Evaluation of a software positioning tool to support SMEs in adoption of big data analytics

Big data analytics has been widely adopted by large companies to achieve measurable benefits including increased profitability,customer demand forecasting,cheaper development of products,and improved stock control.Small and medium sized enterprises(SMEs)are the backbone of the global economy,comprising of 90%of businesses worldwide.However,only 10%SMEs have adopted big data analytics despite the competitive advantage they could achieve.Previous research has analysed the barriers to adoption and a strategic framework has been developed to help SMEs adopt big data analytics.The framework was converted into a scoring tool which has been applied to multiple case studies of SMEs in the UK.This paper documents the process of evaluating the framework based on the structured feedback from a focus group composed of experienced practitioners.The results of the evaluation are presented with a discussion on the results,and the paper concludes with recommendations to improve the scoring tool based on the proposed framework.The research demonstrates that this positioning tool is beneficial for SMEs to achieve competitive advantages by increasing the application of business intelligence and big data analytics.

The Application of Knowledge Management(KM)by Small and Medium-Sized Enterprises(SME)in Manufacturing Industry

To accelerate the digital transformation of small and medium-sized manufacturing enterprises(SMEs),this study delves into the primary challenges encountered in adopting knowledge management(KM)within these organizations and identifies the essential methods for successful implementation.The objective is to provide practical recommendations for the effective adoption of KM.This research suggests that enterprises should promote knowledge management through three key approaches:enhancing employees’cognitive understanding,standardizing knowledge systems,and tailoring business scenarios to meet diverse needs.These findings offer valuable insights into the digital transformation of SMEs in the manufacturing sector,ultimately helping these businesses to remain competitive and innovative in a rapidly changing market.By addressing the specific needs and challenges faced by SMEs,this study aims to contribute to a more comprehensive understanding of how knowledge management can be leveraged to drive digital transformation and improve overall business performance.

电网不平衡下SMES变流器动态演化控制策略研究

针对超导磁储能(SMES)变流器在电网电压不平衡下的工作情况,提出一种新型非线性控制策略,即动态演化控制(DEC)。该控制方法相较于传统PI控制能有效地减小SMES因电网电压不平衡而产生的三相电流畸变以及有功、无功功率产生的二次谐波。文中根据电网不平衡下SMES变流器的工作情况设置三个工作目标;建立了基于DEC的不平衡控制方程,并在Simulink中搭建模型进行仿真分析。通过与传统PI控制作对比,DEC控制具有更强的鲁棒性,更快速的响应能力,理论分析和仿真结果验证了该控制策略的可行性和有效性。

基于SMES装置的车网系统低频振荡抑制策略

近年来,我国电气化铁路发生多起因牵引网网压低频振荡导致的机车保护装置误动作事故,对铁路安全运行造成严重的威胁.现有抑制策略多从机车侧开展,通过对机车控制器参数的修订实现抑制效果,但对于铁路行业的长远发展缺乏灵活性.针对车网系统低频振荡问题,提出从牵引网侧外接超导磁储能(Superconducting Magnetic Energy Storage,SMES)的动态抑制方案.首先,分析SMES抑制车网系统低频振荡的原理,根据车网系统低频振荡的走势对其进行分类,并依据振荡类型设定SMES接入准则;其次,建立车网系统等效阻抗模型,结合阻抗比判据和伯德图分析车网系统稳定性,对SMES接入车网系统前后系统稳定性对比分析,验证所提方案的有效性,并与传统抑制方法进行对比,验证所提方案的灵活性;最后,对单车及多车升弓并网情况下的车网系统进行仿真分析.结果表明:SMES装置接入车网系统后可快速有效地抑制车网系统低频振荡.

Delivery Service Management System Using Google Maps for SMEs in Emerging Countries

This paper proposes a Delivery Service Management(DSM)system for Small and Medium Enterprises(SMEs)that own a delivery fleet of pickup trucks to manage Business-to-Business(B2B)delivery services.The proposed DSM system integrates four systems:Delivery Location Positioning(DLP),Delivery Route Planning(DRP),Arrival Time Prediction(ATP),and Communication and Data Sharing(CDS)systems.These systems are used to pinpoint the delivery locations of customers,plan the delivery route of each truck,predict arrival time(with an interval)at each delivery location,and communicate and share information among stakeholders,respectively.The DSM system deploys Google applications,a GPS tracking system,Google Map APIs,ATP algorithms(embedded in Excel Macros),Line,and Telegram as supporting tools.To improve the accuracy of the ATP system,three tech-niques are applied considering driver behaviors.The proposed DSM system has been implemented in a Thai SME.From the process perspective,the DSM system is a systematic procedure for end-to-end delivery services.It allows the interactions between planner-driver decisions and supporting tools.The supporting tools are simple,can be easily used with little training,and require low capital expenditure.The statistical analysis shows that the ATP algorithm with the three techniques provides high accuracy.Thus,the proposed DSM system is beneficial for practitioners to manage delivery services,especially for SMEs in emerging countries.

Impact of ICTs on Core Competences of SMEs in Bukavu, DRC

Currently, it has been noticed a strong use of ICTs in several companies. The objective of this study was to analyze and measure the impact of the implementation of ICTs on the strategy and structure of management of core competence in SMEs in Bukavu, DRC. The scale used shows the good psychometric properties (χ2 = 75.045;P = 0.16;χ2/ddl = 1.471;CFI = 0.92;IFI = 0.92;RMSEA = 0.049;NFI = 0.79;GFI = 0.94;AGFI = 0.91. This study analyzed primary data collected from 195 SMEs in the city of Bukavu. Data processing was achieved using exploratory and confirmatory factor analysis and flat sorting. The results indicate that the use of ICTs by SME managers in the city of Bukavu has a positive impact on all dimensions of core competence selected in this study. They also reveal that the views of these leaders on the importance attached to the adoption of ICTs were divided and the level of ICT use was above average.

The Polish SMEs as Intelligent Organizations in an Era of Digital Transformation

The impact that the digital transformation(DT)has on businesses,suppliers,and other third parties has increased significantly now.Digital transformation means improving traditional manufacturing processes with the help of digital technologies.The goal of digital transformation is to increase production efficiency and reduce costs,improve the quality of goods and services produced,and quickly adapt to changes in the global market.The state of industrial production is constantly changing due to the instability of global,economic and political decisions,so the adoption and expansion of digital solutions based on Industry 4.0,the Internet of things,machine learning,and other technologies of the future is accelerating.With the help of these technologies,companies are trying to change approaches and find new ways to solve problems.In this article the author analyzed the phenomenon of a complex system of knowledge management with tools as SMAC,AI,IoT and Edge computing in intelligent organizations as a part of intelligent economy.The arguments are illustrated with the results of own research conducted by the author in 2021-2022 in selected SMEs from the Polish Wielkopolska Province and their reference to the general development trends in this area.

基于MPC的SMES多目标控制

模型预测控制(model predictive control,MPC)性能优越,响应迅速而且可实现多目标控制,已受到广泛关注并逐步应用于大功率变流器,特别是在具有高功重比的超导储能磁体(superconductor magnetics energy storage,SMES)控制系统中,应用前景十分广阔。本文提出的基于MPC的SMES多目标控制,不仅实现SMES线圈在储能时较高精度的电流跟踪,同时可控制SMES线圈充放电时电流变化速率,避免较大的电流冲击,而且能够提高其响应速度与精度。通过搭建仿真实验平台验证了本文提出的SMES系统储能稳流性能、功率平衡稳定性能、动态性能以及充放电速率的控制性能。并与基于PI控制的系统进行比较,结果表明基于模型预测控制的SMES系统不仅可以实现稳态时较高精度的电流跟踪,而且可以实现充放电时电流变化速率的控制。

含风电-SMES的电力系统暂态稳定概率评估

大规模风电并网给电力系统的稳定运行带来了新的挑战,储能是应对这一挑战的技术之一。以超导磁储能(SMES)为例,提出了含风电-SMES储能的电力系统暂态稳定概率评估方法。首先搭建了一个含有风电和储能的仿真测试平台,其中:风电场采用双馈型风力发电机等值模拟,储能的模型采用SMES的三阶模型。在此基础上,研究了含风电和SMES的电力系统暂态稳定概率评估的方法,重点考虑了故障扰动和风速波动等随机因素,故障扰动包括故障位置、故障类型、故障持续时间以及重合闸成功与否等。基于二分法和蒙特卡罗仿真,量化了系统失稳的风险,建立了风电场的渗透率、储能容量和系统稳定性之间的定量关系。最后,结合SMES的技术经济性分析,给出了最优储能容量计算方法。

百千焦级高温超导环型SMES磁体设计研究

高温超导SMES磁体未来的发展方向是环型磁体,目前对高温超导环型SMES磁体的概念设计比较多,但储能量主要集中在兆焦级,真正制作完成并并网实验的储能量只有千焦级。文中立足高温超导环型SMES处于实验室研究阶段的现实,用遗传算法和有限元法结合的方法对百千焦级高温超导环型SMES磁体进行了设计研究,总结出了单元线圈数量n、单元线圈内直径d和环型磁体内直径D影响磁体储能量E的规律。

基于STATCOM/SMES系统的平滑风力发电机机端电压输出的研究

恒速异步风力发电机受快速扰动的风速影响其输出的功率和电压将会出现较大波动,含该风力发电机的系统电压稳定性也会受到较大影响。鉴于此现象,通过分析异步风力发电机的功率-电压特性,从理论上研究运行状态及线路阻抗特性对含分布式电源的微网系统电压稳定性的影响,提出一种有功、无功功率解耦控制的STATCOM/SME控制结构,同时首次提出使用指数平均数指标(EXPMA)作为有功功率控制指令信号,有效平滑了风力发电机功率输出,改善了系统的电压稳定性。仿真分析验证了所提出控制结构和策略的有效性。

用于SMES的电压型换流器试验研究

为实现超导储能装置(SMES-Superconducting Magnetic Energy Storage)与输配电网之间的协调作用,达到提高电网输送容量、暂态稳定性和电压稳定性,提高配电网电能质量的目的。根据SMES的结构特点,结合目前大功率电力电子器件以及电路拓扑的发展趋势,设计了一台三单相H桥分立控制的电压型换流器(VSI-Voltage source inverter)及其控制系统平台。该电压型换流器采用三相器件独立运行结构,控制系统采用数字信号处理器(DSP-Digital Signal Processing)设计,在功能上实现了对串联于电力线路的注入电压幅值和相位的灵活控制,最后给出了一台20 kW电压型换流器原理样机对母线电压补偿功能的试验结果,试验结果表明,该电压型换流器可以满足超导储能系统的需要。

基于托卡马克超导纵场线圈的SMES-UPS变流器设计及其控制策略

基于超导托卡马克纵场线圈构成的超导磁体储能不停电电源,可用来避免由于电网嬗变或秒级跳闸使低温和真空系统掉电导致的托卡马克装置中的超导磁体失超。文中为SMES-UPS设计的是电流型变流器系统,该系统既可用作为纵场磁体正常工作时的励磁电源又可用作电网故障时关键负载的备份电源。文章对该SMES-UPS变流器的不同工作条件下的原理和控制目标做了说明,对不同控制目标提出了相应的简单易实现的控制策略,并用Matlab进行了数字仿真,验证了控制策略的可行性。

模块化级联型SMES变流器及其总分式功率无源控制策略

为实现超导磁储能系统(SMES)的大规模可扩展式应用,提高控制系统的动态性能和鲁棒性,改进级联型SMES变流器的电路拓扑,并设计基于无源控制器的总分式功率控制策略。采用二阶广义积分构造虚拟轴,实现单相电路的坐标变换;证明了无源系统反馈互联后仍保持端口受控哈密尔顿模型结构的特征,分别在交、直流侧设计控制策略,降低了控制设计的复杂度;提出总分式功率控制策略,实现系统并网总功率和各级联模块分功率的独立控制;分别在交、直流侧设计无源控制器,提高了系统控制的动态性能和稳定性。仿真分析验证了模块化级联型SMES变流器及其总分式功率无源控制策略的有效性。系统具备模块化特征,可实现灵活扩展以及各超导磁体功率的独立控制,并具有更快的响应速度、更小的超调量和更好的并网电流质量。

高温超导SMES磁体直接冷却的热分析

用G-M制冷机(5W/20K)将Bi2223带材绕制的SMES超导磁体,在10^(-3)Pa真空度下,从常温300K左右冷却到25K,得到了磁体冷却过程速率和磁体温度分布。在实验研究超导磁体降温特性的基础上,对SMES磁体的冷却过程进行了热分析,实验研究表明为使超导磁体有效地冷却和稳定运行,除了减小磁体漏热和其内部发热,有效控制热传导部件间的接触界面热阻是高温超导直接冷却磁储能装置研发应用中的关键技术问题。

旋转空间矢量算法在电压型SMES控制中的应用

研究了将旋转空间矢量算法应用于超导磁储能 (SMES)装置的可行性 ,比较分析了旋转空间矢量控制和传统矢量控制这两种控制算法在系统节点电压幅值或相位发生突变时的控制效果 ,讨论了旋转空间矢量算法在电压不对称条件下的适用性。旋转空间矢量的另一优点是可以减小计算量 ,为空间矢量控制、无差拍控制等复杂算法控制提供了条件。

SME训练Cu-Zn-Al合金的形状记忆效应研究

研究了经SME训练Cu Zn Al合金的单向记忆动作敏感性、单向形状恢复率 ηO 和双向形状恢复率 ηT。结果表明 :随训练次数增加 ,单向记忆的动作敏感性快速下降 ,当训练 10次 ,No .1和No.2合金已分别下降 5 8%和 5 4 % ,然后缓慢下降和趋于稳定 ,此时与初始值相比 ,No.1和No.2合金动作敏感性分别下降 74 %和 72 % ,分别仅有初始值 2 6 %和 2 8%。这在记忆合金驱动元件设计中有重要的参考价值。随训练次数增加 ,单向形状记忆效应先急剧下降 ,然后缓慢下降至趋于稳定。基本稳定时的单向形状恢复率不到初始值的 5 0 %。然而 ,随训练次数增加 ,位错增加 ,可能引入更多择尤取向位错 ,从而促使形成更多择尤取向马氏体 ,导致双向形状记忆效应急剧上升 ,出现峰值 ,然后缓慢降至趋于稳定。

时效和SME训练对Ti_(50)Ni_(50)合金丝记忆效应的影响

研究了不同时效热处理和形状记忆效应训练(SME)对Ti50Ni50合金丝的单程形状回复率ηs、双程回复率ηt的影响。结果表明:时效温度在300～500℃时,ηs保持在一个较高的状态,出现一个稳定的平台;时效温度从500℃升到600℃时,ηs急剧下降,550℃时下降了56.7%,600℃时下降了68.3%。时效温度在400～600℃时双程记忆效应最平稳也是最好的。随着训练次数的增加,单程记忆效应是减弱的,训练75次后的回复率仅为未经训练的60%。不同的时效温度,减弱的趋势是一致的。随着训练次数的增加,ηt显著增加,训练75次后基本稳定,回复率增加了200%,时效温度高于500℃后,训练对双程回复率影响不大。

高温超导SMES磁体的失超检测研究

失超保护是保证磁体安全运行的重要措施,而失超检测是失超保护正常动作的前提。由于SMES磁体运行工况的特殊性,现有失超检测方法在失超信号提取上遇到电磁噪声干扰严重的问题。文中针对高温超导SMES的运行工况,对电桥检测法进行了改进,通过对电桥信号的滤波设计解决电磁噪声干扰,设计了一套适用于高温超导SMES磁体在交变电流情况下的失超检测系统,同时进行了高温超导磁体的失超检测实验。实验结果表明,此系统能快速、准确地检测失超信号,并输出保护动作信号。

基于BPGM-SME和改进UKF的双星多目标跟踪算法

重点研究多传感器协同探测对多目标的跟踪问题。首先,根据观测几何分析双星协同探测的可观测性建立基于重力转弯模型的主动段状态方程和观测方程;其次,针对多目标跟踪情形中的航迹交叉跟踪异常问题,提出基于二元多项式思想的SME滤波算法;最后,为提高目标跟踪精度,提出基于迭代思想的改进无迹卡尔曼滤波算法。仿真结果表明:采用基于二元多项式思想的测量方程(BPGM-SME)算法对多个目标跟踪都能分别得到较好的跟踪效果,与扩展卡尔曼滤波(UKF)算法相比,改进算法能够取得更好的收敛性效果,跟踪精度也更高。