A survey of simulation modeling techniques in production planning and control (PPC)

The manufacturing sector as a whole has undergone remarkable changes in terms of scale, complexity and technology over the past decades and this applies across most modern high-technology manufacturing such as electronics, semiconductor, aerospace and automotive industries. In order to remain competitive, manufacturers have to produce high-quality products at low cost, and at the same time retain sufficient flexibility and to meet rapidly changing customer demands. Production planning and control (PPC) is a key role which enables the manufacturer to gain visibility and control over all aspects of manufacturing activities. PPC in itself forms a subject of study, within which simulation techniques have proven themselves to be one of the most practical methodologies available to investigate and evaluate manufacturing issues. In this review paper, we focus on state-of-the art applications of simulation techniques in PPC to demonstrate their applicability to modern manufacturing issues. The review reports on academic publications on simulation applications in manufacturing from 2002 to 2014, incorporating surveys of peer-reviewed literature. The review covers three types of simulation techniques (system dynamic, discrete event simulation and agent-based simulation) and eight PPC issues (facility resource planning, capacity planning, job planning, process planning, scheduling, inventory management, production and process design, purchase and supply management). Literature survey is analysed on the basis of simulation application to PPC problems which can give a guideline for simulation technique selection and also can help for simulation modelling in PPC problemsWould you consider changing the term “modeling” to “modelling” in the title. Please check, and correct if necessary.     

Achieving manufacturing excellence through the integration of enterprise systems and simulation

This paper discusses the significance of the enterprise systems and simulation integration in improving shop floor’s short-term production planning capability. The ultimate objectives are to identify the integration protocols, optimisation parameters and critical design artefacts, thereby identifying key ‘ingredients’ that help in setting out a future research agenda in pursuit of optimum decision-making at the shop floor level. While the integration of enterprise systems and simulation gains a widespread agreement within the existing work, the optimality, scalability and flexibility of the schedules remained unanswered. Furthermore, there seems to be no commonality or pattern as to how many core modules are required to enable such a flexible and scalable integration. Nevertheless, the objective of such integration remains clear, i.e. to achieve an optimum total production time, lead time, cycle time, production release rates and cost. The issues presently faced by existing enterprise systems (ES), if properly addressed, can contribute to the achievement of manufacturing excellence and can help identify the building blocks for the software architectural platform enabling the integration.     

Bayesian deconvolution of oil well test data using Gaussian processes

We use Bayesian methods to infer an unobserved function that is convolved with a known kernel. Our method is based on the assumption that the function of interest is a Gaussian process and, assuming a particular correlation structure, the resulting convolution is also a Gaussian process. This fact is used to obtain inferences regarding the unobserved process, effectively providing a deconvolution method. We apply the methodology to the problem of estimating the parameters of an oil reservoir from well-test pressure data. Here, the unknown process describes the structure of the well. Applications to data from Mexican oil wells show very accurate results.     

A new modified Jackknifed estimator for the Poisson regression model

The Poisson regression is very popular in applied researches when analyzing the count data. However, multicollinearity problem arises for the Poisson regression model when the independent variables are highly intercorrelated. Shrinkage estimator is a commonly applied solution to the general problem caused by multicollinearity. Recently, the ridge regression (RR) estimators and some methods for estimating the ridge parameter k in the Poisson regression have been proposed. It has been found that some estimators are better than the commonly used maximum-likelihood (ML) estimator and some other RR estimators. In this study, the modified Jackknifed Poisson ridge regression (MJPR) estimator is proposed to remedy the multicollinearity. A simulation study and a real data example are provided to evaluate the performance of estimators. Both mean-squared error and the percentage relative error are considered as the performance criteria. The simulation study and the real data example results show that the proposed MJPR method outperforms the Poisson ridge regression, Jackknifed Poisson ridge regression and the ML in all of the different situations evaluated in this paper.     

“汽车电子与仿真测试”课程中活动引导式教学方法的应用与实践

活动引导式教学法是一种教师在教学过程中,发挥引导作用,在强化学生主体地位的同时,为学生提供特定的学习情景,提高学生的自主学习能力,加深学生对知识的理解以及对实际技能的掌握的一种教学方法。在分析上海理工大学光电学院"汽车电子与仿真测试"课程教学现状的基础上,介绍了活动引导式教学的相关概念,引出了行为活动式教学法在"汽车电子与仿真测试"课程教学中的应用与实践。     

人体对手机辐射吸收剂量的仿真研究

基于时域有限差分法在两种电磁辐射源作用下,对人体组织的局部比吸收量分布进行了数值分析计算,并利用三维数值电磁仿真软件对人体局部的比吸收率分布进行了仿真分析计算。结果表明,人体组织对电磁辐射吸收剂量的分布极不均匀,它与辐射频率、辐射强度、暴露时间以及人体组织的导电率、介电常数等多种参数有关。仿真研究表明减少手机表面电流、避开人体谐振频率可以减少人体的比吸收率。     

基于系统动力学的配送中心仓储系统研究

配送中心仓储系统的优化目标是使库存量尽量小而又能保证不会缺货。本文选用系统动力学方法时配送中心仓储系统进行深入分析，在进行系统边界分析与系统因果关系分析后，建立起配送中心面向三店铺配送的系统动力学流图与方程体系，并结合实例进行计算机仿真模拟。最后得出配送中心优化方向的相关结论——提高需求预测的准确性、减少供货延迟时间、增加库存调节时间及加强信息沟通机制。     

并联型有源电力滤波器的滞环空间矢量控制

本文分析了与滞环相结合的空间矢量PwM的基本控制原理,并将该方法应用到并联型有源电力滤波器的控制中。利用Matlab进行了仿真研究,结果表明有源滤波器在任一时刻输出的补偿电流均能实时地跟踪指令电流,有效减小电流补偿误差,达到消除非线性负载所引起的谐波电流对电网污染的目的。     

修正FTF算法用于高速数传快衰落信道自适应均衡的研究

短波高速数传是当前通信领域研究的一个重要方面,克服这类信道快衰落时变特性给数传带来的障碍是研究的中心课题.近些年提出和探讨的最小平方自适应均衡新技术,人们认为是解决这一问题的有效途径,普遍为人关注.本文对作者已提出的计算复杂度低、稳定性良好的修正 FTF 自适应均衡算法作了进一步研究.考查了其硬件实现方面的问题并模拟分析了均衡性能,初值选取,最佳级数和启动时训练与否的影响等,得出了许多有益的结论.这些分析与讨论对于硬件实现是十分必要的.     

热力对象建模与控制仿真研究

系统介绍了仿真平台的构成及共享内存设计、多编译器嵌入、多进程多任务设计等核心技术。该平台通过OP C技术,实现与Matlab/Simulink的通信,并以水位三冲量调节系统为例进行了仿真建模。经应用实践表明,该系统稳定可靠,通用性强,能够满足实际热力系统建模与控制方案设计的需要。