柴油机质量信息追溯管控系统研究

发布时间：2019-03-16 13:40

【摘要】：质量作为现代企业竞争的核心点之一,已经被越来越多的企业所重视。只有保证产品质量,才能保证企业长久不衰。作为传统制造业的典型产品,柴油机在诸多领域都有着举足轻重的地位。随着交通运输业的蓬勃发展,柴油机的质量安全也在社会中受到了广泛的关注。柴油机生产过程中一直存在着数据管理困难,数据失真以及质量信息难追溯等问题,这些问题都制约着柴油机的质量管理水平。如何解决上述问题,是本文接下来的分析的重点。本文基于质量管理与质量追溯相关理论与方法,结合柴油机生产的实际情况建立质量追溯模型,并将物联网的关键技术,应用到柴油机质量信息采集方案中,建立柴油机质量信息追溯管控系统。首先,本文介绍了质量追溯的相关方法与理论,并借助文献了解质量追溯、物联网的国内外研究现状,提出现阶段国内外质量追溯研究存在的不足,在此基础上提出了本文的论文结构、整体的写作思路。其次,针对柴油机生产过程中的质量管理状况,分析在质量管理过程中各部门的相关工作与业务流程,分析质量管理过程中存在的问题,并围绕这些问题提出解决方案,依据质量追溯相关理论、批次管理方法建立质量追溯模型,用以指导柴油机质量信息追溯管控系统的构建。再次,结合物联网关键技术,对柴油机关键件生产过程进行工艺流程分析,设置关键工序以及质量控制点,并使用RFID电子标签技术设计实物标识方案。对于使用传感器进行质量信息采集方式的情形,通过设计基于无线传感网的信息采集方案,结合ZigBee无线技术,实现质量信息采集与控制的自动化,并通过基于无线传感网的温度采集与控制实验验证方案的可行性。最后,结合质量追溯模型,围绕柴油机质量管理需求完成质量信息追溯管控系统的功能设计。通过UML系统建模的方法验证其功能完整性,并根据企业实际应用进行效果验收说明,实现质量信息数字化管理,有效的解决数据管理困难,数据失真,质量问题难追溯等问题。
[Abstract]:As one of the core points of modern enterprise competition, quality has been paid more and more attention by more and more enterprises. Only to ensure the quality of products, can ensure that the enterprise for a long time. As a typical product of traditional manufacturing, diesel engine plays an important role in many fields. With the vigorous development of transportation, the quality and safety of diesel engine has been paid more and more attention in the society. There are many problems in diesel engine production, such as the difficulty of data management, the distortion of data and the difficulty of traceability of quality information. These problems restrict the quality management level of diesel engine. How to solve the above problems is the focus of the next analysis in this paper. Based on the theory and method of quality management and quality traceability, this paper establishes a model of quality traceability based on the actual situation of diesel engine production, and applies the key technology of Internet of things to the quality information acquisition scheme of diesel engine. Establish the diesel engine quality information traceability control system. First of all, this paper introduces the relevant methods and theories of quality traceability, and with the help of literature to understand the quality traceability, Internet of things at home and abroad research status, put forward the current domestic and foreign quality traceability research shortcomings, On this basis, this paper puts forward the structure of the paper, the overall thinking of writing. Secondly, aiming at the situation of quality management in diesel engine production process, this paper analyzes the related work and business process of each department in the process of quality management, analyzes the problems existing in the process of quality management, and puts forward solutions to these problems. According to the quality traceability theory, the batch management method is used to establish the quality traceability model to guide the construction of diesel engine quality information traceability control system. Thirdly, the key technology of coupling networking is used to analyze the process flow of diesel engine key parts production process, set up key processes and quality control points, and use RFID electronic label technology to design the physical identification scheme. In the case of using the sensor to collect the quality information, through the design of the information collection scheme based on the wireless sensor network and the combination of ZigBee wireless technology, the automation of the quality information collection and control can be realized. The feasibility of the scheme is verified by the temperature acquisition and control experiment based on wireless sensor network. Finally, combined with the quality traceability model, the function design of the quality information traceability control system is completed based on the diesel engine quality management requirements. Through the UML system modeling method to verify its functional integrity, and according to the actual application of the enterprise to verify the effect of acceptance instructions, quality information digital management, effective solutions to the difficulties of data management, data distortion, quality problems are difficult to trace back.
【学位授予单位】：大连理工大学
【学位级别】：硕士
【学位授予年份】：2016
【分类号】：TK42

【参考文献】