ArticleEnvironmental science and pollution research international2021
Selection and performance estimation of Green Lean Six Sigma Projects: a hybrid approach of technology readiness level, data envelopment analysis, and ANFIS.
Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Nowadays budget and schedule constraints have forced organizations to select six sigma projects based on pre-defined success criteria. Also, progressive approaches based on green and lean paradigm are vital for companies to enhance their social and environmental performance. Then, Green Lean Six Sigma (GLS) projects play the main role in improving the performance of an organization while augmenting its sustainability. Accordingly in this paper, past studies were reviewed, and GLS projects' indicators and performance evaluation criteria were identified. Data envelopment analysis (DEA) was employed for the appropriate selection of GLS projects. Next, the ranking and performance weight of each project were investigated, and also the projects were categorized based on the technology readiness level (TRL). Additionally, an adaptive neuro-fuzzy inference system (ANFIS) method was applied for the successful prediction of selected GLS projects. Twenty-eight inputs and 9 outputs for the first project category (with TRL 9) and 28 inputs and 6 outputs for the second project category (with TRL 8) were entered into the model. The statistical assessment measures such as Nash-Sutcliffe efficiency (NSE), root mean squared of error (RMSE), mean absolute error (MAE), and R
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