Reducing Welding Defects in Turnaround Projects: A Lean Six Sigma Case Study

Anderson, Nicole C.; Kovach, Jamison V.

doi:10.1080/08982112.2013.801492

Cited by 51 publications

(30 citation statements)

References 30 publications

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“…monitoring and institutionalizing the improvement actions taken (see Section 4.5). Anderson and Kovach (2014) and Vinodh, Kumar, and Vimal (2014) applied the DMAIC approach and integrated the Lean Six Sigma methodology throughout the waste reduction project and observed significant improvements in terms of operational performance and lower failure rate which translates into positive sustainability impacts in general. The methodology used in this case study integrated the LM tools specifically the Sus-VSM to illustrate the value stream mapping for all the processes, activities, values and information throughout the process and to identify the potential areas for improvement and opportunities for waste reduction.…”

Section: Methodology: Proposed Dmaic-based Approach To Sus-vsmmentioning

confidence: 99%

DMAIC-based approach to sustainable value stream mapping: towards a sustainable manufacturing system

Jamil

Gholami

Saman

et al. 2020

Economic Research-Ekonomska Istraživanja

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The research for this article was built upon the discussion concerning sustainable value stream mapping (Sus-VSM), which had recently emerged towards advancing sustainable manufacturing systems. Research on this sustainable-oriented lean tool has been confined to only a handful of studies only. Specifically, the lack of a continuous improvement process, where subsequent value stream developmental maps can be established to continue the cycle, is highlighted as a notable shortfall of this application. To fill the gap, this paper proposes a methodological approach, based on the DMAIC improvement cycle, to systematically implement and conduct Sus-VSM studies. The proposed methodology is practically validated with an industrial case to support this narrow body of knowledge. The research findings revealed that a DMAIC-based approach can be effectively applied to systematize the Sus-VSM towards sustainable manufacturing. The paper also provides a guiding reference for operations managers who wish to undertake similar improvement projects and make their manufacturing operations more sustainable, and, hopefully, inspire other researchers and practitioners to broaden the study of this under-researched field, which is now receiving growing interest in various industries.

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Section: Methodology: Proposed Dmaic-based Approach To Sus-vsmmentioning

confidence: 99%

DMAIC-based approach to sustainable value stream mapping: towards a sustainable manufacturing system

Jamil

Gholami

Saman

et al. 2020

Economic Research-Ekonomska Istraživanja

View full text Add to dashboard Cite

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“…They can help manufacturers evaluate the process quality of their production processes and serve as an effective and convenient means of communication between internal engineers [11][12][13]. Six Sigma, developed in 1986 by Motorola, is widely applied to enhance product quality levels in the manufacturing industry [5,[14][15][16]. Several studies have investigated the correlations between PCIs and Six Sigma quality levels [9][10]17].…”

Section: Fig 1: Ic Packaging Flow Chartmentioning

confidence: 99%

Process-Quality Evaluation for Wire Bonding With Multiple Gold Wires

Lai

Chen

et al. 2020

IEEE Access

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Taiwan is a world-leader in wafer foundry services and IC packaging and testing. Wire bonding is a crucial process in the overall IC-packaging industry chain. Thus, this paper proposes a processquality evaluation model for wire bonding with multiple gold wires. We chose process quality indices as a tool of evaluation fully mirroring process yield and quality levels. These indices contain unknown parameters and thus require sample data to estimate. We first derived the uniformly minimum variance unbiased estimator of the indices and calculated the upper confidence limits of the indices based on DeMorgan's theorem and Boole's inequality. The upper confidence limits of the indices were then employed to create a confidence interval-based fuzzy membership function, in order to improve the accuracy of estimation as well as solve the problem of uncertainty of the measured data. Next, we obtained the fuzzy critical value and used index estimates and the fuzzy critical value to establish fuzzy test rules. Next, we marked the fuzzy critical value on the axes of a radar chart, which is a visualization evaluation tool, and connected neighboring critical points to create a critical region in the form of a regular polygon. The observed values of the indices were then marked on the axes to produce a visualized fuzzy radar evaluation chart. This fuzzy radar evaluation chart has a solid foundation in statistical inference, and evaluation rules were established using precise fuzzy test methods. Not only is this fuzzy radar evaluation chart easy to use, but it also reduces the chance of misinterpretations made by sampling errors, so that the accuracy of evaluation can be enhanced. INDEX TERMS process quality index, fuzzy critical value, critical region, wire bonding, radar chart.

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“…Many of the nominal-the-best quality characteristics (QCs) of important machine tool components, such as the inner or outer diameters of shafts, bearings, and gears, have asymmetric tolerances [6][7][8][9]. A process capability index (PCI) is not only a convenient tool for process capability assessment and analysis but also an effective tool for communication between sales departments and customers [10][11][12][13][14][15][16]. A process has a symmetric tolerance when the target value, T, equals the tolerance midpoint, M, where M = (USL + LSL)/2, and USL and LSL are the upper and lower specification limits, respectively.…”

Section: Introductionmentioning

confidence: 99%

Statistical Hypothesis Testing for Asymmetric Tolerance Index

Chen

Hsu

et al. 2021

Applied Sciences

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Many of the nominal-the-best quality characteristics of important machine tool components, such as inner or outer diameters, have asymmetric tolerances. An asymmetric tolerance index is a function for the average of the process and the standard deviation. Unfortunately, it is difficult to obtain the 100(1−α)% confidence interval of the index. Therefore, this study adopts Boole’s inequality and DeMorgan’s theorem to find the combined confidence region for the average of the process as well as the standard deviation. Next, using the asymmetric tolerance index for the target function and the combined confidence region for the feasible region, this study applies mathematical programming to find the confidence interval as well as employs this confidence interval for statistical hypothesis testing. Lastly, this study demonstrates the applicability of the proposed approach with an illustrative example.

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Reducing Welding Defects in Turnaround Projects: A Lean Six Sigma Case Study

Cited by 51 publications

References 30 publications

DMAIC-based approach to sustainable value stream mapping: towards a sustainable manufacturing system

DMAIC-based approach to sustainable value stream mapping: towards a sustainable manufacturing system

Process-Quality Evaluation for Wire Bonding With Multiple Gold Wires

Statistical Hypothesis Testing for Asymmetric Tolerance Index

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