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Proposal of the Comprehensive Project on
“A Study on the barriers of data driven quality
management in Indian Automobile Industry “
Name: Tanmoy Kolay
Roll: 21PGDM-BHU112
Project Title:
“A Study on the barriers of data driven quality management in Indian Automobile Industry “
Project Objective:
• To know about the data driven quality management.
• To study about the current scenario of data driven quality management in automobile industry.
• To identify the barriers of data driven quality management.
• How to overcome those barriers
Project Summary:
The automotive industry has always been an example in the field of Project Management and Leadership
and, of course, as far as quality is concerned. Increasing global competition over the past decade has
forced automotive companies to improve quality and efficiency. Using the management tools that are
relevant to the organization’s needs has become a strategic issue for companies in today’s competitive
environment. Data-driven quality management enables to pre-emptively identify possible defect points
before and during as opposed to after production. This approach involves:
 Systematically collecting and analysing real-time quality data
 Using data to build quality models and profiles
 Comparing product samples and machinery status to the quality models and profiles in real time
Data-driven quality management delivers a more accurate and efficient way to identify the exact point of
potential defects, improving problem solving and resulting in products that adhere more closely to
predetermined standards.
The aim of this research is to identify the various types of barriers that an automotive component
manufacturing company faces when attempting to introduce data driven quality management. So, the
future scope of this study is huge.
The process flow of the project will be:
1. Identifying the barriers of data driven quality management.
2. Consulting with industry professionals to get more clarity about these barriers.
3. Then analysis will be done based on the previous two.
4. The findings and limitations of the research will be noted.
5. Then the future scopes of improvements of the study will be recommended.
Research Methodology:
• Research Design: Exploratory
• Source of the data: Both Primary and Secondary Data.
• Sampling Plan: Convenient Sampling.
• Sample Location: Both Online and Offline Survey.
• Research models to be used: ISM-Dematel, Network relation Map
• Data Analysis and Representation: Both graphical and statistical analysis of data.

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CP.pdf

  • 1. Proposal of the Comprehensive Project on “A Study on the barriers of data driven quality management in Indian Automobile Industry “ Name: Tanmoy Kolay Roll: 21PGDM-BHU112
  • 2. Project Title: “A Study on the barriers of data driven quality management in Indian Automobile Industry “ Project Objective: • To know about the data driven quality management. • To study about the current scenario of data driven quality management in automobile industry. • To identify the barriers of data driven quality management. • How to overcome those barriers Project Summary: The automotive industry has always been an example in the field of Project Management and Leadership and, of course, as far as quality is concerned. Increasing global competition over the past decade has forced automotive companies to improve quality and efficiency. Using the management tools that are relevant to the organization’s needs has become a strategic issue for companies in today’s competitive environment. Data-driven quality management enables to pre-emptively identify possible defect points before and during as opposed to after production. This approach involves:  Systematically collecting and analysing real-time quality data  Using data to build quality models and profiles  Comparing product samples and machinery status to the quality models and profiles in real time Data-driven quality management delivers a more accurate and efficient way to identify the exact point of potential defects, improving problem solving and resulting in products that adhere more closely to predetermined standards. The aim of this research is to identify the various types of barriers that an automotive component manufacturing company faces when attempting to introduce data driven quality management. So, the future scope of this study is huge. The process flow of the project will be: 1. Identifying the barriers of data driven quality management. 2. Consulting with industry professionals to get more clarity about these barriers. 3. Then analysis will be done based on the previous two. 4. The findings and limitations of the research will be noted. 5. Then the future scopes of improvements of the study will be recommended.
  • 3. Research Methodology: • Research Design: Exploratory • Source of the data: Both Primary and Secondary Data. • Sampling Plan: Convenient Sampling. • Sample Location: Both Online and Offline Survey. • Research models to be used: ISM-Dematel, Network relation Map • Data Analysis and Representation: Both graphical and statistical analysis of data.