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Selection and performance estimation of Green Lean Six Sigma Projects: a hybrid approach of technology readiness level, data envelopment analysis, and ANFIS

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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 R2 were employed for capability appraisal of ANFIS model. Results of NSE and R2 indicators for both project categories were 1.00 that proved the efficiency of the ANFIS model for success prediction of GLS projects. Also, RMSE and MAE indicators for category 1 were 0.01 and 0.02 respectively. Similarly, these measures for category 2 were 0.02 and 0.02. The results advocate a proper approximation for observed values by the ANFIS model. Also, the results indicated that TRL as an important enabler of the GLS project has a meaningful role in the performance of GLS projects.

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Authors and Affiliations

  1. Information Technology Department, Iranian Research Institute for Information Science and Technology (IRANDOC), Tehran, Iran

    Mohammad Javad Ershadi

  2. Industrial Engineering Department, Science and Research Branch, Islamic Azad University, Tehran, Iran

    Omid Qhanadi Taghizadeh & Seyyed Mohammad Hadji Molana

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  1. Mohammad Javad Ershadi
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  2. Omid Qhanadi Taghizadeh
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  3. Seyyed Mohammad Hadji Molana
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Contributions

O. Qanadi Taghizadeh: conceptualization, methodology, and software

MJ Ershadi: data curation and writing - original draft preparation

SM Hadji Molana: visualization and investigation

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Correspondence to Mohammad Javad Ershadi.

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Ershadi, M.J., Qhanadi Taghizadeh, O. & Hadji Molana, S.M. Selection and performance estimation of Green Lean Six Sigma Projects: a hybrid approach of technology readiness level, data envelopment analysis, and ANFIS. Environ Sci Pollut Res 28, 29394–29411 (2021). https://doi.org/10.1007/s11356-021-12595-5

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