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ArticlePeer ReviewedOpen AccessPlagiarism Passed
Paper ID:IJSREM62413

Garment360-Integrated Analytics And Decision Support Platform

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM62413

Volume:

10 |

5 |

May 2026

Pages:

1-7

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
Not assigned

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Agalya A

Agalya A

Computer Science And Engineering

Tagore Institute Of Engineering And Technology

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BK

Bhuvana K

Computer Science And Engineering

Tagore Institute Of Engineering And Technology

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AC

Abitha C

Computer Science And Engineering

Tagore Institute Of Engineering And Technology

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PS

Pachaiyammal S

Computer Science And Engineering

Tagore Institute Of Engineering And Technology

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Mentors

BK

Bakya K

Computer Science And Engineering

Tagore Institute Of Engineering And Technology

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Abstract

The garment industry continues to rely on fragmented, manual processes for managing inventory, workforce attendance, billing, and financial transactions, leading to data inconsistencies, processing delays, and poor decision-making. This paper presents the analysis and design of Garment360, a computerized integrated management system developed for garment business operations. The system requirement study was carried out across garment business workflows encompassing billing, labour attendance, stock management, transaction processing, and reporting. System analysis is performed using Data Flow Diagrams (DFDs) identifying key processes across four functional sub-systems: Billing, Labour Attendance, Stock Management, and Transaction Management. Design of system entities, their relationships, and attributes is carried out using Entity Relationship (ER) modelling. Structural design is accomplished using Unified Modelling Language (UML) techniques. The complete database consists of five normalized tables designed up to Third Normal Form (3NF). Built using Python with Tkinter and SQLite, the platform supports multi-branch operations across five locations with three-tier role-based access control (Admin, Manager, Staff) secured by SHA-256 hashing. All eight system test cases passed, confirming the reliability of the platform for small to medium-scale garment enterprises.

KEYWORDS

Keywords—garment management system; DFD; ERD; UML; database normalization; Python Tkinter; SQLite; inventory control; labour attendance; multi-branch operations; role-based access control; SME digitalization

Cite This Article

Agalya A, Bhuvana K, Abitha C, Pachaiyammal S, Bakya K, "Garment360-Integrated Analytics And Decision Support Platform," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-7, May 2026.

Full Article/Conclusion

Our findings confirm that lack of adequate resources constrains garment enterprises from effectively implementing generalized ERP systems, and that these constraints have different impacts at different operational stages. (i)    Thorough requirement study of Garment360 resulted in identifying important activities in garment business management and related data and information flows across four sub-systems. (ii)  After system analysis, the Garment360 platform comprises four functional sub-systems: Billing Management, Labour Attendance Management, Stock Management, and Transaction Management. (iii)   Analysis of data flow, information flow, and processing activities using DFDs identified six processes in Billing, seven in Labour Attendance, five in Stock Management, and four in Transaction Management. (iv)   Preliminary system design using ERD identified five entity types (User, Branch, Labour, Stock, Transaction) with five relationships between them. (v)  Structural design using UML produced four core classes and a complete database schema normalized to 3NF/BCNF. (vi)  The complete database consists of five tables with attributes, data types, and relationship keys fully specified and implemented. All eight test cases passed, confirming platform reliability. Future enhancements: (i) web-based architecture using Django/Flask; (ii) mobile companion application for Android/iOS; (iii) cloud storage integration (AWS S3/Firebase); (iv) ML-based demand forecasting and inventory optimization; (v) barcode scanning hardware, automated procurement notifications, and advanced drill-down analytics.

References

[1]  T. H. Davenport, “The future of enterprise system-enabled organizations,” Information Systems Frontiers, vol. 2, no. 2, pp. 163–180, 1998. [2]  Z. Lee and J. Lee, “An ERP implementation case study from a knowledge transfer perspective,” J. Information Technology, vol. 15, pp. 281–288, 2000. [3]   M. Summer, “Risk factors in enterprise-wide/ERP projects,” J. Information Technology, vol. 15, no. 4, pp. 317–327. [4]  R. Elmasri and S. Navathe, Fundamentals of Database Systems, 3rd ed. Addison-Wesley, 2000. [5]  E. Handoyo, “SRS Document Proposal Analysis on the Design of MIS According to IEEE STD 830-1998,” Procedia Social and Behavioural Sciences, vol. 67, pp. 123–134, 2012. [6]  R. K. Chakrabortty and S. K. Paul, “Study and Implementation of Lean Manufacturing in a Garment Manufacturing Company,” J. Optimization in Industrial Engineering, vol. 7, pp. 11–22, 2011. [7]   I. Sommerville, Software Engineering, 10th ed. Pearson, 2016. [8]  J. Rumbaugh, I. Jacobson, and G. Booch, UML Reference Manual, 2nd ed. Addison-Wesley, 2004. [9]   W. McKinney, Python for Data Analysis, 3rd ed. O’Reilly, 2022. [10] M. T. Tsai and C. H. Lin, “Integrated Inventory Management for Apparel Industries,” J. Textile Engineering, vol. 8, no. 2, 2022. [11]  A. Tiwari and K. Sharma, “Digital Transformation in Small Garment Industries Using Open Source Tools,” Proc. IEEE ICET, 2023. S. Bhattacharya, “Role-Based Access Control in Lightweight Desktop ERP Applications,” Int. J. Inf. Syst. Manag., vol. 5, no. 1, 2021

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Publication Date

5/3/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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