Research efforts to improve performance of production systems

In order to solve the problem of low efficiency of production systems, a lot of work has been done. The research efforts to improve the performance of production systems are summed up here and future research directions are discussed at last.

PARAMETRIC MATCHING SELECTION OF MULTI-MEDIUM COUPLING SHOCK ABSORBER

To achieve the dual demand of resisting violent impact and attenuating vibration in vibration-impact-safety of protection for precision equipment such as MEMS packaging system, a theo- retical mathematical model of multi-medium coupling shock absorber is presented. The coupling of quadratic damping, linear damping, Coulomb damping and nonlinear spring are considered in the model. The approximate theoretical calculating formulae are deduced by introducing transformation-tactics. The contrasts between the analytical results and numerical integration results are developed. The resisting impact characteristics of the model are also analyzed in progress. In the meantime, the optimum model of the parameters matching selection for design of the shock absorber is built. The example design is illustrated to confirm the validity of the modeling method and the theoretical solution.

A Portfolio Selection Method Based on Pattern Matching with Dual Information of Direction and Distance

Pattern matching method is one of the classic classifications of existing online portfolio selection strategies. This article aims to study the key aspects of this method—measurement of similarity and selection of similarity sets, and proposes a Portfolio Selection Method based on Pattern Matching with Dual Information of Direction and Distance (PMDI). By studying different combination methods of indicators such as Euclidean distance, Chebyshev distance, and correlation coefficient, important information such as direction and distance in stock historical price information is extracted, thereby filtering out the similarity set required for pattern matching based investment portfolio selection algorithms. A large number of experiments conducted on two datasets of real stock markets have shown that PMDI outperforms other algorithms in balancing income and risk. Therefore, it is suitable for the financial environment in the real world.

Molecular engineering binuclear copper catalysts for selective CO_(2) reduction to C_(2) products

Molecular copper catalysts serve as exemplary models for correlating the structure-reaction-mechanism relationship in the electrochemical CO_(2) reduction(eCO_(2)R),owing to their adaptable environments surrounding the copper metal centres.This investigation,employing density functional theory calculations,focuses on a novel family of binuclear Cu molecular catalysts.The modulation of their coordination configuration through the introduction of organic groups aims to assess their efficacy in converting CO_(2) to C_(2)products.Our findings highlight the crucial role of chemical valence state in shaping the characteristics of binuclear Cu catalysts,consequently influencing the eCO_(2)R behaviour,Notably,the Cu(Ⅱ)Cu(Ⅱ)macrocycle catalyst exhibits enhanced suppression of the hydrogen evolution reaction(HER),facilitating proton trans fer and the eCO_(2)R process.Fu rthermore,we explo re the impact of diverse electro n-withdrawing and electron-donating groups coordinated to the macrocycle(R=-F,-H,and-OCH_3)on the electron distribution in the molecular catalysts.Strategic placement of-OCH_3 groups in the macrocycles leads to a favourable oxidation state of the Cu centres and subsequent C-C coupling to form C_(2) products.This research provides fundamental insights into the design and optimization of binuclear Cu molecular catalysts for the electrochemical conversion of CO_(2) to value-added C_(2) products.

Simultaneous hydrogen production with the selective oxidation of benzyl alcohol to benzaldehyde by a noble‐metal‐free photocatalyst VC/CdS nanowires

In this work we used CdS NWs(nanowires)with vanadium carbide(VC)attached via facile electrostatic self‐assembly and calcination method.The results showed that compared to pristine CdS NWs,the photocatalytic activity of CdS NWs loaded with the particular amount of VC was dramatically enhanced.Among them,the VC/CS‐15 indicated the highest enhancement for simultaneous production of H2 with selective oxidation of benzyl alcohol(BO)into benzaldehyde(BD).The highest hydrogen evolution rate of 20.5 mmol g^(-1)h^(-1)was obtained with more than 99%selectivity for BD production under visible light(λ˃420 nm)irradiation for 2 h,which was almost 661 times higher than the pristine CdS NWs.This enhancement of photocatalytic activity is due to the VC,which provides a favorable attraction for BO by lowering the zeta potential,along with the active site for hydrogen production,and retard the recombination of electron‐hole pairs by increasing the conductivity of the photocatalyst.Moreover,the apparent quantum efficiency(AQE)of VC/CS‐15 for BD and H_(2)production at monochromatic 420 nm is about 7.5%.At the end of the hydrogen evolution test,the selective oxidation with more than 99%selectivity was obtained.It hopes this work will prove its future significance and move scientific community toward a more economical way for achieving the commercialization of H_(2) by photocatalysis.

Evaluation of Gray Leaf Spot Tolerant Genotypes from CIMMYT in the Highland Maize Production Eco-systems of Bhutan

Bhutan is a small landlocked country located in the eastern Himalayas. Over 69% of the population is engaged in agriculture. Rice, maize, wheat, barley, buckwheat and millets are the major cereal crops cultivated. Rice is the most preferred food crop of the Bhutanese. Maize is a primary food crop after rice and it ranks first among food crops in production. The cultivation ranges from less than 300 m asl （metres above sea level） nearly up to 2,800 m asl. In 2007, a new, extremely serious problem of GLS （gray leaf spot） in maize that was previously never reported in Bhutan was confirmed. This disease spread rapidly in the highland maize growing areas causing production losses of over 50% to 70%. All the maize varieties cultivated in the country were found to be highly susceptible to the disease. In order to contain this devastating disease, the national maize program drew short and long term strategies with the help of a CIMMYT Expert. As an immediate short term action to contain GLS, systemic fungicide Tilt 25 EC （active ingredient propiconazole） was supplied free of cost to the farmers. A longer term strategy pursued was the introduction, e＇valuation and selection of GLS tolerant genotypes for the highland ecosystem. Over 100 GLS tolerant genotypes vcere introduced from CIMMYT Colombia, Mexico, Zimbabwe and Nepal. These materials were initially evaluated in a disease hotspot sites and then further tested in multi-location trials in GLS affected areas across the country. Farmers were engaged for Participatory Variety Selection by organizing farmer＇s field days at the trial sites. Finally, in 2011 considering the need of GLS tolerant varieties for farmers, two GLS tolerant genotypes ICAV305 and S03TLYQAB05 were provisionally released. In the 2011 season, these two provisionally released genotypes were put under large scale demonstration in the GLS affected areas in nine districts across the country. In 2012, the two genotypes were formally released by the Technology Release Committee of the Ministry of Agriculture and Forest. Rapid seed increase of the new varieties was initiated through farmers from Community Based Seed Production groups and so far 75% seed replacement of GLS affected farmers has been accomplished.

Concepts for Sensor Matching in Mechatronic Systems

A typical mechatronic system consists of a multitude of components,and the sensors belong to an important and crucial class of such components.Optimal matching of the system components is implicit in the current definition of a mechatronic system.The focus of the present paper is the optimal matching of sensors with other hardware in the system.Sensor matching may be based on several concepts such as the operating frequency range(operating bandwidth),speed of response(and the corresponding rate of data sampling in digital conversion),the device sensitivity(or gain or data amplification),and the effect of component acc uracy on the overall accuracy of the system.The present paper explores all these concepts and presents suit able approaches for sensor matching through those criteria.The relevant procedures are illustrated using case studies.

System Analysis of New Product Family Development Selection

This paper presents a new approach to the selection of new product family development. First,the factors are discussed that contribute to the new product family development. Due to the vagueness and uncertain existing in the factors,the fuzzy continue-semantic scale is introduced. Then,the fuzzy analytic hierarchy process (AHP) has been used in weighting the importance of the factors. Next,the fuzzy clustering method is applied to the selection of new product family developments. Lostly,one case is provided to illustrate the proposed approach.

A significant quantitative trait locus on chromosome Z and its impact on egg production traits in seven maternal lines of meat-type chicken

Background:Egg production is economically important in the meat-type chicken industry.To better understand the molecular genetic mechanism of egg production in meat-type chicken,genetic parameter estimation,genome-wide association analyses combined with meta-analyses,Bayesian analyses,and selective sweep analyses were performed to screen single nucleotide polymorphisms(SNPs)and other genetic loci that were significantly associated with egg number traits in 11,279 chickens from seven material lines.Results:Yellow-feathered meat-type chickens laid 115 eggs at 43 weeks of age and white-feathered chickens laid 143 eggs at 60 weeks of age,with heritability ranging from 0.034–0.258.Based on meta-analyses and selective sweep analyses,one region(10.81–13.05 Mb)on chromosome Z was associated with egg number in all lines.Further analyses using the W2 line was also associated with the same region,and 29 SNPs were identified that significantly affected estimation of breeding value of egg numbers.The 29 SNPs were identified as having a significant effect on the egg number EBV in 3194 birds in line W2.There are 36 genes in the region,with glial cell derived neurotrophic factor,DAB adaptor protein 2,protein kinase AMP-activated catalytic subunit alpha 1,NAD kinase 2,mitochondrial,WD repeat domain 70,leukemia inhibitory factor receptor alpha,complement C6,and complement C7 identified as being potentially affecting to egg number.In addition,three SNPs(rs318154184,rs13769886,and rs313325646)associated with egg number were located on or near the prolactin receptor gene.Conclusion:Our study used genomic information from different chicken lines and populations to identify a genomic region(spanning 2.24 Mb)associated with egg number.Nine genes and 29 SNPs were identified as the most likely candidate genes and variations for egg production.These results contribute to the identification of candidate genes and variants for egg traits in poultry.

Impedance Matching Algorithm for Selection of Suitable Explosives for Any Rock Mass-A Case Study

Proper selection of the explosive is an important part of blast design.The judicious selection of explosives is governed by economic considerations and site/field conditions.The mine management desires to select an explosive that will give the lowest cost per unit of rock broken,while assuring that fragmentation,fragment size distribution,muck pile profile,muck pile diggability,displacement of the rock,onset of movement,face movement,burden relief rate,ground vibration and noise remains within control limits.Factors which influence the selection of an explosive include explosive cost,charge diameter,cost of drilling,fragmentation difficulties and fragment size requirement with loose muck pile condition,water conditions,atmospheric temperature,propagating ground,storage considerations,sensitivity considerations,explosive atmospheres and nearness of communities from mine.All these concerns can be handled effectively by using the impedance matching technology where explosive impedance is matched with rock impedance for optimal blast performance with due concern to productivity,economics and environment.This paper discusses a case study in limestone mines where rock impedance was determined by carrying out surface refraction test and a patented algorithm was used to estimate the explosives’properties i.e.VOD(velocity of detonation)and density of explosives required.

A Load-Fairness Prioritization-Based Matching Technique for Cloud Task Scheduling and Resource Allocation

In a cloud environment,consumers search for the best service provider that accomplishes the required tasks based on a set of criteria such as completion time and cost.On the other hand,Cloud Service Providers(CSPs)seek to maximize their profits by attracting and serving more consumers based on their resource capabilities.The literature has discussed the problem by considering either consumers’needs or CSPs’capabilities.A problem resides in the lack of explicit models that combine preferences of consumers with the capabilities of CSPs to provide a unified process for resource allocation and task scheduling in a more efficient way.The paper proposes a model that adopts a Multi-Criteria Decision Making(MCDM)method,called Analytic Hierarchy Process(AHP),to acquire the information of consumers’preferences and service providers’capabilities to prioritize both tasks and resources.The model also provides a matching technique to assign each task to the best resource of a CSP while preserves the fairness of scheduling more tasks for resources with higher capabilities.Our experimental results prove the feasibility of the proposed model for prioritizing hundreds of tasks/services and CSPs based on a defined set of criteria,and matching each set of tasks/services to the best CSPS.

SA-MSVM:Hybrid Heuristic Algorithm-based Feature Selection for Sentiment Analysis in Twitter

One of the drastically growing and emerging research areas used in most information technology industries is Bigdata analytics.Bigdata is created from social websites like Facebook,WhatsApp,Twitter,etc.Opinions about products,persons,initiatives,political issues,research achievements,and entertainment are discussed on social websites.The unique data analytics method cannot be applied to various social websites since the data formats are different.Several approaches,techniques,and tools have been used for big data analytics,opinion mining,or sentiment analysis,but the accuracy is yet to be improved.The proposed work is motivated to do sentiment analysis on Twitter data for cloth products using Simulated Annealing incorporated with the Multiclass Support Vector Machine(SA-MSVM)approach.SA-MSVM is a hybrid heuristic approach for selecting and classifying text-based sentimental words following the Natural Language Processing(NLP)process applied on tweets extracted from the Twitter dataset.A simulated annealing algorithm searches for relevant features and selects and identifies sentimental terms that customers criticize.SA-MSVM is implemented,experimented with MATLAB,and the results are verified.The results concluded that SA-MSVM has more potential in sentiment analysis and classification than the existing Support Vector Machine(SVM)approach.SA-MSVM has obtained 96.34%accuracy in classifying the product review compared with the existing systems.

Tensile stress enhanced dynamic oxygen vacancies on interlayer stretched Bi_(2)O_(2)CO_(3) as pivotal knobs to promote sustainable selective CO_(2) photoreduction

Surface oxygen vacancies(OVs) with abundant localized electrons on bismuth-oxygen based photocatalysts are proved to have the ability to capture and activate CO_(2).However,the surface OVs are easily filled with oxygen-containing species and destroyed,losing their effects as active sites and hindering the subsequent CO_(2)photoreduction.For realistic and sustainable CO_(2)photoreduction,constructing sustainable and stable surface OVs as active sites on photocatalysts is essential.This work shows the synthesis of interlayer stretched Bi_(2)O_(2)CO_(3) ultrathin nanosheets with tensile stress,which are beneficial to continuously generating light-induced dynamic OVs.With sufficient active sites,excellent,stable,and selective photoreduction of CO_(2)to CO under simulated solar light is achieved.The light-induced OVs can reduce the energy barrier of rate-determining step,resulting in the 100% product selectivity.The results presented herein demonstrate the effect of dynamic OVs induced by interlayer tensile strain on catalysts for the enhanced selective CO_(2)photoreduction process.

Selective conversion of CO_(2)to CO using earth abundant tin modified copper gas diffusion electrodes

Earth-abundant copper-tin(CuSn)electrocatalysts are potential candidates for cost-effective and sustainable production of CO from electrochemical carbon dioxide reduction(eCO_(2)R).However,the requirement of highoverpotential for obtaining reasonable current,low Faradaic efficiencies(FE)and low intrinsic catalytic activities require the optimisation of the CuSn nanoarchitecture for the further advancement in the field.In the current work,we have optimised Sn loading on Cu gas diffusion electrodes(GDEs)by electrochemical spontaneous precipitation.Samples with various Sn loadings were tested in a three-chamber GDE reactor to evaluate their CO_(2)reduction performances.The best performance of 92%CO Faradaic efficiency at a cathodic current density of 120 mA cm^(-2)was obtained from the 20 min Sn deposited Cu_(2)O sample operated at-1.13 V vs.RHE.The electrocatalyst had~13%surface coverage of Sn on Cu GDE surface,and had Sn in oxide form and copper in metallic form.The catalyst also showed stable performance and was operable for>3 h under chronoamperometric conditions.The surface of the GDE reduces from Cu2O to Cu during eCO_(2)R and goes further reconstruction during the eCO_(2)R.This study demonstrates the potential of Cu-Sn for selective CO production at high current densities.

一个包含数据要素的经济增长模型:生产率效应与数据要素化

数字经济时代,数据成为独立生产要素,是科技创新的新引擎和经济高质量发展的新动能。从纯数字资产与数据匹配性投入共同组成数据要素化投入的角度理解数据生产要素化,使用数据匹配性投入综合得分对中国数据要素化投入进行时空分析和生产率效应分析。结果表明,中国数据要素化投入存在明显的区域差异,基于数据要素化投入对经济产出的积极作用,其对区域经济协调发展具有重要作用;数据匹配性投入价格持续下降会影响生产要素间的交互作用,数据生产要素的使用带来生产方式的根本变革;数据生产要素化基于数据间的互联互通和经济融合,能够加快数据确权,促进生产要素合理配置,从而推动产业创新和经济高质量发展。

领军企业创新链模式研究:基于不同创新情境的多案例分析

加快构建领军企业创新链是我国科技发展征程中面临的一个重要理论和现实问题.然而,目前对领军企业创新链的模式尚缺乏深入研究.本文聚焦产品类型和技术创新路径这两个重要的情境因素,选择四家分属不同情境的中国领军企业作为案例企业,通过对案例企业在其关键产品研发中的创新链部署过程进行多案例比较分析,探究领军企业创新链的模式及其与创新情境的匹配.研究发现,产品类型和技术创新路径对领军企业创新链的结构与运行特征产生重要影响;通过在数据资料中对案例企业创新链部署过程进行扫描,分别从创新链的结构与运行视角对不同情境下领军企业创新链的特征进行了归纳,提炼了领军企业创新链的四种模式,分别是:“共生开放型”、“线性开放型”、“共生聚合型”和“线性聚合型”;并采用模式匹配技术构建了情境因素与领军企业创新链模式之间的关联.研究结论可以为不同行业的领军企业根据所处情境有效部署创新链提供理论指导,并为政府制定创新链相关政策提供有效参考.

基于地貌分区的湖北省粮食生产格局与耕地资源匹配关系研究

【目的】研究不同地貌区粮食生产格局与区域耕地资源的匹配关系,为粮食生产布局和耕地资源保护提供决策依据。【方法】采用集中度、变异系数、重心模型、匹配度和LMDI模型等研究湖北省1990—2020年不同地貌区粮食生产格局变化与耕地资源的匹配关系。【结果】1990—2020年鄂西山地、鄂中岗地、鄂东丘陵、江汉平原粮食产量占湖北省粮食总产量的比重逐步调整为11.2%、30.6%、26.2%、32.0%。近30年湖北省各地貌区粮食作物生产集中度及变化趋势存在显著差异,粮食生产向鄂中岗地集中的趋势明显,以小麦和玉米为主,大豆生产则向江汉平原集中。湖北省粮食播种面积重心和粮食产量重心向西北方向移动了5.37和14.63 km,但鄂中岗地粮食生产重心向东北方向移动,江汉平原和鄂西山地则向西南移动。近30年来,鄂西山地、鄂中岗地、鄂东丘陵、江汉平原粮食生产与耕地资源重心的平均空间距离为6.20、3.35、10.57、6.82 km,变动一致性平均指数分别为0.49、0.44、0.40、0.27。湖北省粮食生产与耕地资源的基尼系数均大于0.5,且有增加趋势,鄂西山地和江汉平原不平衡指数为正,鄂中岗地与鄂东丘陵不平衡指数为负。近30年各地貌区粮食产量变化的耕地数量效应与结构效应为负,耕地集约效应和质量效应为正,其中耕地种植结构变化对鄂东丘陵粮食生产的减量作用达到309.70万t,而复种指数变化对鄂中岗地粮食生产的增量作用达到300.46万t。【结论】近30年湖北省各地貌区耕地质量效应和耕地结构效应的增量作用正在减弱,数量效应的减量作用在增强,湖北省面临优质耕地减少的种植风险和粮食种植结构调整带来的产量风险。湖北省粮食生产与耕地资源长期处于不匹配状态,且表现出明显的区域地理特征。粮食生产空间布局和种植结构调整应充分考虑不同地貌区自然地理和耕地资源禀赋特征,推动粮食生产与耕地利用协调发展。

电化学合成耦合可再生能源制氢:机遇与挑战

利用可再生能源实现物质和能量的转化,是发展节能减排技术、实现双碳目标的重要手段.有机电合成是一种温和、清洁、高效的物质合成方法,可以有效解决传统化工过程的高能耗和高污染问题.将电解水制氢与有机电合成耦合,利用水分解产生的活性氧/氢直接氧化/还原有机物,不仅有助于降低能耗,还可以生产高附加值有机化工产品,是提高电能利用效率、降低生产成本的有效方案.然而,尽管这种方法具有诸多优势,其工业化应用仍面临一系列难题.本文回顾了电化学合成的发展历史,探讨了氢能时代为电化学合成带来的发展机遇.同时,分析了将电化学合成与电解水耦合所面临的挑战以及未来发展方向.首先,应当慎重选择与电解水制氢耦合的阳极反应体系,其氧化产物不但要具有比反应物更高的经济价值,而且要有较大的市场需求量,以匹配制氢规模.其次,虽然在热力学上有机物氧化比析氧更容易发生,但在动力学及传质方面,有机物氧化可能存在劣势,因此必须开发适用于工业制氢电流密度(500‒2000 mA cm^(‒2))的有机物氧化电极材料.第三,阳极有机产物选择性不仅影响反应物的利用率,而且决定后续分离纯化成本,需要通过调控活性氢/氧及有机物表面的竞争吸附等手段,提高阳极目标产物选择性及法拉第效率.第四,隔膜是分离两极反应物料、防止副反应发生的重要部件.然而,现有的阴、氧离子交换膜的耐有机物腐蚀性能差,需要开发适用于电解耦合体系的、具有高离子传导能力且性能稳定的新型隔膜材料.最后,当有机物氧化与电解水耦合后,产物的分离复杂程度增加,需要将精馏、萃取、膜分离等手段与电化学反应相结合,以提升电解过程效率.综上,本文讨论了电化学合成耦合可再生能源制氢的若干技术难题,为未来电合成与氢能技术共同发展提供新思路.

基于改进遗传算法的PC构件生产调度优化

基于流水线车间生产调度理论,建立以生产成本为决策变量、以最大化生产利润为目标的数学模型;结合预制构件车间生产的实际情况,设计最优选择法、局部变异算子改进遗传算法,求解最优生产调度方案。某预制构件公司订单生产调度仿真研究表明,基于改进遗传算法的PC构件生产调度优化可以在较短的时间内获得更高的利润,为提高预制构件智能化生产效率提供了技术基础。

基于生产数据的混合流水车间动态调度方法研究

在智能制造背景下,物联网等信息技术为制造系统积累了大量数据,同时人工智能等先进方法为车间数据分析和实时控制提供了有效手段。因此,针对不相关并行机混合流水车间调度问题,提出了一种基于生产数据的动态调度方法,以实现订单完工时间最小化。首先以高质量调度方案为基础,从中提取生产特征和调度规则完成样本构建。其次使用Relief F算法过滤冗余生产特征,获得用于训练和预测的调度样本。然后采用融合鲸鱼优化算法的概率神经网络作为调度模型,实现基于调度样本的训练和预测过程。最后,实验结果表明,所提方法具有良好的特征选择能力和较高的预测精度,与其他实时调度方法相比具有更加优越的性能,可以有效地根据车间实时状态指导制造执行过程。