Construction of Automated Manufacturing Systems with Production Management using Grey Theory

利用灰色理论构建生产管理自动化制造系统

• 批准号: 15510142
• 负责人: KITAOKA Masatoshi
• 金额: $ 1.6万
• 依托单位: KANAGAWA UNIVERSITY
• 依托单位国家: 日本
• 项目类别: Grant-in-Aid for Scientific Research (C)
• 财政年份: 2003
• 资助国家: 日本
• 起止时间: 2003 至 2005
• 项目状态: 已结题
• 来源: https://kaken.nii.ac.jp/en/grant/KAKENHI-PROJECT-15510142/
• 关键词: Grey Theory; Neural network; Automated Production Systems; Quality Control; Parts Feeder; Wavelet Transformation; Material Handling; Image Processing; ファジイ・ニューロ; 自動化システム; 信頼性工学; PLC; 人間-機械系; 人体モデル; 生産管理; 流動数曲線; 部品供給システム; 自然言語; シナリオ; Grey Theory; Neural network; Automated Production Systems; Quality Control; Parts Feeder; Wavelet Transformation; Material Handling; Image Processing; ファジイ・ニューロ; 自動化システム; 信頼性工学; PLC; 人間-機械系; 人体モデル; 生産管理; 流動数曲線; 部品供給システム; 自然言語; シナリオ

This paper composed with 6 research items.1)The new debugging operation method is proposed, when the automated production equipment was installed. Here, the theoretical formula of reliability engineering was proposed on the debugging operation, and proposed model formula was verified from the test data 2)The decreasing rate of parts of automated assembly system is caused abnormal conditions with the parts feeder. The abnormal condition of parts feeder is detected based on the ARMA control line. The cause of the abnormal condition is recognized by Fuzzy neural network and Wavelet analysis. 3)For the pattern recognition of work, the method for combining genetic algorithm with Fuzzy ART is proposed. The pyramid image analysis for the template matching by GA. Next, the hierarchical Fuzzy ART is proposed. It does not use learning parameter, vigilance parameter and decreasing parameter. Proposed the algorithm become possible with high-speed image processing. 4)The shipping volume prediction method of the distribution center by the 2 time cumulative data for the gray theory GM(1,1) model is proposed. The method for applying multiple GM(1,1) models in search of the inflection point is shown. 5)The gray theory is applied to the supply chain system, and the parts supplies, information to the consumer from the production, goods, parts delay and flow are verified. Queueing theory is also applied to the model analysis for SCM. 6)The Manual Material Handling (MMH) activities, especially lifting dominate occupationally related low back disorder risk. Using the three-dimensional motion analysis system, the manual asymmetric lifting posture is filmed and analyzed. The operation of the human body, and it displays the working posture by computer graphics is developed. Then, OWAS code is generated with automatically for the MMH posture, and the risk of the worker in MMH would be beforehand estimated

本文由6个研究项目组成。1）安装自动生产设备时提出了新的调试操作方法。在这里，在调试操作上提出了可靠性工程的理论公式，并从测试数据中验证了拟议的模型公式2）自动装配系统部分的零件速率降低是与零件进料器的异常条件。根据ARMA控制线检测到零件馈线的异常状态。异常状况的原因通过模糊神经网络和小波分析确认。 3）为了对工作的模式识别，提出了将遗传算法与模糊艺术相结合的方法。 GA匹配的模板匹配的金字塔图像分析。接下来，提出了分层模糊艺术。它不使用学习参数，警惕参数和降低参数。提出的算法通过高速图像处理成为可能。 4）提出了灰色理论GM（1,1）模型的2个时间累积数据的分配中心的运输量预测方法。显示了应用多个GM（1,1）模型寻找拐点的方法。 5）将灰色理论应用于供应链系统，零件供应，从生产中向消费者提供的信息，商品，零件延迟和流程得到验证。排队理论也适​​用于SCM的模型分析。 6）手动材料处理（MMH）活动，尤其是举重占据了与职业相关的小背疾病风险。使用三维运动分析系统，对手动不对称举重姿势进行了拍摄和分析。开发了人体的操作，并通过计算机图形显示了工作姿势。然后，OWAS代码是为MMH姿势自动生成的，并且将事先估计MMH中的工人的风险