Application of the Just-in-Time Teaching(JiTT)Model in Bilingual Courses of Chinese-Foreign Cooperative Education

The teaching abilities of bilingual teachers have emerged as one of the major bottlenecks hindering the further development of Chinese-foreign cooperative education projects.Implementing the JiTT(Just-in-Time Teaching)model in bilingual courses of Chinese-foreign cooperative education can effectively integrate information technology with traditional classroom teaching.This integration enhances teaching quality and effectiveness,encourages university instructors to improve their diverse and collective capabilities,promotes digital development,and contributes to the enhancement of students’learning abilities and overall improvement.

库存控制系统中MRP和JIT的比较研究

在企业的库存控制系统中,MRP和JIT构成了两种关键的库存管理形式。现代企业如何采用科学的管理方式来优化企业的库存资源配置,促使库存管理的效率提升,成为企业需要应对的关键问题。通过对比MRP和JIT的异同之处,能够为企业提供完善库存控制系统的重要保障,确保企业在建立库存控制系统时能够采用可行性最佳的方案。

客车制造企业供应链JIT优化策略研究

随着市场经济的发展,客车制造企业面临日益激烈的市场竞争和客户需求变化,供应链管理成为其核心竞争力提升的关键。论文旨在探讨和优化客车制造企业中供应链管理中的JIT(即时生产)运作策略,确保企业生产效率和响应速度的同步提升。论文通过数据分析和现场问题调研,确定了影响企业供应链JIT运作的关键因素,并在此基础上构建了一套完整的优化策略框架。研究结果表明,通过优化原材料采购、生产流程、库存控制及物流配送等环节,显著提高了整个供应链的效率和灵活性。论文提出的JIT优化措施可为同行业内其他企业提供借鉴,具有良好的理论价值与实际应用意义。

JIT对出版企业提升利润率的启示

随着传统出版物市场被不断压缩,出版企业去库存、提利润已迫在眉睫。JIT在20世纪70年代帮助丰田公司大获成功,对出版企业同样具有借鉴意义。本文着眼于JIT提升利润率的儿大因素,对出版企业如何将JIT为已所用提出建议。

基于互信息和Just-in-Time优化的回声状态网络

为了提高回声状态网络(ESN)的适应性,提出基于互信息(MI)和Just-in-Time(JIT)的优化方法,对ESN的输入伸缩参数以及输出层进行优化,所得网络称为MI-JIT-ESN.ESN的优化方法分为两部分:一是基于网络输入与输出之间的互信息,对网络的多个输入伸缩参数进行调整;二是基于JIT优化的局部输出层,对ESN的隐层输出数据进行局部重新建模,从而提升ESN输出层的回归拟合精度.将MI-JIT-ESN应用于青霉素补料分批发酵过程建模.结果显示,MI-JIT优化方法能提高模型的适应性,并优于其他比较方法.

Calibration of soft sensor by using Just-in-time modeling and Ada Boost learning method

Soft sensor is an efficacious solution to predict the hard-to-measure target variable by using the process variables.In practical application scenarios, however, the feedback cycle of target variable is usually larger than that of the process variables, which causes the deficiency of prediction errors. Consequently soft sensor cannot be calibrated timely and deteriorates. We proposed a soft sensor calibration method by using Just-in-time modeling and Ada Boost learning method. A moving window consisting of a primary part and a secondary part is constructed.The primary part is made of history data from certain number of constant feedback cycles of target variable and the secondary part includes some coarse target values estimated initially by Just-in-time modeling during the latest feedback cycle of target variable. The data set of the whole moving window is processed by Ada Boost learning method to build an auxiliary estimation model and then target variable values of the latest corresponding feedback cycle are reestimated. Finally the soft sensor model is calibrated by using the reestimated target variable values when the target feedback is unavailable; otherwise using the feedback value. The feasibility and effectiveness of the proposed calibration method is tested and verified through a series of comparative experiments on a pH neutralization facility in our laboratory.

Just-in-time learning based integrated MPC-ILC control for batch processes

Considering the two-dimension(2 D) characteristic and the unknown optimal trajectory problem of the batch processes, an integrated model predictive control-iterative learning control(MPC-ILC) for batch processes is proposed in this paper. Firstly, the batch-axis information and time-axis information are combined into one quadratic performance index. It implies the integration of ILC and MPC algorithm idea, which leads to superior tracking performance and better robustness against disturbance and uncertainty. To address the problem of the unknown optimal trajectory, both time-varying prediction horizon and end product quality control are employed. Moreover, an integrated 2 D just-in-time learning(JITL) model is used to improve the predictive accuracy. Furthermore, rigorous description and proof are presented to prove the convergence and tracking performance of the proposed MPC-ILC strategy. The simulation results show the effectiveness of the proposed method.

A New Efficient Obstacle Avoidance Control Method for Cars Based on Big Data and Just-in-Time Modeling

This paper provides a new obstacle avoidance control method for cars based on big data and just-in-time modeling. Just-in-time modeling is a new kind of data-driven control technique in the age of big data and is used in various real systems. The main property of the proposed method is that a gain and a control time which are parameters in the control input to avoid an encountered obstacle are computed from a database which includes a lot of driving data in various situations. Especially, the important advantage of the method is small computation time, and hence it realizes real-time obstacle avoidance control for cars. From some numerical simulations, it is showed that the new control method can make the car avoid various obstacles efficiently in comparison with the previous method.

Minimizing Distance Using Just-in-Time Teaching and Flipped Classroom

JiTT （Just-in-Time Teaching） and flipped classroom are two innovations in academia where high-tech and no-tech resources are blended to encourage more interaction and creativity among students. These two methods also help minimize the dependency on face-to-face lecture and make the class time more creative and effective. This study is the very first attempt of implementing these strategies in Bangladesh. It explores the prospect of JiTT and flipped classroom at tertiary level in Bangladesh. In the first part of this paper, recent studies on JiTT and flipped classroom are discussed to shed light on their effectiveness and problems. The latter part explains the data and research findings. Before collecting the data, JiTT and flipped classroom were used with 33 students of undergraduate level who were students of＂ELT Methodology＂ course. After the implementation of the methods, a questionnaire survey was conducted to collect data regarding their response to these two methods. The study reveals that JiTT and flipped classroom help cover more topics in a short time while enhancing students＇ interaction and participation. They make students come to the class prepared and reflect on their learning. Teachers can understand students need better and provide required feedback. The overall interaction among students and teachers can be improved using JiTT and flipped classroom since everyone is clear about each other＇s existing knowledge and learning objectives.

Supervised local and non-local structure preserving projections with application to just-in-time learning for adaptive soft sensor

In soft sensor field, just-in-time learning(JITL) is an effective approach to model nonlinear and time varying processes. However, most similarity criterions in JITL are computed in the input space only while ignoring important output information, which may lead to inaccurate construction of relevant sample set. To solve this problem, we propose a novel supervised feature extraction method suitable for the regression problem called supervised local and non-local structure preserving projections(SLNSPP), in which both input and output information can be easily and effectively incorporated through a newly defined similarity index. The SLNSPP can not only retain the virtue of locality preserving projections but also prevent faraway points from nearing after projection,which endues SLNSPP with powerful discriminating ability. Such two good properties of SLNSPP are desirable for JITL as they are expected to enhance the accuracy of similar sample selection. Consequently, we present a SLNSPP-JITL framework for developing adaptive soft sensor, including a sparse learning strategy to limit the scale and update the frequency of database. Finally, two case studies are conducted with benchmark datasets to evaluate the performance of the proposed schemes. The results demonstrate the effectiveness of LNSPP and SLNSPP.

Online Batch Process Monitoring Based on Just-in-Time Learning and Independent Component Analysis

A new method was developed for batch process monitoring in this paper. In the devdopad method, just-in-time learning （ JITL ） and independent component analysis （ICA） were integrated to build JITL-ICA monitoring scheme. JITL was employed to tackle with the characteristics of batch process such as inherent time- varying dynamics, multiple operating phases, and especially the case of uneven length stage. According to new coming test data, the most correlated segmentation was obtained from batch-wise unfolded training data by JITL. Then, ICA served as the principal components extraction approach. Therefore, the non.Gaussian distributed data can also be addressed under this modeling framework. The effectiveness and superiority of JITL-ICA based monitoring method was demonstrated by fed-batch penicillin fermentation.

A Preliminary Study of Just-in-Time Methods for a Seamless Public Transportation Information Framework

A seamless multimodal transit system has been a goal for transportation planners and users. Owing to the developments of advanced public transportation and telecom technologies such as automatic vehicle location (AVL) and real-time passenger information system, key just-in-time (JIT) concepts can now be realized in process design and coordinated scheduling to shape a seamless multimodal transit system. JIT refers to a production system that times both movements of goods during production and delivery from suppliers together. It meets the same logic for seamless multimodal services. Therefore, this study innovatively analyzes possible public transportation technologies for JIT uses;moreover, to layout the possible application frame-work of a transportation technology based JIT multimodal transit system for main station area in Taipei city. With this innovative framework, multimodal transit services can deliver to the right place at right time.

Just-In-Time Hypermedia

Many analytical or computational applications create documents and display screens in response to user queries “dynamically” or in “real time”. Hypermedia features must be generated “just in time” – automatically and dynamically. Conversely, the hypermedia features may have to cause target documents to be generated or re-generated. This paper presents a just-in-time hypermedia framework to provide hypermedia support of virtual documents.

Minimizing Products Rates Variation in Just-in-Time Mixed-Model Manufacturing

Mixed-Model assembly lines are often used in manufacturing based on just-in-time techniques. The effective utilization of these lines requires a schedule for assembling the different models be determined. The objective is to minimize the total deviation of actual production rates from the desired production rates. Mathematical method with the optimization algorithm is proposed here to solve this problem. To prove the efficiency of the proposed algorithm, a number of test problems are solved. The results show that the proposed algorithm is an efficient and effective algorithm which gives better results with the large problem sizes. This paper presents a practical procedure to minimize total product variation rates, and easy to use by practitioner.

基于“Just-in-Time”原理的信息系统的综合发展

研究了提高解决商业问题的信息技术设备利用率的问题。研究了解决上述问题的方法：改进信息系统；提高信息技术设备培训的强度；改善实用问题解决过程的文件编制；改进信息技术设备的应用规划；在准时制（Just－in－TimeSystem）的组织原理基础上，改善信息技术设备应用过程的管理和标准化。还研究了下列问题：提高信息技术设备对用户需求的满足程度；信息技术设备应用过程的结构化；提高计算机应用对管理质量影响的客观性；研究信息技术设备的合理基础设施。较大注意力集中在最有效的信息技术设备的基础上和应用服务器的最佳状态下，保证信息系统灵活的发展。对在现有技术和财政限制情况下，发展信息技术设备的分阶段的规划方法进行了说明。强调指出了，综合发展信息技术设备基本元件（计算技术设备、保证设备及其基础设施）的重要性。

JIT在企业转型中的应用探析

在企业转型升级过程中,存在各种各样适合企业自身需要的发展模式。从企业的发展现状和实际困境出发,围绕队伍建设、质量管理、设备运维、制度标准、数字信息等多个方面探析JIT推行的可行性,为JIT的生产理念做适应性探究。

JIT模式下仓储实践

传统仓储管理模式已不能适应新的仓储管理需求。尤其是当前汽车行业下行的大趋势下,构建创新型的仓储管理信息化系统平台,协调各个环节的运作,提高仓库的作业水平、人员操作效率和仓库利用率,从而增强企业市场竞争力。一、背景结合当前厂内仓储管理实践经验,剖析现场物流运作的难点与痛点,发现在管理过程中,除了“人”这个不可控的变量因素影响外,工具及方法的影响力也很大,经过总结,当前我们主要面临以下的问题:1.供应商拉动准确率低,不按拉动到货率高;2.传统到货时间窗跟踪,目视指导意义弱,无法精准监控;3.线旁物料拉动信号延迟。

基于自适应邻域模拟退火算法的零部件接收与转运优化

现代混线生产对于多品种小批量零部件物流的准确度和准时性提出更高要求,其中零部件接收与转运是管理者面临的首要难题,需要考虑三种情形,一是供应商的卡车交付与装配线需求均具有时间窗口;二是车辆调度问题,即决定每个仓库门服务的车辆的处理顺序;三是车辆分配问题,即每辆牵引车承载的需求,这大大提升了问题的复杂性。为优化零部件接收与转运,本文建立一套考虑准时制的零部件超市物流模式,将交叉转运应用于工厂物流管理,研究了中心仓侧的车辆分配与调度问题(Vehicle Assignment and Scheduling Problem,VASP),并对问题进行了建模和线性化处理。由于该类问题的内在复杂性,本文设计一种自适应邻域模拟退火算法(Adaptive Neighborhood Simulated Annealing,ANSA),并将其与先进的商业优化求解器进行比较。本文开展了大量计算数值实验,结果表明ANSA算法在不同规模的算例上均有较好表现。

基于JIT的多目标总装准时物料配送方法研究

针对机械产品总装过程中的准时物料配送问题,从优化目标、约束条件及影响因素三方面考虑,提出以物料运输成本、物料运输时间、线旁库存三者综合为优化目标的多目标准时物料配送模型。给出优化目标的计算方法,并设计了混合粒子群算法,给出了使用此算法求解模型的具体实现过程。最终求解得到物料配送单用于指导配送,使决策者能够根据实际情况选择优化的偏好值。通过一个总装车间准时物料配送问题的实例验证了此模型和算法的有效性。

MRPII、JIT、TOC生产计划与控制比较研究

在对MRPII、JIT、TOC三种生产管理思想的适用性和优缺点分析、比较的基础上,在生产计 划与控制的不同层面,根据不同要求,对MRPII、JIT、TOC 进行了定位分析,并把MRPII定 位在厂级或企业级,负责主生产计划、物料需求及各车间零部件的月、周计划;TOC定位在车 间级,负责车间或工段工序日作业计划与调度、物料的投放;JIT定位在生产现场,负责作业 计划的执行、生产的控制和现场的反馈。