Assessment approach to stage of lean transformation cycle based on fuzzy nearness degree and TOPSIS

Liu, Chaochao; Niu, Zhanwen; Chang, Pei‐Chann; Zhang, Bo

doi:10.1080/00207543.2017.1355124

Cited by 17 publications

(12 citation statements)

References 32 publications

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“…The TOPSIS method is used for decision-making and as an evaluation tool to assess and rank alternatives [40]. It is a multiple-criteria decision-making technique for ranking preferences through similarity to find the best solution among a limited set of alternatives.…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation Based-MCDM Approach for Evaluating Traffic Solutions

MAGHABLEH

Mumani

2022

Promet

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Traffic congestion problems have dramatically esca-lated with the increasing volume of vehicles, pedestrians, and cyclists in the face of limited road capacity. This re-search aims to reduce the time road users spend in the system (school-zone area) and improve the efficiency of the process of dropping off and collecting children from a crowded school area. The study integrates discrete-event simulation (DES) and multi-criterion decision-mak-ing (MCDM) techniques to comprehensively evaluate the proposed alternatives to select an optimal solution based on many performance measures. A real-world case study of the traffic and congestion problems experienced by parents when they drop off and fetch their children from school during peak hours is presented. A heuristic algorithm was developed to simulate the random and un-predictable behaviour of road users. A cost-benefit anal-ysis considered the impact of waiting time, traffic den-sity, number of accidents, additional fuel expenses, and emission reduction. The technique for order of preference by similarity to ideal solution (TOPSIS) and preference selection index (PSI) methods were utilised to select the most appropriate option for parents. The study found that the integration of simulation techniques with MCDM methods could efficiently solve traffic problems.

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Section: Literature Reviewmentioning

confidence: 99%

Simulation Based-MCDM Approach for Evaluating Traffic Solutions

MAGHABLEH

Mumani

2022

Promet

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“…Through the literature reviewed many studies have examined leanness either on manufacturing or no-manufacturing sectors. According to Liu et al, (2017) three main types of lean assessment exist. The first type focuses on lean practices as a lean assessment metrics such as: TPM, JIT, VSM, and 5S.…”

Section: Leanness Assessmentmentioning

confidence: 99%

Product-service system leanness assessment model: study of a UK manufacturing company

Elnadi

Shehab

2021

IJLSS

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Purpose Numerous leanness assessment models were developed for both manufacturing and service sectors. However, little research effort was made to provide an instrument that can be used to measure the leanness level of the product-service system (PSS). This paper aims to propose an index to assess the leanness of PSS in a UK manufacturing company. Design/methodology/approach The development of the assessment model was carried out through an iterative process. Commencing from existing literature on lean manufacturing assessment and lean service assessment, the initial model for assessing PSS leanness was developed. This initial model was refined via two consecutive phases. The first one includes semi-structured interviews with academic researchers involved in lean projects where their comments were considered. In the second phase, semi-structured interviews with several experts working in different UK manufacturing industries and involved in lean and continuous improvement projects were conducted to reach the final assessment model. After developing the model, the next step was identifying a suitable company for applying the model. The case company was selected because of its commitment to implement lean practices and its ability to participate in this study. After that, data was collected from the case company and the PSS leanness index was calculated using a multi-grade fuzzy approach. Finally, areas for further improvement were identified and the results obtained were validated. Findings The PSS leanness index computed for the case company indicates that the service offering process provided by the company is generally lean. Areas for further improvement were identified. Research limitations/implications This study focussed on a single case company and is based on the experts’ opinions; this may tend to be biased. However, future studies will be performed to multiple-case studies to enhance findings and more empirical research will be conducted to catch more insights into PSS leanness. Practical implications This paper provides guidelines to manufacturing companies’ managers for measuring the PSS leanness index and planning for the future. This index gives information regarding the degree of lean adoption in the service offering process and identifying the gap between the current PSS leanness level and the desired state. Originality/value The proposed model has been developed by the opinion of academicians and industry experts. The proposed model can provide guidelines and directions for managers for PSS leanness assessment.

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“…Narayanamurthy and Gurumurthy (2016) used graph-theoretic approach for assessing systemic leanness. Liu et al (2017) developed an assessment tool to measure the stage of lean transformation using the enterprise transformation characteristics from the enterprise level. This model was based on fuzzy nearness degree and TOPSIS approach.…”

Section: Literature Reviewmentioning

confidence: 99%

Development of leanness index for SMEs

Yadav

Khandelwal

Jain

et al. 2019

IJLSS

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Purpose This paper aims to discuss the concept of leanness and provide an effective assessment tool for measuring leanness of small and medium enterprises (SMEs). Design/methodology/approach A hybrid interpretive structural modelling–analytical network process (ISM-ANP) approach is used to develop leanness index for SMEs. The parameters for leanness are extracted from the literature survey, and the inter-relationships among them are identified through ISM approach. Further, the ANP tool is used to derive the weights of the parameters, and the leanness index is developed for SMEs. Findings A leanness assessment model is developed, which considers the interdependencies among leanness parameters. Continuous improvement, Just in Time and active management participation, respectively, get first, second and third ranks for leanness measurement in SMEs. Research limitations/implications This study is based on the expert’s opinion, and it may tend to be biased. However, future study will be performed as empirical research to catch more explicit concept and more insights of leanness in context of SME sector. Practical implications This paper provides guidelines to the managers of SMEs for measuring the leanness index and planning for future. This leanness index gives information regarding the degree of lean adoption in the organization. Originality/value The proposed model has been developed by the expert opinion of academicians and practitioners. The proposed model can provide guidelines and directions for managers for leanness assessment in SME context.

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Assessment approach to stage of lean transformation cycle based on fuzzy nearness degree and TOPSIS

Cited by 17 publications

References 32 publications

Simulation Based-MCDM Approach for Evaluating Traffic Solutions

Simulation Based-MCDM Approach for Evaluating Traffic Solutions

Product-service system leanness assessment model: study of a UK manufacturing company

Development of leanness index for SMEs

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