Acceptance of Taguchi's Quality Philosophy and Practice by Lean practitioners in apparel manufacturing

Gamage, P.; Jayamaha, Nihal; Grigg, Nigel P.

doi:10.1080/14783363.2015.1135729

Cited by 13 publications

(10 citation statements)

References 39 publications

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“…Gamage et al (2016) refer to the LM socio-technical system, highlighting its two-fold content. Similarly, Taj (2005) stresses the two important aspects in LM, the human and the non-human.…”

Section: Defining Lmmentioning

confidence: 99%

Research gaps in Lean manufacturing: a systematic literature review

Psomas

Antony²

2019

IJQRM

103

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Purpose Literature contributions to Lean manufacturing (LM) are fragmented and show some significant limitations. The purpose of this paper is to identify the existing research gaps in LM as well as to group them into respective themes. Design/methodology/approach A systematic literature review (SLR) of peer reviewed journal articles in LM was carried out by the authors, based on four major publishers, namely, Emerald Online, Science Direct, Springer Link and Taylor & Francis. In total, 120 articles published in 30 journals during 2005–2016 were collected which revealed LM research gaps. A simple affinity diagram was applied in order to group the research gaps into logical themes. Findings A large number of research gaps are identified in the LM literature and meaningful themes of these gaps are also revealed. Research limitations/implications The SLR carried out by the authors is based on only four academic journal publishers and some of other publishers might have been missed out in this search. Excluding articles focusing on an individual Lean principle or tool/technique is also a limitation of the present SLR. Practical implications Researchers and practitioners can use the LM research gaps presented in this study for further development of LM methodology. Originality/value Presenting LM research gaps analytically and grouping them into meaningful themes, significantly differentiates the present SLR study from those published so far.

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“…Gamage et al (2016) refer to the LM socio-technical system, highlighting its two-fold content. Similarly, Taj (2005) stresses the two important aspects in LM, the human and the non-human.…”

Section: Defining Lmmentioning

confidence: 99%

Research gaps in Lean manufacturing: a systematic literature review

Psomas

Antony²

2019

IJQRM

103

View full text Add to dashboard Cite

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“…Five articles focused on the effect of lean on workers engagement and participation and reported both positive and negative associations. For example, one article presented evidence that organizational support during lean implementation increased job involvement, commitment, awareness and reduced turnover intention (Gamage et al, 2016;Kaur et al, 2016;Wickramasinghe & Wickramasinghe, 2011b). Other articles presented evidence showing that lean practices increased workers commitment and participative decision-making (Wickramasinghe & Wickramasinghe, 2011a, 2017, and reduced absenteeism and labour turnover (Jackson & Mullarkey, 2000;Wickramasinghe & Wickramasinghe, 2011b).…”

Section: Worker Engagement and Participationmentioning

confidence: 99%

The effect of lean on occupational health and safety and productivity in the garment industry – a literature review

Hamja

Maalouf

Hasle

2019

Production & Manufacturing Research

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Introduction: Lean is increasingly used by garment manufacturers to increase productivity for reducing costs and lead time. Yet, it has not been documented in a review whether lean actually improves productivity, and it is an open question whether lean can improve productivity without jeopardizing occupational health and safety (OHS).Objective: This article contributes to this debate by reviewing the present knowledge about the effect of lean on productivity and OHS in the RMG industry. Methodology: A systematic review of the available peer-reviewed studies of lean in RMG and its related effects on productivity and OHS. Results: We identified 18 relevant articles, which showed strong positive effect of lean on productivity and weak positive to mixed effects of lean on OHS. Conclusions: Our results indicate that lean in RMG is likely to improve productivity, but RMG manufacturers need to make careful assessment of the effect of lean on OHS and adjust lean implementation accordingly. ARTICLE HISTORY

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“…This design is selected as it's an efficient tool to maintain accuracy with small data set. 45 The investigated output of the conducted EBW process is the longitudinal residual stress, obtained from two different approaches namely the process parameters and from natural frequency of vibrations.…”

Section: Methodsmentioning

confidence: 99%

“…Moreover, Taguchi L9 design is a well-established technique used to deal with the less number of experimental data without compromising the model performances. 45 …”

Section: Data Setmentioning

confidence: 99%

Prediction of residual stress in electron beam welding of stainless steel from process parameters and natural frequency of vibrations using machine-learning algorithms

Das

Pratihar

et al. 2020

Proceedings of the Institution of Mechanical Engineers, Part C:

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In the present study, machine learning algorithms have been used to predict residual stress during electron beam welding of stainless steel using the information of input process parameters and natural frequency of vibrations. Accelerating voltage, beam current and welding speed have been considered as input process parameters. Both residual stress and natural frequencies of vibration of the weld obtained using each set of the input parameters are measured experimentally. A number of machine learning algorithms, namely M5 algorithm-based Model Trees Regression, Random forest, Support Vector Regression, Reduced Error Pruning Tree, Multi-layer perceptron, Instance-based k-nearest neighbor algorithm, and Locally weighted learning have been used for the said purpose. Support vector regression and Locally weighted learning are found to perform consistently good and bad, respectively. The predicted welding residual stresses have been validated experimentally through X-ray diffraction (XRD) and good agreements are obtained. In addition, statistical tests are conducted, and the estimated reliability values of the employed models are analyzed through Monte-Carlo simulations.

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Acceptance of Taguchi's Quality Philosophy and Practice by Lean practitioners in apparel manufacturing

Cited by 13 publications

References 39 publications

Research gaps in Lean manufacturing: a systematic literature review

Research gaps in Lean manufacturing: a systematic literature review

The effect of lean on occupational health and safety and productivity in the garment industry – a literature review

Prediction of residual stress in electron beam welding of stainless steel from process parameters and natural frequency of vibrations using machine-learning algorithms

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