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论文编号：	13932
作者编号：	2320200742
上传时间：	2023/6/6 17:04:24
中文题目：	A公司基于物联网数据的设备综合效率提升研究
英文题目：	Research On Overall Equipment Effectiveness Improve Of A Company Based On IOT Data
指导老师：	林润辉
中文关键字：	设备综合效率；物联网；全员生产维护
英文关键字：	Overall Equipment Effectiveness; Internet of Things; Total Productive Maintenance
中文摘要：	在当前新冠疫情常态化防控措施优化的大背景下，中国制造业迎来一次业务爆发，很多企业订单量暴涨，部分品类产品甚至供不应求。与此同时，市场需求变化加快，市场波动性更强，由于需求的不确定性，企业的投资偏向保守，不敢盲目扩大产能，与旺盛的市场需求形成矛盾。因此很多企业提出数字化转型的战略，以客户为中心结合数字化手段实现流程再造和管理提升，先进的技术如物联网、5G、设备预测性维护等技术被引入制造业。老工厂和新技术的结合，产生了大量新的数据，这些数据如何管理和应用，可以用在企业的哪些领域成了新的研究问题，也是企业数字化转型过程中不得不回答的问题。 在提高制造业生产效率方面，全员生产维护和精益生产体系多年前已完成导入，但是用于衡量企业自身效率水平的指标如设备综合效率数据来源不统一、不准确、不及时，获取成本高、不利于统计、计算和损失分析，以至于企业难以找到指标表现不佳背后的原因并提出针对性的有效解决措施。而基于物联网技术的数据采集正好可以弥补手工管理填报不准确、管理颗粒度不细、数据填报不及时的问题。 论文首先介绍了设备综合效率、物联网等相关技术和理论，其次，结合A公司的实际情况，选择汽车轮毂轴承生产过程中的分选、合套装配过程设备产线作为研究对象，以专题项目的形式开展研究，使用物联网技术收集设备数据并自动计算得出设备综合效率结果，从时间开动率、性能开动率、质量合格率三个方面进行分析。针对分析结果，提出适合离散制造企业可复用的基于物联网数据采集的设备综合效率分析采集、计算和分析方法，为制造企业设备数字化转型提供典型应用场景参考，使设备绩效管理和数字化转型相关技术结合起来，让数字化价值落地。
英文摘要：	Under the background of the current optimization of normalized prevention and control measures for the COVID-19, China's manufacturing industry ushered in a business outbreak, with orders from many enterprises soaring, and some categories of products even in short supply. At the same time, the change of market demand is accelerating, the market volatility is stronger, due to the uncertainty of demand, the investment of enterprises is conservative, dare not blindly expand production capacity, and the strong market demand forms a contradiction. Therefore, many enterprises have proposed digital transformation strategies, customer-centric combined with digital means to achieve process reengineering and management improvement, advanced technologies such as the Internet of Things, 5G, equipment predictive maintenance and other technologies have been introduced into the manufacturing industry. The combination of old factories and new technologies has generated a large amount of new Data, and how these Data are managed and applied, and in which areas of the enterprise can be used has become a new research question, and it is also a question that must be answered in the process of digital transformation of enterprises. In terms of improving the Overall Equipment Effectiveness of the manufacturing industry, the full production maintenance and lean production system has been introduced many years ago, but the indicators used to measure the effectiveness level of the enterprise itself, such as the comprehensive effectiveness of the equipment Data source is not uniform, inaccurate, not timely, the acquisition cost is high, not conducive to statistics, calculation and loss analysis, so that it is difficult for enterprises to find the reasons behind the poor performance of the indicators and propose targeted solutions. Data collection based on Internet of Things technology can make up for the problems of inaccurate manual management filling, coarse management granularity, and untimely data filling. Firstly, the thesis introduces the Overall Equipment Effectiveness, Internet of Things and other related technologies and theories, and secondly, combined with the actual situation of A Company, the most critical quenching, sorting, and fitting assembly process equipment production line in the production process of automobile wheel bearings is selected as the research object, and the research is carried out in the form of a special project, using the Internet of Things technology to collect equipment data and automatically calculate the comprehensive effectiveness results of equipment, and analyze it from three aspects: time operation rate, performance operation rate and quality qualification rate. According to the analysis results, a reusable comprehensive effectiveness analysis and collection, calculation and analysis method based on IoT data collection suitable for discrete manufacturing enterprises is proposed, which provides a reference for typical application scenarios for the digital transformation of equipment in manufacturing enterprises, and combines equipment performance management and digital transformation related technologies and realizes the value of digitization.
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