Abstract:
n recent years, particularly in the aftermath of COVID-19 pandemic, there
has been a drastic decline in the number of production orders in the realm of
home textile industry. This abrupt decline in production volume has
significantly contributed to an increase in competition within the industry,
exacerbating the already-difficult task of maintaining customer satisfaction.
As a result, it has become imperative for the industry to deftly navigate such
ongoing challenges; therefore, this scholarly work delves into systematic
approach to efficiently improve production processes in textile sector. It
begins by understanding critical customer needs, including higher quality, on time delivery, improved working conditions, cost-effectiveness, and safety
audits within facilities. Thereafter, customer requirements are translated into
technical specifications using the Quality Function Deployment (QFD). The
study employs Monte Carlo simulation to prioritize risks and uses statistical
tools like Pareto charts in Minitab software to analyse current risk conditions.
As it is observed that home textile sector has remained an untapped domain,
devoid of significant research, the application of this integrated approach in
the home textile sector, and the commencement of research within textile
industry at large, underscore the novelty of this study. Also, innovating
beyond conventional DMAIC approach, this study pioneers a novel matrix
that comprehensively encapsulates the entire spectrum of defects,
transcending traditional matrices. Consequently, corrective measures
suggested by experts and literature are implemented and evaluated in a pilot
run, demonstrating the impact of improvements on the production processes.
This research offers a structured, data-driven approach to enhance product
quality, meet customer expectations, and mitigate prioritized risks in home
textile manufacturing industry.
