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| 1 | Economic integration of design optimization 显示文摘 | Young Jin Kim Byung Rae Cho | 2000 | Quality Engineering2000，12，4： | 1 |
| 2 | Economic integration of design optimization显示文摘 | YOUNG JIN KIM BYUNG RAE CHO | 2000 | Quality Engineering2000，12，4： | 1 |
| 3 | Project selection and its impact on the successful deployment of Six Sigma显示文摘 | Maneesh Kumar Jiju Antony Byung Rae Cho | 2009 | Business Process Management2009，5，15： | 1 |
| 4 | Designing the Optimal Process Target Levels for Multiple Quality Characteristics显示文摘 | Teeravaraprug Jirarat Cho Byung Rae | 2002 | International Journal of Production Research2002，40，1： | 1 |
| 5 | Robust design modeling with correlated quality characteristics using a multicriteria decision framework显示文摘 | Srikrishna Madhumohan Govindaluri Byung Rae Cho | 2007 | The International Journal of Advanced Manufacturing Technology2007，，5： | 1 |
| 6 | Economic integration of design optimization显示文摘 | Young Jin Kim Byung Rae Cho | 2000 | Quality Engineering2000，12，4： | 1 |
| 7 | DESIGNING THE OPTIMUM CONFIGURATIONS OF CIRCULAR AND SPHERICAL PRODUCT SPECIFICATIONS FOR MULTIPLE QUALITY CHARACTERISTICS显示文摘As an integral part of tolerance design in the context of design for six sigma, determining optimal product specifications has become the focus of increased activity, as manufacturing industries strive to increase productivity and improve the quality of their products. Although a number of research papers have been reported in the research community, there is room for improvement. Most existing research papers consider determining optimal specification limits for a single quality characteristic. In this paper, we develop the modeling and optimization procedures for optimum circular and spherical configurations by considering multiple quality characteristics. The concepts of multivariate quality loss function and truncated distribution are incorporated. This has never been adequately addressed, nor has been appropriately applied in industry. A numerical example is shown and comparison studies are made. | Byung Rae CHO Michael D. PHILLIPS Jami KOVACH | 2005 | Journal of Systems Science and Systems Engineering2005，14，4： | 1 |
| 8 | DEVELOPMENT OF REALISTIC QUALITY LOSS FUNCTIONS FOR INDUSTRIAL APPLICATIONS显示文摘A number of quality loss functions, most recently the Taguchi loss function, have been developed to quantify the loss due to the deviation of product performance from the desired target value. All these loss functions assume the same loss at the specified specification limits. In many real life industrial applications, however, the losses at the two different specifications limits are often not the same. Further, current loss functions assume a product should be reworked or scrapped if product performance falls outside the specification limits. It is a common practice in many industries to replace a defective item rather than spending resources to repair it, especially if considerable amount of time is required. To rectify these two potential problems, this paper proposes more realistic quality loss functions for proper applications to real-world industrial problems. This paper also carries out a comparison studies of all the loss functions it considers. | Abdul-Baasit SHAIBU Byung Rae CHO | 2006 | Journal of Systems Science and Systems Engineering2006，15，4： | 0 |
| 9 | A MARKOVIAN APPROACH TO DETERMINING PROCESS MEANS WITH DUAL QUALITY CHARACTERISTICS显示文摘这篇论文学习产品连续地被生产的一个生产系统;其说明限制为屏蔽检查被指定。在这篇论文,我们考虑双优秀特征;与在一个更低的说明下面掉落的每个优秀特征联系的不同费用限制一个上面的说明限制的以上。由于这些不同费用,期望的全部的利润将极大地取决于过程参数,一个特别过程平均数。这篇论文为在一个单个阶段的系统与双优秀特征的考虑决定最佳进程工具开发一个基于 Markovian 的模型。建议模型然后通过一个数字例子被说明;敏感分析被执行验证模型。结果证明最佳为两个优秀特征处理平均数在系统的性能上有重要效果。自从处理多质量特征是极其有限的文学调查表演,建议模型,结合了 Markovian 途径,提供唯一的贡献给这个领域。 | Mohammad T.KHASAWNEH Shannon R.BOWLING Byung Rae CHO | 2008 | Journal of Systems Science and Systems Engineering2008，17，1： | 0 |
| 10 | ROBUST DESIGN MODELS FOR CUSTOMER-SPECIFIED BOUNDS ON PROCESS PARAMETERS显示文摘Robust design (RD) has received much attention from researchers and practitioners for years, and a number of methodologies have been studied in the research community. The majority of existing RD models focus on the minimum variability with a zero bias. However, it is often the case that the customer may specify upper bounds on one of the two process parameters (i.e., the process mean and variance). In this situation, the existing RD models may not work efficiently in incorporating the customer’s needs. To this end, we propose two simple RD models using the ε?constraint feasible region method - one with an upper bound of process bias specified and the other with an upper bound on process variability specified. We then conduct a case study to analyze the effects of upper bounds on each of the process parameters in terms of optimal operating conditions and mean squared error. | Sangmun SHIN Byung Rae CHO | 2006 | Journal of Systems Science and Systems Engineering2006，15，1： | 0 |
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