实物期权法在分阶段投资项目中的应用

分阶段投资项目具有较高的不确定性，运用传统净现值法不能充分发掘项目的不确定性所包含的潜在价值。引入Black．Scholes期权定价模型和风险中性原理，并通过传统净现值法和实物期权法在实例中的对照比较，说明了在不确定性较高的环境下，运用实物期权法对分阶段投资项目进行决策的优越性。     

国外柔性制造系统(FMS)在齿轮加工中的应用

为了发展多品种生产,提高劳动生产率,降低生产成本,缩短生产周期,增强市场竟争能力,目前,世界各国都正在大力发展柔性制造系统(简称FMS)。柔性制造系统已成为机械制造业今后的重要发展形式和方向。柔性制造系统在国外发展得很快。据粗略统计,到1985年,全世界的柔性制造系统已达300多条,广泛应用于汽车、拖拉机、飞机、机床等的多品种生产。其中约有十多条柔性制造系统,用于齿轮的柔性生产。即齿轮柔性制造系统。下面简要介绍主要几条齿轮柔性制造系统。     

实物期权在多阶段投资中的应用研究

运用实物期权理论的相关知识，研究了多阶段实物期权模型拓展和相互影响关系，以及用蒙特卡罗模拟计算期权价值的问题。Geske模型是分析多阶段实物期权的基础，首先在此基础上进行了拓展分析，描述了多阶段投资过程中应用复合期权的整体思路，然后对多阶段实物期权的相互作用进了分析，阐述了不同类型的实物期权具有不同的相互影响，最后应用蒙特卡罗模拟对此类问题进行了数值分析，使输入变量更加符合实际，计算结果更加容易被理解和认可。     

各国柔性制造系统应用概况及204例(一)

为了适应多品种生产的发展,提高劳动生产率,降低成本,缩短生产周期,增强市场竞争能力,近年来,世界各国都在大力发展柔性制造系统(英文缩写为FMS)。 进入80年代,柔性制造系统发展到应用阶段。据粗略统计,目前全世界已有柔性制造系统300多条,应用于汽车、拖拉机、飞机、机床、内燃机等行业的多品种中小批量生产,其中一些也应用于少品种大批量生产。目前开发的柔性制造系统,大多数用于切削加工,也有用于装配、焊接等作业。在柔性制造系统上加工的零件类型,箱体类占80%左右,回转体类占20%左右。另外,从加工零件的品种数目看,约有35%的FMS用于…     

实物期权在多阶段投资中的应用研究

运用实物期权理论的相关知识,研究了多阶段实物期权模型拓展和相互影响关系,以及用蒙特卡罗模拟计算期权价值的问题。Geske模型是分析多阶段实物期权的基础,首先在此基础上进行了拓展分析,描述了多阶段投资过程中应用复合期权的整体思路,然后对多阶段实物期权的相互作用进了分析,阐述了不同类型的实物期权具有不同的相互影响,最后应用蒙特卡罗模拟对此类问题进行了数值分析,使输入变量更加符合实际,计算结果更加容易被理解和认可。     

柔性制造系统的发展现状和前景展望

随着科学技术的发展．日益加剧的市场竞争和客户的个性化需求使得现代制造业中多品种．中、小批量生产所占的比重越来越大。柔性制造系统正是为了适应这种新的市场环境而发展起来的。但进入20世纪90年代后．柔性制造系统的发展遇到了一定困难．本文分析了柔性制造系统在实施过程中存在的一些问题．并尝试找出相应的对策，以便使柔性制造系统焕发新的生机。     

柔性制造系统

随着新技术革命的兴起,在生产领域中,除了电子计算机,还有两个新的主角登台了。这就是工业机器人和柔性制造系统。本文仅对柔性制造系统作一简单介绍。一、什么是柔性制造系统作为冷加工工人,对传统的车、铣、刨、磨、钻等机床是十分熟悉的。对数控机床和组合机床及其自动线也不陌生。它们分别被人们统称为通用机床、数控机床和专用机床。前者适用于单件生产,后者则主要是为大批大量生产同一种零件设计的。目前,社会对产品提出了多样化的要求,而且品种花样变化很快,致使产品的每一种品种产量减少,因而迎来了多品种中小批量生产的时代。然而,对多品种中小批量生产却长期以来未找到经济合理的     

柔性制造系统实施过程中应注意的问题

针对市场对于小批量、多品种产品目益递增的需要，文中介绍了柔性制造系统的组成，提出在我国实现柔性制造系统过程中所应注意的问题，并着重探了人员因素对柔性制造系统实施过程的影响。     

FMS的应用前景探讨

市场竞争和客户的个性化需求使现代的制造业中多品种,中、小批量生产所占的比重越来越大.柔性制造系统正是为适应这种新的市场环境而发展起来的.但进入20世纪90年代后,柔性制造系统的发展遇到一定困难,分析柔性制造系统在实施过程中存在的一些问题,并尝试找出相应的对策,以便使柔性制造系统焕发新的生机.     

柔性自动化车间的最优随机生产计划

研究了由多个柔性制造系统组成的柔性自动化车间的最优随机生产计划问题,首先根据实际需要建立车间生产计划的随机非线性规划模型,为求解方便,将其近似转化成确定非线性规划模型,并通过引进约束进一步转化成线性规划模型。由于这种模型规模较大,很难在微机上用单纯形法在可接受的时间内获得其最优解。为此,分别用卡马卡算法和基于卡马卡算法的关联预测法,求解柔性自动化车间最优生产计划问题,并编制了相应软件。最后通过算例研究,比较了卡马卡算法、基于卡马卡算法的关联预测法和Matlab中的线性规划法,结果表明,所提方法非常适合将不确定性环境中的随机产品需求计划,最优分解成由柔性自动化车间中各柔性制造系统执行的短期随机计划。     

Development and evaluation of feature-focused dynamic routing policy

This paper reports on a development of feature-focused dynamic routing policy and its evaluation in a flexible manufacturing systems (FMS) simulation framework. The dynamic policy is based on an integrative methodology in which process planning system IMPlanner is integrated with FMS simulation module. IMPlanner’s rule-based system process selection system performs knowledge-intensive task of generating alternative processing options for each feature for parts in production plan. Generated alternative routings (process plan network) for each part are utilized in the FMS simulation module such that routing decision in FMS are made on periodic intervals by considering alternative processes for each feature and making decision based on the current system status and performance. The proposed framework has been evaluated in an experimental FMS simulation module, implemented in Arena, in which two performance criteria, machine utilization and WIP, were used to make routing decisions. The feature-focused approach is compared with traditional static decision-making, and its improved performance is demonstrated.     

Integrated definition modeling and Taguchi analysis of flexible manufacturing systems: aircraft industry application

In this paper, flexible manufacturing systems (FMS) are studied. Firstly, an FMS design approach is proposed using integrated definition for function methodology. A systematic layout design and performance evaluation scheme is presented and detailed using this modeling framework. Then, the proposed approach is carried out with a case study from an aircraft industry to convert an existing traditional production system to FMS. To improve the system performance, a simulation-based method with Taguchi approach consisting of multiproducts is utilized. The objective is to find the machine and the product mix that achieves the maximum utilization while minimizing the cycle time. FMS system performance has been greatly improved by determining the most advantageous level of system components. It has also shown that FMS is a practicable production system in aircraft industry.     

Designing a control mechanism using earned value analysis: an application to production environment

Earned value analysis is a project performance method which simultaneously presents both cost and schedule performances. The purpose of this paper is to model the uncertainty associated with activity duration in earned value analysis. The approach incorporates to design a control mechanism, which would be applicable through production control as well as project management problems. The job processing times have been considered as triangular fuzzy number. Costs are assumed to be directly related to fuzzy activity time, which are estimated through a bottom up hierarchy process. Consequently, different earned value metrics have been achieved. Research findings provide an efficient control mechanism in earned value analysis, which would be highly applicable in production control area. This research also yields a novel approach for representing a production performance index during implementation of production processes. In addition to the above mentioned issues, forecasting features can be further performed for predicting completion time of products for delivery to the customer. The approach presented in this paper has been successfully implemented through a multi-period–multi-product production planning problems, which efficiently demonstrates the applicability of the proposed control mechanism.     

Optimal production-inventory policy for make-to-order versus make-to-stock based on the M/Er/1 queuing model

This paper analyzes a multi-product production / inventory system where demands for each item arrive according to a Poisson process and the production time for each product has an Erlang distribution. The paper proposes an optimality condition that specifies whether each product should be produced make-to-stock or make-to-order. In the event a product should be produced make-to-stock, an approach for computing the optimal base-stock level is proposed. Numerical examples are given for illustrative purpose.     

混合型装配线平衡问题的不确定性仿真研究

针对实际生产系统存在的不确定性因素,采用仿真实验方法研究混合型装配线平衡问题.对混合型装配线平衡问题进行数学建模,并对存在的不确定性因素进行分析;用eM-Plant仿真软件对混合型装配线进行仿真建模,通过仿真实验,研究不确定性因素对混合型装配线平衡问题的影响;通过仿真研究举例说明研究方法的有效性.     

A heuristic algorithm to batching and loading problems in a flexible manufacturing system

Part type selection and machine loading are two major problems in the production planning of flexible manufacturing systems (FMS). The two problems are viewed as selecting subsets from the jobs of part types in a planning horizon and allocating jobs of the subsets among machines. In this paper, in order to develop a practical and efficient approach to solving FMS production planning problems, a heuristic algorithm is suggested that develops heuristic rules with the objective of minimisation of the number of tool changes and minimisation of the imbalance in per machine. To compare the proposed algorithm, a series of computational experiments is done on randomly generated test problems and the results show that the developed algorithm is very simple and efficient.     

An Investigation of Stochastic Analysis of Flexible Manufacturing Systems Simulation

This paper describes the use of an ARIMA (autoregressive-integrated- moving-average) model and its equivalent state space models to produce rule-based knowledge for flexible manufacturing systems (FMS) that can be used to investigate a wide variety of problems including machine breakdown, material shortage, and changes of scheduling rules. One great advantage of using the proposed models is the ease with which the simulation results can be summarised, analysed and captured, as well as the availability of the mathematical representation of the knowledge that can be kept in a knowledge database for evaluation and selection of alternative FMS strategies in a real-time environment. Various case studies are used to illustrate the methodology and the development of ARIMA and state space models, the analysis includes the system cost and stability of changes or interventions, the relationships among the simulation inputs and outputs, and the formulation of the production rule-base for the FMS scheduler. Management can use this integrated approach to describe and predict the dynamic behaviour of a complex FMS.     

Production planning of a flexible manufacturing system in a material requirements planning environment

Early flexible manufacturing system (FMS) production planning models exhibited a variety of planning objectives; typically, these objectives were independent of the overall production environment. More recently, some researchers have proposed hierarchical production planning and scheduling models for FMS. In this article, we examine production planning of FMS in a material requirements planning (MRP) environment. We propose a hierarchical structure that integrates FMS production planning into a closed-loop MRP system. This structure gives rise to the FMS/MRP rough-cut capacity planning (FMRCP) problem, the FMS/MRP grouping and loading (FMGL) problem, and the FMS/MRP detailed scheduling problem.We examine the FMRCP and FMGL problems in detail and present mathematical programming models for each of these problems. In particular, the FMRCP problem is modeled as a generalized assignment problem (GAP), and a GAP-based heuristic procedure is defined for the problem. We define a two-phase heuristic for the FMGL problem and present computational experience with both heuristics. The FMRCP heuristic is shown to solve problems that exhibit a dependent-demand relation within the FMS and with FMS capacity utilization as high as 99 percent. The FMGL heuristic requires very little CPU time and obtains solutions to the test problems that are on average within 1.5 percent of a theoretical lower bound.This FMS/MRP production planning framework, together with the resulting models, constitutes an important step in the integration of FMS technology with MRP production planning. The hierarchical planning mechanism directly provides for system-level MRP planning priorities to induce appropriate production planning and control objectives on the FMS while simultaneously allowing for necessary feedback from the FMS. Moreover, by demonstrating the tractability of the FMRCP and FMGL problems, this research establishes the necessary groundwork upon which to explore systemwide issues pertaining to the coordination of the hierarchical structure.     

An FMS scheduling and control decision support system based on generalised stochastic Petri nets

This paper presents an FMS scheduling and control DSS (decision support system) using generalised stochastic Petri nets (GSPNs) for model representation and analysis. The function of the DSS is to assist the FMS operator to search for suitable control strategies that will achieve efficient performance. It can also be called upon in the event of unforeseen changes in production requirements, component failures, or other related contingencies. The GSPN modelling approach is employed because GSPNs can characterise random processing times, machine breakdown and repair rates. The GSPN employed in the proposed DSS also incorporates dispatching control at conflicting immediate transitions and can be used to determine various performance measures pertaining to scheduling and control. An application example of the DSS for the processing of two part types in a three-machine FMS is also described.     

A fuzzy rule for job dispatching in a wafer fabrication factory—a simulation study

Job scheduling in wafer fabrication factories is subject to many sources of uncertainty or randomness. To consider the uncertainty and improve the scheduling performance in a wafer fabrication factory, this paper proposes an innovative fuzzy rule that solves the problem of slack overlapping in a non-subjective way. The fuzzy rule considers the uncertainty in the remaining cycle time and is aimed at the simultaneous optimization of the average cycle time and cycle time standard deviation. Few existing publications discuss this issue. A systematic procedure has also been established to optimize the value of the adjustable parameter in the fuzzy rule. On the other hand, a novel fuzzy back propagation network approach is also proposed in this paper to estimate the remaining cycle time accurately. The performance of the proposed methodology is evaluated with a series of production simulation experiments.