Variation Modeling of Lean Manufacturing Performance Using Fuzzy Logic Based Quantitative Lean Index

Oleghe, Omogbai; Salonitis, Konstantinos

doi:10.1016/j.procir.2016.01.008

Cited by 32 publications

(20 citation statements)

References 16 publications

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“…Khía cạnh Lean dựa trên TPS Taj 20 Doolen & Hacker 21 Wan & Chen 22 Vimal & Vinodh 23 Wong, Ignatius & Soh 24 Chauhan & Singh 25 Ali & Deif 26 Pakdil & Leonard 27 Oleghe & Salonitis 28…”

Section: Bảng 1: So Sánh Các Phương Pháp/công Cụ đáNh Giá Mức độ Tinhmentioning

confidence: 99%

Leanness assessment: a study on JVN company

Nguyen

Giang

Hao

2020

Sci. Tech. Dev. J. Econ. Law. Manag.

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This study focuses on reviewing, analyzing, comparing lean assessment methods/tools from previous researches, and selecting an appropriate method/tool, and then applying the selected one to evaluate the leanness level in the specific company. Literature review and case study research at JVN-Company are conducted in this study. The result finds that: (a) LAT developed by Pakdil & Leonard (2014) is the effective tool to measure efforts in implementing Lean and identify wastes from Lean perspective within an enterprise; and (b) By applying LAT to assess the leanness level at JVN company, the results show that JVN company has achieved the leanness level at 68,58%; while Customer dimension has the highest LAT score showing that JVN has high customer satisfaction and loyalty. However, the delivery dimension, particularly late delivery, is in special need of improvement in comparison with other dimensions. Accordingly, a few proposals have been recommended for JVN to consider and adopt the appropriate ones to improve its performance. Overall, the results of this study provide helpful references for manufacturing companies in Vietnam to self–assess their leanness comprehensively, thereby developing the proper and effective roadmap for Lean transformation.

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Section: Bảng 1: So Sánh Các Phương Pháp/công Cụ đáNh Giá Mức độ Tinhmentioning

confidence: 99%

Leanness assessment: a study on JVN company

Nguyen

Giang

Hao

2020

Sci. Tech. Dev. J. Econ. Law. Manag.

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“…The new lean transportation management envisions those lean practices that properly fulfill lean principles and objectives, namely, reduced transportation cycle, zero claims and returns, visibility along the SCM, continuous improvement of communication and tracking capabilities of the shipment and also information management system. (Oleghe and Salonitis, 2016) The new lean practices in transportation respond to the new trend of digitization by using advanced technologies from cloud applications to automated activities especially ones that involve shipping and receiving activities. The companies "leanness" is defined by the operational and financial performance, using certain metrics capable to quantify the effectiveness of the new practices introduced.…”

Section: Transportation Lean Practices and Assessment Issuesmentioning

confidence: 99%

The most innovative lean practices deployed in transportation and their effects on the financial and operational performance

Popescu

2020

Proceedings of the International Conference on Business Excellence

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The new lean paradigm defines the necessary management tools and techniques that create more value for the customers using lean resources. By reducing the non-value activities in one hand, and emphasizing on continuous improvement on the other hand, the lean practices implemented open the path for superior level of financial and operational performance. The purpose of this paper is to highlighting the strong correlation between the combination of the TQM, JIT, TMS, TPM and RFID as the most important lean practices employed by the transportation companies surveyed and its financial and operational performance. The correlation between the lean practices deployed within the transportation companies analyzed and their financial or operational performance has been established due to applying the SPSS quantitative methods, factor analysis and linear regression.

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“…In order to reduce the conceptual differences between what is understood as “lean production” and to facilitate the understanding of practitioners and academics, several Asian researchers have developed research through theoretical studies, case studies and surveys to create a single leanness index for manufacturing companies based on fuzzy logic (Singh et al , 2010; Behrouzi and Wong, 2011; Vinodh and Chintha, 2011; Vinodh and Balaji, 2011; Vinodh and Vimal, 2012; Pakdil and Leonard, 2014; Susilawati et al , 2015; Azadeh et al , 2015; Oleghe and Salonitis, 2016; Vidyadhar et al , 2016) and alternative methods (Wan and Chen, 2008; Gibbons and Burgess, 2010; Karim and Arif-Uz-Zaman, 2013). Wan and Chen (2008) proposed a unit-invariant leanness measure with a self-contained benchmark to quantify the leanness level of manufacturing systems using the concept of data envelopment analysis (DEA).…”

Section: Literature Reviewmentioning

confidence: 99%

Knowledge building about performance evaluation in lean production

Staedele

Ensslin

Forcellini

2019

JMTM

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Purpose The purpose of this paper is to focus on the analysis of the characteristics and gaps of a literature fragment from the international scientific publications on performance evaluation in lean production, aiming to generate new knowledge and suggestions for future scientific research. Design/methodology/approach The authors have adopted “ProKnow-C” methodology, a qualitative research approach that is used for literature selection, identification, analysis and reflection on the established characteristics. Findings From a bibliographic portfolio of 67 research works, 91 per cent of the works have individual metrics and 84 per cent have sets of metrics. Evaluating the focus of the performance measurement system, 34 per cent of works measure performance, 43 per cent compare performance and only 18 per cent assist in strategic planning. Evaluating the phases of the PMS life cycle, 87 per cent attend to the design, and 66 per cent attend to the activities of data collection, allow diagnosis, evaluate performance and communicate results. However, only 3 per cent of the studies analysed the use of PMS after its implementation and no research evidenced the review of metrics and objectives based on strategic planning. Research limitations/implications The search formula to capture the bibliographic portfolio (BP) was limited to the following terms: performance measurement, performance evaluation, performance assess*, performance appraisal, management, indicator*, critical factors, best practices, lean production, lean manufacturing and lean system. The BP was determined based on the limitations set by the research authors: articles published in English and Portuguese languages, from 2000 to 2018, in the Engineering Village, Scopus, EBSCO, Web of Science, ProQuest and Science Direct databases, which were freely available on the internet. Lastly, conceptual knowledge was used to select the articles, so there is a chance that unintentional losses could happen. Practical implications As practical implications for practitioners, the authors have identified that a PMS from an organisation that aims to become “lean” needs to be defined and revised considering its strategy, adjusting its set of metrics and targets to the internal and external challenges. As practical implications for researchers, opportunities have been identified to develop longitudinal studies in PMS utilisation and review to understand how the measurement system must evolve over time through changes in the internal and external environments of organisations. Originality/value This research adds value because its results allow researchers and practitioners to visualise the boundaries of the knowledge from the BP, about performance management in lean production, and what their gaps are in relation to the reference model of performance evaluation. This research is original because it was not observed in the literature review, a research that used the ProKnow-C methodology for analysis of the alignment and gaps between lean production and performance evaluation.

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Variation Modeling of Lean Manufacturing Performance Using Fuzzy Logic Based Quantitative Lean Index

Cited by 32 publications

References 16 publications

Leanness assessment: a study on JVN company

Leanness assessment: a study on JVN company

The most innovative lean practices deployed in transportation and their effects on the financial and operational performance

Knowledge building about performance evaluation in lean production

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