六西格玛管理在电源模块测试中的应用研究

六西格玛管理是一种新兴的管理思路和工具,核心思想是通过持续改进达到零缺陷,帮助企业保持改进,使企业在激烈的竞争中拥有持续的竞争力和发展动力。六西格玛管理将成为企业未来管理的趋势。文章介绍了六西格玛管理的基本含义和方法,针对研制过程中电源模块测试存在的问题,利用六西格玛管理的DMAIC模型,改进了电源模块的测试方法,提高了测试效率和质量,达到了预期目标。     

Future‐Proofing Six Sigma

Six Sigma started some three decades ago as a problem solving framework for quality improvement. It has since evolved, while being implemented in industry, into a management approach to performance excellence. Whether Six Sigma will continue to enjoy the attention it has been getting and keep embraced by practitioners depends on whether its implementation continues to be in line with new organizational needs in the twenty‐first century. This paper considers what it would take for Six Sigma to face the future world and analyzes from both strategic and operational directions a number of maneuvers necessary to sustain its relevance. Various inclusive and proactive features are explained for remaking of a Six Sigma that is to remain in demand for many years to come. Copyright © 2013 John Wiley & Sons, Ltd.     

Six Sigma-based approach to optimise the diffusion process of crystalline silicon solar cell manufacturing

Silicon-based photovoltaics (PV) plays the dominant role in the history of PV due to the continuous process and technology improvement in silicon solar cells and its manufacturing flow. In general, silicon solar cell process uses either p-type- or n-type-doped silicon as the starting material. Currently, most of the PV industries use p-type, boron-doped silicon wafer as the starting material. In this work too, the boron-doped wafers were considered as the starting material to create pn junction and phosphorus was used as n-type doping material. Industries use either phosphorous oxy chloride (POCl₃) or ortho phosphoric acid (H₃PO₄) as the precursor for doping phosphorous. While the industries use POCl₃ as the precursor, the throughput is lesser than that of the industries’ use of H₃PO₄ due to the manufacturing limitations of the POCl₃-based equipments. Hence, in order to achieve the operational excellence in POCl₃-based equipments, business strategies such as the Six Sigma methodology have to be adapted. This paper describes the application of Six Sigma Define–Measure–Analyze–Improve–Control methodology for throughput improvement of the phosphorus doping process. The optimised recipe has been implemented in the production and it is running successfully. As a result of this project, an effective gain of 0.9 MW was reported per annum.     

6σ方法在动臂焊接质量改进中的应用

针对某重工企业出现的动臂焊接缺陷率高的问题,运用6σ方法的DMAIC模型进行改进,并借助数理统计软件Minitab,经过正交试验设计法,确定焊接最佳参数组合,提出了一套具体的质量改进方案。结果表明,通过实施6σ方法提高了动臂焊接的过程能力、降低了动臂焊接缺陷率、提高了顾客满意度。     

6sigma在CMMI中的应用

在CMMI的实施过程中，定量管理是一个难题。6sigma是基于数据的决策方法，强调用数据说话，量化是6sigma的基础，量化的指标客观地反映现状。通过介绍6sigma的DMAIC模型及其与CMMI关系，阐述在高成熟度组织中如何运用6sigma的思想、方法和工具更有效地实施CMMI。     

精益六西格玛项目管理模式研究及系统开发

实施精益六西格玛项目比单纯实施精益改进项目或六西格玛项目更复杂,目前还缺乏一套有效的管理方法.为此,在明确精益六西格玛项目管理的内涵基础上,通过对精益六西格玛项目实施流程(DMAICⅡ)的分析,建立了精益六西格玛项目管理的一般模式,并开发了该管理模式下的原型系统,为现代企业实施精益六西格玛项目提供了一套新的解决方案,有...     

The practices of integrating manufacturing execution system and six sigma methodology

Currently, manufacturing execution systems (MES) are widely used in the aerospace, automotive, semiconductor, optoelectronic, pharmaceutical and petrochemical industries, etc. MES can link with automation equipment to record relevant information automatically and control the quality of work-in-process (WIP), statistics analysis, production scheduling and maintenance of equipment and instruments, etc. In recent years the manufacturing industry has successfully applied six sigma projects. However, some of the projects failed due to insufficient data and human errors. This paper aims to discuss the define-measure-analyse-improve-control (DMAIC) phases of integrating MES and six sigma, detailing phases to improve the above situation and to avoid the time and cost for sourcing data. It will improve the process performance and capability, cycle time, rolled throughout yield and operating costs significantly, which in turn improve the quality of implementing six sigma quickly and precisely.     

The practices of integrating manufacturing execution systems and Six Sigma methodology

Currently, manufacturing execution systems (MESs) are widely used in the aerospace, automotive, semiconductor, optoelectronic, pharmaceutical and petrochemical industries, as well as other sectors. An MES can link with automation equipment to record relevant information automatically and control the quality of work in process (WIP), statistics analysis, production scheduling and the maintenance of equipment and instruments, etc. In recent years, the manufacturing industry has successfully applied the Six Sigma methodology to projects. However, due to insufficient data or a misunderstanding of the Six Sigma methodology, some of the projects failed. This paper aims to discuss the define, measure, analyse, improve, control (DMAIC) phases of integrating an MES with Six Sigma methodology, detailing the phases to improve the above situation and to avoid the extra time and cost of sourcing data. It will improve the process performance and capability, cycle time, rolled throughput yield and operating costs significantly, which, in turn, improves the quality of implementing the Six Sigma methodology quickly and precisely.     

Statistical Control of a Six Sigma Process

Six Sigma as a methodology for quality improvement is often presented and deployed in terms of the dpmo metric, i.e., defects per million opportunities. As the sigma level of a process improves beyond three, practical interpretation problems could arise when conventional Shewhart control charts are applied during the Control phase of the define-measure-analyze-improve-control framework. In this article, some alternative techniques are described for the monitoring and control of a process that has been successfully improved; the techniques are particularly useful to Six Sigma Black Belts in dealing with high-quality processes. The approach used would thus ensure a smooth transition from a low-sigma process management to maintenance of a high-sigma performance in the closing phase of a Six Sigma project.     

A “Six Sigma”© Case Study: G.E.P. Box's Paper Helicopter Experiment—Part B

This article presents an application of the “Six Sigma” DMAIC model to G.E.P. Box's famous “paper helicopter” experiment. The Improve and Control Phases are presented here. The Define, Measure, and Analyze Phases were presented in an earlier paper. The intent of this article is to present the reader with a case study for structuring a “Six Sigma” project.