Degree
Master of Science in Data Science
Department
Department of Computer Science
Faculty/ School
School of Mathematics and Computer Science (SMCS)
Date of Submission
Fall 2023
Supervisor
Dr. Imran Khan, Assistant Professor, Department of Computer Science
Keywords
Process Mining, Fabric defects, Knitting, Workflows, Power Automate, Process Discovery
Abstract
Defects in the Knits manufacturing process result in a significant waste of resources and further affect the quality of finished products. These defects occur due to inefficient processes, non-standardized systems, and the inability to track root causes promptly. Reducing the defects in the knitting process can decrease production downtime and manufacturing costs which will increase productivity and revenue.
Process Mining is a very efficient tool that helped in defect reduction by optimizing the overall knitting process workflows. The ability to extract useful information from process logs helps in identifying top defects, their root causes, and process bottlenecks which aid in proactive decision-making. The main phases of Process Mining are process discovery, conformance checking, and process enhancement.
In this paper, a large Knits manufacturing industry was selected as a case study. Process mining methods and techniques were applied to the production log data logs. In Process discovery, process workflows were extracted and visualized, important trends were observed and notable insights were given. These insights included top defects across all categories, products with the most defects, and inefficient parts of the processes.
The recommendations based on the insights were pivotal in the implementation of some improvement and optimization projects for a product range. It not only reduced the number of defects but also decreased the rejection rate by 3.6%.
Document Type
Restricted Access
Submission Type
Research Project
Recommended Citation
Zahidi, U. (2023). Reducing Defects in Textile Knitting Operations Using Process Mining Approach (Unpublished graduate research project). Institute of Business Administration, Pakistan. Retrieved from https://ir.iba.edu.pk/research-projects-msds/27
Demo video -Uzair Zahidi.rar (24712 kB)
The full text of this document is only accessible to authorized users.
