Value stream mapping approach and analytical network process to identify and prioritize production system’s Mudas (case study: natural fibre clothing manufacturing company)

The current research has been done to identify and prioritize the Mudas of the production line of a natural fibre clothing manufacturing company; in this way, value stream mapping has been used to identify the Mudas, then analytical hierarchy method has been used to screen the Mudas. In the first step, necessary information to design value stream of production process has been obtained by observation, measurement and interview; afterward, according to the obtained information and by forming a focus group, Mudas in the production line have been identified and prioritized according to seven categories of Mudas. In order to prioritizing the Mudas by the usage of analytical hierarchy method, the Super Decision software has been applied. Then, according to the obtained priorities, suggested map of the future value system has been drawn and some suggestions have been presented to eliminate Mudas and move towards the lean manufacturing.     

Sustainability assessment of Iranian petrochemical companies in stock exchange: A data envelopment analysis-based approach

The assessment of efficiency is always of particular importance according to different indicators from different perspectives. There are various techniques for evaluating petrochemical companies, among which the data envelopment analysis technique is one of the best techniques that can be used to calculate the relative efficiency of a set of decision-making units with network structures. In the present paper, seven petrochemical companies listed in the Iranian stock exchange were analysed. These companies were evaluated in terms of financial performance and sustainable development, and their relative efficiency was calculated during 2015–2016. According to the obtained results, only Marun Petrochemical Co. was found to be efficient in all areas and years. The results also showed that four companies were efficient in financial terms over the period under study. In the general conclusion regarding the companies' performance, Marun was ranked first, Jam was ranked second, and Zagros was ranked third.     

基于卷积神经网络的葡萄叶片氮含量识别方法

为实现对葡萄叶片氮素含量快速、便捷的识别，在卷积神经网络VGG-16网络结构基础上，将数据增广后的图像按不同梯度划分进行模型训练，通过十折交叉验证法探究最佳的训练集与验证集分配比例，并构建4个不同深度的网络模型进行训练对比，采用全局平均池化代替全连接层约简网络参数量。训练结果表明，氮含量梯度设为0.70%、0.35%和0.175%时，室内简单背景识别准确率分别为85.9%、76.2%和71.1%；晴天室外复杂背景下识别准确率分别为44.6%、35.0%和30.4%。研究结果表明利用VGG-16建立的网络学习模型对葡萄叶片氮含量识别提供了一种新的便捷方法，对农业信息化和智能化技术应用具有一定促进作用。     

Densely connected convolutional network block based autoencoder for panorama map compression

As a novel virtual reality (VR) format, panorama maps are attracting increasing attention, while the compression of panorama images is still a concern. In this paper, a densely connected convolutional network block (dense block) based autoencoder is proposed to compress panorama maps. In the proposed autoencoder, dense blocks are specially designed to reuse feature maps and reduce redundancy of features. Meanwhile, a loss function, which imports a position-dependent weight item for each pixel, is proposed to train and adjust network parameters, in order to make the autoencoder fit to properties of panorama maps. Based on the proposed autoencoder and the weighted loss function, a greedy block-wise training scheme is also designed to avoid gradient vanishing problem and speed up training. During training process, the autoencoder is divided into several sub-nets. After each sub-net is trained separately, the whole network is fine-tuned to achieve the best performance. Experimental results demonstrate that the proposed autoencoder, compared with JPEG, saves up to 79.69 % bit rates, and obtains 7.27dB gain in BD-WS-PSNR or 0.0789 gain in BD-WS-SSIM. The proposed autoencoder also outperforms JPEG 2000, HEVC and VVC in both BD-WS-PSNR and BD-WS-SSIM. Meanwhile, subjective results show that the proposed autoencoder can recover details of panorama images, and reconstruct maps with high visual quality.     

Emissions of VOCs,SVOCs, and mold during the construction process: Contribution to indoor air quality and future occupants’ exposure

Building materials and human activities are important sources of contamination indoors, but little information is available regarding contamination during construction process which could persist during the whole life of buildings. In this study, six construction stages on two construction sites were investigated regarding the emissions of 43 volatile organic compounds (VOCs), 46 semi-volatile organic compounds (SVOCs), and the presence of 4 genera of mold. Results show that the future indoor air quality does not only depend on the emissions of each building product but that it is also closely related to the whole implementation process. Mold spore measurements can reach 1400 CFU/m³, which is particularly high compared with the concentrations usually measured in indoor environments. Relatively low concentrations of VOCs were observed, in relation to the use of low emissive materials. Among SVOCs analyzed, some phthalates, permethrin, and hydrocarbons were found in significant concentrations upon the delivery of building as well as triclosan, suspected to be endocrine disruptor, and yet prohibited in the treatment of materials and construction since 2014. As some regulations exist for VOC emissions, it is necessary to implement them for SVOCs due to their toxicity.     

环形供热管网水力工况设计方法研究

为提高环形供热管网水力工况运行稳定性,提出了基于模糊PID控制的环形供热管网水力工况控制方法。构建环形供热管网水力工况控制的约束参量模型,在此基础上采用回归模型逼近方法构建其测试指标集,结合自适应融合反馈跟踪方法进行环形供热管网水力工况信息的融合处理,并从中提取分布特征量;采用模糊PID控制方法调节提取结果的输出稳定性,实现环形供热管网水力工况优化设计和自适应控制。仿真结果表明,采用该方法进行环形供热管网水力工况控制的稳定性较好,自适应控制能力较强,实现了环形供热管网水力工况优化调节。     

某带钢连续热浸镀机组卧式连续退火炉水冷炉辊的开裂原因

采用宏观和微观形貌观察、化学成分分析、显微组织观察、硬度测试等方法,对某带钢连续热浸镀机组卧式连续退火炉水冷炉辊的开裂原因进行了分析。结果表明:水冷炉辊辊套成分中不含铌元素,镍元素含量偏低,导致组织中形成网状富铬碳化物析出相;辊套内腔结垢、水冷不畅使水冷炉辊产生局部过热,导致工作侧辊套基体中粒状合金碳化物的析出和网状富铬碳化物的长大,使工作侧辊套的脆性增加;随着结垢的沉积,水冷炉辊出现轴承转动不畅,甚至堵转现象;在热应力、扭力作用下,裂纹在网状富铬碳化物析出相中形成并沿网状碳化物逐渐向基体内扩展,最终导致水冷炉辊的开裂。     

建筑产业转型升级新时代下高职建筑工程技术特色专业建设问题的新思考

随着建筑业技术进步和转型升级,高职建筑工程技术专业建设应顺应新时代要求,产教融合,办出特色。本文提出了“四个对接一个融合”的特色专业建设新思考。     

Actuator fault tolerant control using adaptive RBFNN fuzzy sliding mode controller for coaxial octorotor UAV

In this paper, a robust controller for a Six Degrees of Freedom (6 DOF) coaxial octorotor helicopter control is proposed in presence of actuator faults. Radial Base Function Neural Network (RBFNN), Fuzzy Logic Control approach (FLC) and Sliding Mode Control (SMC) technique are used to design a controller, named Fault Tolerant Control (FTC), for each subsystem of the octorotor helicopter. The proposed FTC scheme allows avoiding difficult modeling, attenuating the chattering effect of the SMC, reducing the rules number of the fuzzy controller, and guaranteeing the stability and the robustness of the system. The simulation results show that the proposed FTC can greatly alleviate the chattering effect, good tracking in presence of actuator faults.