Exploring the importance of flexible manufacturing system performance variables for textile industries
Vikas Swarnakar, Vimal Kumar, Malik KhalfanPurpose
Manufacturing firms in the textile sector face simultaneous pressure to enhance responsiveness, maintain quality, shorten lead times, and align production with sustainability expectations. In the current Industry 4.0/5.0 environment, flexible manufacturing systems (FMS) are increasingly viewed as strategic enablers of product variety, speed and resource efficiency. However, managers still lack clear evidence on which performance variables deserve priority in textile settings. This study, therefore, identifies, classifies and prioritizes the most influential FMS performance variables for textile manufacturing.
Design/methodology/approach
A triangulation design was adopted. First, a focused literature review was undertaken to compile candidate FMS performance variables. Second, semi-structured interviews with 17 experts and a questionnaire survey of 135 domain experts were used to validate the variables for the textile context. Third, 19 validated variables were classified into 3 major categories, quality, productivity and flexibility, and prioritized using the best-worst method (BWM), a multi-criteria decision-making approach selected for its lower comparison burden and stronger consistency.
Findings
The study identifies 19 performance variables that are significant for FMS in textile industries and classifies them into quality, productivity and flexibility categories. The results show that quality-related variables dominate the overall ranking; automation emerges as the most influential quality variable, unit manufacturing cost is the leading productivity variable and the use of automated material-handling devices is the most important flexibility variable. These findings offer an evidence-based basis for sequencing FMS investment and improvement efforts.
Research limitations/implications
The results are derived from expert judgements and a textile-sector case context and should therefore be interpreted with appropriate contextual caution. Even so, the study offers actionable implications for managers by showing which variables should be prioritized first under limited resources. The findings also suggest that future research should test the framework through larger cross-sector datasets and incorporate broader sustainability and digitalization variables.
Originality/value
The originality of the study lies not simply in applying BWM, but in contextualizing FMS prioritization for the textile sector at a time when digitalization, sustainability and circular-economy objectives are reshaping manufacturing choices. The paper shows how textile-specific operational constraints influence the relative importance of FMS performance variables in ways that are not fully captured by prior generic manufacturing studies.