六西格玛方法与DMAI方法在铁路制造企业中的应用

Tania Silvani, A. Yanuar, W. Juliani
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Define phase using Supplier – Input – Process – Output – Customer (SIPOC) diagram and Critical to Quality (CTQ). Measure phase using c-Chart to know the process stability, then Cp and Sigma Level to know the process capability. Fishbone diagram and Failure Mode Effect Analysis (FMEA) are used in the analyze phase. The result of FMEA is the base to design improvements in the improve phase, the improvements are material storage characteristics, workstation design and procedure display. Introduction As one of railway manufacturing company in Southeast Asia, quality is an important factor in maintaining customer satisfaction and one of the key success in business competition [1]. Also, this railway manufacturing company has to improve its quality, which is the products that have been produced must be zero defects [2]. The core product of this railway manufacturing company is train. One train consist of two main components, which are bogie and car body. The components that arrange one car body are shown in the Figure 1. One of car body sub assembly, namely underframe (Figure 2), has its problem. The problem is, defective products have been found which cause the underframe to be repair, so the underframe production is delayed. The production data of underframe is shown in Table 1. It can be seen from Table 1 that the type of defect is porosity. The identified defects are located in different connections, which are on the side sill connection and the center sill connection. There are 12 joints that need to be inspected on each connection, so the total is 24 joints. Porosity (Figure 3) comes from the welding process during the assembly of underframe’ components. The components of underframe (Figure 2) are front end, rear end, side sill, center sill, and cross beam. Therefore, this study uses the Six Sigma method with DMAI approach to give improvements on welding process so the defect which is porosity will be reduced or may not exist and to maintain the quality. 1st International Conference on Engineering and Management in Industrial System (ICOEMIS 2019) Copyright © 2019, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). 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引用次数: 0

摘要

作为东南亚地区的铁路制造企业之一,质量是保持客户满意度的重要因素,也是在商业竞争中取得成功的关键之一。在铁路生产中,车体分总成即车底总成在装配过程中存在问题。由于发现了不良品,导致底盘需要修理,导致底盘生产延迟。缺陷的类型是气孔,这是由装配过程中的焊接过程造成的。因此,本研究采用六西格玛方法与定义-测量-分析-改进(DMAI)方法对焊接工艺进行改进,以减少或不存在气孔缺陷,并保持质量。使用供应商-输入-过程-输出-顾客(SIPOC)图和关键质量(CTQ)定义阶段。测量阶段使用c图来了解过程稳定性,然后使用Cp和Sigma水平来了解过程能力。分析阶段采用鱼骨图和失效模式效应分析(FMEA)。在改进阶段,FMEA的结果是设计改进的基础,改进的内容包括材料存储特性、工作站设计和程序显示。作为东南亚地区铁路制造企业之一,质量是保持客户满意度的重要因素,也是商业竞争中取胜的关键因素之一[1]。同时,该铁路制造企业必须提高质量,即生产出来的产品必须是零缺陷的[2]。这家铁路制造公司的核心产品是火车。一列火车主要由转向架和车体两部分组成。排列一个车身的组件如图1所示。车身分总成之一,即底架(图2),有其问题。问题是发现了不良品,导致底盘需要修理,导致底盘生产延迟。底盘生产数据如表1所示。由表1可以看出,缺陷的类型为气孔。所识别的缺陷分布在不同的连接上,分别位于边基连接和中基连接。每个连接处有12个连接处需要检查,所以总共是24个连接处。气孔(图3)来自于底盘组件组装过程中的焊接过程。底盘的组成部分(图2)是前端,后端,侧窗台,中心窗台和横梁。因此,本研究采用六西格玛方法结合DMAI方法对焊接工艺进行改进,以减少或不存在气孔缺陷,并保持质量。第一届工业系统工程与管理国际会议(ICOEMIS 2019)版权所有©2019,作者。亚特兰蒂斯出版社出版。这是一篇基于CC BY-NC许可(http://creativecommons.org/licenses/by-nc/4.0/)的开放获取文章。智能系统研究进展,第171卷
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Six Sigma Method with DMAI Approach in Railway Manufacturing Company
As one of railway manufacturing company in Southeast Asia, quality is an important factor in maintaining customer satisfaction and one of the key success in business competition. During the railway production, there is problem in the assembly process of car body sub assembly, namely underframe. Defective products have been found which cause the underframe to be repair, so the underframe production is delayed. The type of defect is porosity, which results from the welding process during the assembly process. Therefore, this study uses the Six Sigma method with the Define – Measure – Analyze – Improve (DMAI) approach to give improvements on welding process so the defect which is porosity will be reduced or may not exist and to maintain the quality. Define phase using Supplier – Input – Process – Output – Customer (SIPOC) diagram and Critical to Quality (CTQ). Measure phase using c-Chart to know the process stability, then Cp and Sigma Level to know the process capability. Fishbone diagram and Failure Mode Effect Analysis (FMEA) are used in the analyze phase. The result of FMEA is the base to design improvements in the improve phase, the improvements are material storage characteristics, workstation design and procedure display. Introduction As one of railway manufacturing company in Southeast Asia, quality is an important factor in maintaining customer satisfaction and one of the key success in business competition [1]. Also, this railway manufacturing company has to improve its quality, which is the products that have been produced must be zero defects [2]. The core product of this railway manufacturing company is train. One train consist of two main components, which are bogie and car body. The components that arrange one car body are shown in the Figure 1. One of car body sub assembly, namely underframe (Figure 2), has its problem. The problem is, defective products have been found which cause the underframe to be repair, so the underframe production is delayed. The production data of underframe is shown in Table 1. It can be seen from Table 1 that the type of defect is porosity. The identified defects are located in different connections, which are on the side sill connection and the center sill connection. There are 12 joints that need to be inspected on each connection, so the total is 24 joints. Porosity (Figure 3) comes from the welding process during the assembly of underframe’ components. The components of underframe (Figure 2) are front end, rear end, side sill, center sill, and cross beam. Therefore, this study uses the Six Sigma method with DMAI approach to give improvements on welding process so the defect which is porosity will be reduced or may not exist and to maintain the quality. 1st International Conference on Engineering and Management in Industrial System (ICOEMIS 2019) Copyright © 2019, the Authors. Published by Atlantis Press. This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/). Advances in Intelligent Systems Research, volume 171
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