base. The scheduling heuristic with the planning data obtained from the suggested model, is designed, and their performance is evaluated through the computational experiment.     

Dynamic production planning model: a dynamic programming approach

Production planning is one of the most important issues in manufacturing. The nature of this problem is complex and therefore researchers have studied it under several and different assumptions. In this paper, applied production planning problem is studied in a general manner and it is assumed that there exists an optimal control problem that its production planning strategy is a digital controller and must be optimized. Since this is a random problem because of stochastic values of sales in future, it is modeled as a stochastic dynamic programming and then it is transformed to a linear programming model using successive approximations. Then, it is proved that these two models are equivalent. The main objective of the proposed model is achieving optimal decisions using forecasting sales which can be applied in master production schedule, manufacturing resource planning, capacity requirements planning, and job shop/shop floor scheduling.     

区域性制造业信息化工程方案设计方法研究

分析了区域性制造业信息化的资源系统构成及其市场要素需求，从资源优化配置角度，以支持区域制造业与信息化技术服务产业的整体发展为目的，构建了区域性整体制造业信息化工程的设计实施体系框架，并研究了其中的关键环节，提出了企业信息化的梯度扩展理论．在需求分析的基础上阐述了典型区域制造业信息化工程规划方案。     

一种新型家庭监控报警系统的设计

提出了一种新型家庭监控报警系统的设计,并对系统所用到的ROK101 008蓝牙模块和S3C2410X微处理器做了简要描述,详细论述了系统的硬件及软件设计并给出了程序流程图.该系统能够实时监控终端探测设备的信息,并同监控中心交换数据,当有突发事件时能够及时发出报警.实践证明,该系统运行可靠,具有简单、经济、易于实现的特点,也能很好地应用于其他功能的监控报警系统.     

The Application and Evaluation of Banker''s Algorithm for Deadlock-Free Buffer Space Allocation in Flexible Manufacturing Systems

Deadlock-free operation is essential for operating highly automated manufacturing systems. The seminal deadlock avoidance procedure, Banker's algorithm, was developed for computer operating systems, an environment where very little information regarding the future resource requirements of executing processes is known. Manufacturing researchers have tended to dismiss Banker's algorithm as too conservative in the manufacturing environment where future resource requirements are well defined by part routes. In this work, we investigate this issue by developing variants of Banker's algorithm applicable to buffer space allocation in flexible manufacturing. We show that these algorithms are not overly conservative and that, indeed, Banker's approach can provide very good operational flexibility when properly applied to the manufacturing environment.