The garment industry has long relied on experience and historical data for planning. But with shorter lead times, changing demand, and complex supply chains, intuition alone is no longer enough.
Operations Research (OR) brings a scientific approach: converting production challenges into mathematical models, testing solutions through simulation, and selecting the most efficient option.
It transforms uncertainty into structured, data-driven decision-making.
"Complex dynamic problems are being addressed with static assumptions — OR changes that."
Capacity is planned using SAM/SMV and expected efficiency. Materials are planned using past consumption and vendor history. These methods often ignore real-time variability.
Variables at Play
Resulting Problems
A production challenge is systematically transformed through four stages:
This shifts factories from guesswork to optimization.
Optimize labour, machine, and time allocation
Match operators to tasks efficiently
Reduce waiting time and bottlenecks
Improve material movement
Support sourcing and strategic decisions
They help improve: Line balancing · Plant layout · Machine allocation · Supply chain planning
Modern production requires scientific planning.
Capacity, demand, and materials must work together.
Virtual testing improves decision quality.
Better models lead to better outcomes.
When factories make the shift from intuition to intelligence, they achieve higher efficiency, predictability, and profit.
"Model the system, measure its behavior, manage its flow — only then can you truly optimize its outcome."
