Hierarchical production control for a flow shop with dynamic setup changes and random machine breakdowns

In this paper, we study a manufacturing system consisting of two machines separated by two intermediate buffers, and capable of producing two different products. Each product requires a constant processing time on each of the machines. Each machine requires a constant non-negligible setup change time from one product to the other. The demand rate for each product is considered to be piecewise constant. Each machine undergoes failure and repair. The time-to-failure and time-to-repair are exponentially distributed random variables. The setup change and processing operations are resumable. We model our system as a continuous time, continuous flow process. An optimal control problem is formulated for the system to minimize the total expected discounted cost over an infinite horizon. To determine the optimal control policy structure, a discrete version of the problem is solved numerically using a dynamic programming formulation with a piecewise linear penalty function. A real-time control algorithm is then developed with the objective of maintaining low work-in-process inventory and keeping the production close to the demand. The algorithm uses a hierarchical control structure to generate the loading times for each product on each machine in real time and to respond to random disruptions in the system. The system is simulated using this algorithm to study its performance. The performance of the algorithm is also compared to alternative policies.     

An integrated intelligent machining system for axisymmetric parts using PC-based CAD and CAM software packages

Machining process planning involves the formation of a set of directions describing the machining operations required to transform raw stock into a finished part. Conventional process planning, performed manually, relies on the knowledge and competence of an experienced process planner and tends to be time consuming and error prone. In the past two decades, much effort has been spent on improving process planning by utilizing the power of a computer to emulate the capabilities of an experienced planner. During the same period, computer-aided design (CAD) and computer-aided manufacturing (CAM) software has been developed to enhance design productivity and to assist the NC code generation facets of the machining process. The entire planning process may be automated be integrating CAD and CAM using computer-aided process planing (CAPP). The research described in this paper outlines the design and development of an intelligent CAPP system integrating two commercial CAD and CAM software packages, Autocad and Mastercam.     

Hierarchical intelligent control with flexible AC transmission systems application

A novel hierarchical intelligent controller configuration is proposed using an artificial neural network as a control-mode classifier in the supervisory level and a set of pre-designed controllers in the lower level. Controller outputs are modified nonlinearly by the classifying signals in a structure resembling one artificial neuron with adaptively changed weights. The lower-level local controllers are implemented using neural networks. An illustrative example of this approach is based on the transient stabilization of a single-machine infinite-bus system studied in Flexible AC Transmission Systems (FACTS) research.     

柔性制造系统生产中的零件分批算法

根据ＦＭＳ资源、加工任务、零件工艺提出了零件分批算法，该算法在零件交货期的束下，以机床负荷平衡为目标，搜索零件集合，找出最合适的零件组合形成零件加工批。此算法为简化ＦＭＳ的动态调度和提高系统生产率创造了条件。仿真结果表明分批算法是行之有效的。     

ZXJ10机IN业务功能扩展及实现

本文从智能网的基本概念入手,论述了利用 ZXJ10程控交换系统为发展智能网业务提供支持功能的技术策略以及分阶段实现的过程,并对各个阶段能够实现的业务作了简要介绍。     

Multi-plant production scheduling in SMEs

Traditionally, companies used to view themselves as separate entities and did not devote efforts to collaborate with other echelons of the extended enterprise. This even happened at multi-site companies owning different plants that belonged to the same supply chain. However, manufacturing facilities of the same supply chain should intensively share information and coordinate planning and scheduling tasks in order to get a globally optimized solution. This paper discusses some specific characteristics of the planning and scheduling problem in the extended enterprise including an analysis of a case study, and reviews the available state-of-the-art research studies in this field. Most studies suggest that integrated approaches can have a significant impact on the system performance, in terms of lower production costs, and less inventory levels. The paper provides some conclusions and suggestions of future works.     

A multi-objective programming model for scheduling emergency medicine residents

Scheduling emergency medicine residents (EMRs) is a complex task, which considers a large number of rules (often conflicting) related to various aspects such as limits on the number of consecutive work hours, number of day and night shifts that should be worked by each resident, resident staffing requirements according to seniority levels for the day and night shifts, restrictions on the number of consecutive day and night shifts assigned, vacation periods, weekend off requests, and fair distribution of responsibilities among the residents. Emergency rooms (ERs) are stressful workplaces, and in addition shift work is well-known to be more demanding than regular daytime work. For this reason, preparing schedules that suit the working rules for EMRs is especially important for reducing the negative impact on shift workers physiologically, psychologically, and socially. In this paper, we present a goal programming (GP) model that accommodates both hard and soft constraints for a monthly planning horizon. The hard constraints should be adhered to strictly, whereas the soft constraints can be violated when necessary. The relative importance values of the soft constraints have been computed by the analytical hierarchy process (AHP), which are used as coefficients of the deviations from the soft constraints in the objective function. The model has been tested in the ER of a major local university hospital. The main conclusions of the study are that problems of realistic size can be solved quickly and the generated schedules have very high qualities compared to the manually prepared schedules, which require a lot of effort and time from the chief resident who is responsible for this duty.     

基于ARX模型的压电智能结构振动预测控制

采用预测控制法对压电智能结构的振动主动控制进行了实验研究，通过实验方法建立了系统的ARX模型，并在此基础上设计了预测控制器对结构进行振动主动控制。实验结果验证了该方法在压电智能结构振动主动控制中的可行性和有效性。     

基于软件总线的星载系统软件结构的研究与设计

针对目前国内外星载系统软件可重构性较差的问题，提出了一种基于软件总线的星载系统软件结构。首先，介绍了软件总线和软构件的结构。其次，阐述了星载实时多任务操作系统中混合任务调度算法的设计。最后，对这个混合任务调度算法的正确性给出了证明。     

轴快流CO2激光器气体压力控制

激光切割对激光功率模式、功率密度和功率稳定性要求很高,采用轴快流CO2激光器时,控制工作气体压力工作在最佳状态并保持其恒定是激光器输出连续、稳定功率的必要条件和关键技术之一。在深入研究激光器工作原理和影响激光输出功率因素的基础上,采用带积分分离的智能PID控制算法对工作气体压力进行调节。该过程控制算法简单实用,可以有效地提高气体压力控制精度,改善功率控制精度和稳定性,并用实验加以验证。