Deconstruction of Operational Variability in Biomass Production: An Application of Lean Six Sigma and System Dynamics

Purpose: This study seeks to optimise key production parameters for biomass pellets by employing Lean Six Sigma (LSS) alongside dynamic system simulation. Emphasis is placed on fine-tuning moisture content, durability, and pellet diameter to meet international quality standards and performance operational. Methodology/Approach: The research integrates DMAIC methodology with dynamic simulation modelling, analysing and optimising drum speed, material feed rate, and drying temperature via factorial design and system dynamics. Findings: Implementing LSS markedly reduced moisture variability, hitting a stable mean of 9.446% and cutting defects down to 59,000 PPM. Durability saw a notable lift from 91.976% to 95.896%, with defects slashed by 80%. Pellet diameter was fine-tuned from 7.241 to 7.051 mm, bringing defects down to 45,000 PPM. The results meet international standards and show improvements in process performance. Research Limitation/Implication: The study is limited to one biomass site, focusing on key quality parameters. Future research could assess scalability and suitability across other renewable energy sectors. Originality/Value of paper: This research highlights the novel integration of Lean Six Sigma and dynamic simulation in biomass pellet production, providing a robust framework for quality and operational stability in energy.

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Publication Details

Journal
Quality Innovation Prosperity
Published
2025-03-31
DOI
https://doi.org/10.12776/qip.v29i1.2138
Primary Topic
Quality and Supply Management
Type
article
Field-Weighted Citation Impact
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article

Deconstruction of Operational Variability in Biomass Production: An Application of Lean Six Sigma and System Dynamics

Juan Carlos Cayán-Martínez, Eduardo Francisco García Cabezas, Julio César Moyano Alulema, Angel G. Guamán Lozano et al.
Quality Innovation Prosperity
Quality and Supply Management
article

Deconstruction of Operational Variability in Biomass Production: An Application of Lean Six Sigma and System Dynamics

Juan Carlos Cayán-Martínez, Eduardo Francisco García Cabezas, Julio César Moyano Alulema, Angel G. Guamán Lozano, Esteban Paúl Jordán Rodríguez, Juan Fernando Haro Velasteguí
article en

Abstract

Purpose: This study seeks to optimise key production parameters for biomass pellets by employing Lean Six Sigma (LSS) alongside dynamic system simulation. Emphasis is placed on fine-tuning moisture content, durability, and pellet diameter to meet international quality standards and performance operational. Methodology/Approach: The research integrates DMAIC methodology with dynamic simulation modelling, analysing and optimising drum speed, material feed rate, and drying temperature via factorial design and system dynamics. Findings: Implementing LSS markedly reduced moisture variability, hitting a stable mean of 9.446% and cutting defects down to 59,000 PPM. Durability saw a notable lift from 91.976% to 95.896%, with defects slashed by 80%. Pellet diameter was fine-tuned from 7.241 to 7.051 mm, bringing defects down to 45,000 PPM. The results meet international standards and show improvements in process performance. Research Limitation/Implication: The study is limited to one biomass site, focusing on key quality parameters. Future research could assess scalability and suitability across other renewable energy sectors. Originality/Value of paper: This research highlights the novel integration of Lean Six Sigma and dynamic simulation in biomass pellet production, providing a robust framework for quality and operational stability in energy.

Quality Innovation ProsperityVol. 29(1)
Escuela Superior Politécnica del Chimborazo (EC), Instituto Tecnológico de Cerro Azul (MX), Universidad Nacional de Chimborazo (EC)
Openalex Percentile: Top 91%
Quality and Supply Management
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