Enabled by technology, consumers now have access to an unlimited array of products. They have massive choices The fast-growing online channels have driven an important change: A demand-driven model, that every brand and retailer is adapting to Mass customization of products has translated into an urgent need for agility. To make and move an increasingly large SKU count, coupled with smaller volumes per SKU, is a challenge that EPIC is ready to embrace.
Manufacturers must combine large scale mass production units with leaner and agile Micro-Factories Micro-factories are smaller in scale, highly automated, and need fewer resources to set up and run, compared to a traditional factory. They are more flexible and can shift between different product types. They can manage smaller quantities efficiently and are less reliant on recruiting, training, and retaining large numbers of workers.
EPIC Group is using its decades-long success as a “Leading Supplier of Quality Apparel” to jump into the future. Looking at manufacturing through fresh eyes and “thinking outside the box”, we intend to create ZERO DEFECT, INNOVATION DRIVEN & ENVIRONMENTALLY SUSTAINABLE manufacturing units.
Through our relentless pursuit of better and diligent examination of all aspects of our current manufacturing processes and systems, we are developing an actionable industrial vision that will achieve the future of manufacturing.
MICRO FACTORIES – Key Features
Automating as many operations as possible to improve efficiency and productivity. Time will still be needed for retooling machines between two production runs, but we aim to reduce the change-over time thanks to versatile equipment and flexible production line layout
Expanding the operator skill-set to carry out multiple operations efficiently is one of the keys to reduce the learning curve in micro-factories where there are far fewer operators compared to a traditional factory. Such multi-skilled operators produce better quality products, are more efficient, and more likely to be retained for a longer period
A data-driven analytical allocation of operators to the appropriate workstations in the production line, not only based on their core skills but also considering their secondary skills, has been proven to be successful in reducing the learning curve
Across multiple products, this will help to reduce the change- over time and learning curve in addition to creating procurement leverage.
CLUSTERING SIMILAR PRODUCTS
This reduces the learning curve substantially when the production line switches from one product to another similar type of product.