Assessment of Lean Six Sigma Readiness (LESIRE) for manufacturing industries using fuzzy logic

Raja Sreedharan V., R. Raju, Vijaya Sunder M., Jiju Antony

Research output: Contribution to journalArticle

Abstract

Purpose: Many organizations have reported significant benefits after the implementation of Lean Six Sigma (LSS). Embracing LSS requires asking some important questions: How Lean Six Sigma Readiness (LESIRE) can be measured? How can an organization identify the barriers for LESIRE? Answers to these questions are critical to both academicians and practitioners. The paper aims to discuss this issue. Design/methodology/approach: This study illustrates the development process of a Lean Six Sigma Readiness (LESIRE) evaluation model to assess an organization’s readiness for LSS deployment using the fuzzy approach. The model was developed from 4 enablers, 16 criteria and 46 attributes of LSS, identified through a literature review. Findings: To demonstrate the efficiency of the model, this study testing the LESIRE evaluation model in three Indian SMEs. Using experts’ ratings and weight, the researchers calculated the Fuzzy Lean Six Sigma index (FLSS) which indicates the LESIRE level of an organization and the Fuzzy Performance Importance Index (FPII) that helps to identify the barriers for LESIRE. Research limitations/implications: The main limitations of this study are that it did not consider the failure factors of LSS for model development and the LESIRE was only tested in manufacturing industries. Thus, future researchers could focus on developing a model with failure factors. The results obtained from the SMEs show that LESIRE is capable of assessing LESIRE in an industrial scenario and helps practitioners to measure LESIRE for the future decision making process. Practical implications: The LESIRE model is easy to understand and use without much computation complexity. This simplicity makes the LESIRE evaluation model unique from other LSS models. Further, LESIRE was tested in three different SMEs, and it aided them to identify and improve their weak areas, thereby readying them for LSS deployment. Originality/value: The main contribution of this study it proposes a LESIRE model that evaluates the organization for FLSS and FPII for LESIRE, which is essential for the organization embarking on an LSS journey. Further, it improves the readiness of the organization that is already practicing LSS.

LanguageEnglish
JournalInternational Journal of Quality and Reliability Management
Early online date22 Jan 2019
DOIs
StateE-pub ahead of print - 22 Jan 2019

Fingerprint

Lean Six Sigma
Fuzzy logic
Manufacturing industries
Readiness
Small and medium-sized enterprises
Evaluation model
Factors

Keywords

  • FLSS
  • FPII
  • Fuzzy logic
  • Lean Six Sigma (LSS)

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Strategy and Management

Cite this

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title = "Assessment of Lean Six Sigma Readiness (LESIRE) for manufacturing industries using fuzzy logic",
abstract = "Purpose: Many organizations have reported significant benefits after the implementation of Lean Six Sigma (LSS). Embracing LSS requires asking some important questions: How Lean Six Sigma Readiness (LESIRE) can be measured? How can an organization identify the barriers for LESIRE? Answers to these questions are critical to both academicians and practitioners. The paper aims to discuss this issue. Design/methodology/approach: This study illustrates the development process of a Lean Six Sigma Readiness (LESIRE) evaluation model to assess an organization’s readiness for LSS deployment using the fuzzy approach. The model was developed from 4 enablers, 16 criteria and 46 attributes of LSS, identified through a literature review. Findings: To demonstrate the efficiency of the model, this study testing the LESIRE evaluation model in three Indian SMEs. Using experts’ ratings and weight, the researchers calculated the Fuzzy Lean Six Sigma index (FLSS) which indicates the LESIRE level of an organization and the Fuzzy Performance Importance Index (FPII) that helps to identify the barriers for LESIRE. Research limitations/implications: The main limitations of this study are that it did not consider the failure factors of LSS for model development and the LESIRE was only tested in manufacturing industries. Thus, future researchers could focus on developing a model with failure factors. The results obtained from the SMEs show that LESIRE is capable of assessing LESIRE in an industrial scenario and helps practitioners to measure LESIRE for the future decision making process. Practical implications: The LESIRE model is easy to understand and use without much computation complexity. This simplicity makes the LESIRE evaluation model unique from other LSS models. Further, LESIRE was tested in three different SMEs, and it aided them to identify and improve their weak areas, thereby readying them for LSS deployment. Originality/value: The main contribution of this study it proposes a LESIRE model that evaluates the organization for FLSS and FPII for LESIRE, which is essential for the organization embarking on an LSS journey. Further, it improves the readiness of the organization that is already practicing LSS.",
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Assessment of Lean Six Sigma Readiness (LESIRE) for manufacturing industries using fuzzy logic. / Sreedharan V., Raja; Raju, R.; Sunder M., Vijaya; Antony, Jiju.

In: International Journal of Quality and Reliability Management, 22.01.2019.

Research output: Contribution to journalArticle

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