Case Study Keya Knit Composite
ACTIONS
Case Study : ERP Project
Company Profile
Keya Knit Composite a leading manufacturer, merchandiser and exporter of knitted garments. With state-of-the-art yarn spinning mills, fabric cutting and sewing facilities, Keya knit produces and exports high quality of ready-made garments. It is capacitated to finish 170,000-210,000 pieces T-shirts per day through 170 production lines and 10200 machines. The industry is capacitated to produce its own yarn using raw cotton and fabric as per buyer specifications, which are vests, trunks and T-shirts.
With over 25 years of experience, it has unique product ranges that are designed to cater every segment of men, women, boys and girls.
ERP System
To meet the customer specification the entire operation performed using automated equipment. After knitting, dyeing and cutting of fabrics in different Style, Color and Size, the garments are sewn/stitched in assembly lines where sewing machine operators receive a bundle of cut fabric and repeatedly sew the same portion of the garment and passing that completed portion to the next operator.
Quality assurance is performed at the end of the sewing line to ensure that the garment has been properly assembled and that no manufacturing defects exists. Cosmetic flaws, stains and other spots on the garment are marked and cleaned using steam, hot water or chemical stain removers.
Completed sewn garments are ironed, folded, tagged, sized and packaged according to the customer specifications. Finally, the retail ready-made garments are shipped to client distribution centers via sea/air freight forwarder.
The Pain Points Faced By The Organization
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The company has two manufacturing units; thus, they can’t track the exact order position/status due to no centralized software system to monitor buyer order position between multiple production units.
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The existing legacy systems were standalone solutions. So, the data was unavailable to report at a glance.
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The organization didn’t have the integrated centralized system to track and update the top management with reports on:
- Daily Production, Rejection and Delivery
- Details of Stock
- Financial Activities
- Order Pre and Post Costing
- Merged Profit & Loss between multiple units
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Production shortage due to machine breakdown and unavailability of spares stock for maintenance
ERP Implementation
Our proposed ERP understood the needs and purposes of the company business processes through the roadmap business process re-engineering. The system study team collaborated with the organization core team and through preliminary analysis & As-Is study, captured the changes required to address the digital needs of all its business processes, especially the pain points. The ERP modules implemented into the business workflows to digitize, integrate, streamline and automated system are:
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Financial Management
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Supply Chain Management
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Planning and Manufacturing
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Plant Maintenance
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Commercial Management
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Quality Inspection
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Wastage Management
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Sales and Distribution
Answer To The Company’s Pain Points
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The implemented ERP system facilitates to capture multi-unit, multi-segment data in centralized systems. So, the merge reporting easily can manage between the units
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Maintained integrated workflows as per business processes between the departments and sub-departments from material sourcing to dispatching
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Track the Re-order level of stock at the production area helps to the current used and required stock of raw materials
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Track Buyer Order, Style, Color and Size wise material requirement, purchase, consumption and wastage to analyze pre & posting costing
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Track Buyer Order, Style, Color and Size wise daily input, output and reject in between production processes
e.g. Knitting → Dyeing → Cutting → Sewing → Finishing to monitor the order position at a glance.
Implementation Success
Our ERP system has perfectly aligned with the organization business workflow. The ERP solution facilitates faster and better management decision by providing crucial information in timely manner. Its also eliminates errors caused by multiple input of the same data and has ultimately delivered the ROI.