Knowledge Discovery for Procurement of Electric Vehicles' Parts in Pakistan

Project Title

Knowledge Discovery for Procurement of Electric Vehicles' Parts in Pakistan

Project Area of Specialization Mechanical EngineeringProject Summary

Project Summary:

The purpose of the project is to develop an assessment tool for the procurement of Electric Vehicles' parts in Pakistan with a minimum risk of scam/fraud. Knowledge discovery and quality control management technique helps inspect the quality of EV products and grade every international EV vendor based on performance. This initiative helps filter out the dealers who can deliver quality EV products. The tool for assessment of suppliers/vendors can ultimately also help a common man import spare parts of EVs safely without facing any fraud/scam.

Project Objectives

The Objectives of the Project include:

1. Gathering Data from Different Resources
2. Pre-Processing and Mining Data
3. Interpretation of Data for a Model
4. Analysis of the Data
5. Development of Assessment Tool to check reliability of a vendor.

Project Implementation Method

The focus of methodology is primarily on knowledge discovery from the data available to help Pakistan’s automobile dealers make procurement decisions.

(1) Comprehending the Desired Goals:

Initially, the research is executed to determine the intended goals of Knowledge Discovery regarding authentic international suppliers for EV parts. To fulfil the objective, a thorough analysis of global research papers is carried out to find the availability and supply of EVs and their parts worldwide.

(2) Gathering Target Data:

The certified assessment reports, available online, of vendors/suppliers that provide EV parts to customers are analyzed for data collection. The criteria to evaluate supplier performance are chosen based on knowledge of the hypothesis and design of research.

(3) Pre-Processing and Mining:

Data Pre-Processing techniques are employed to complete the missing points, even noisy data and eliminate inconsistencies.

(4) Model Building:

The research under consideration uses algorithms, for example, JRIP (ripple), PART and J48 (decision tree) to construct diverse models by employing a data mining tool such as WEKA.

(5) Evaluation and Interpretation of Mined Data:

Several patterns concerning a vendor’s grades are analyzed. The outputs are improved by changing the algorithms' features and afterwards run their interpretation to assess the data on the supplier of EV parts.

(6) Development of Assessment Tool

The research integrates the knowledge into the performance system to develop an assessment tool to check an EV vendor's reliability. 

Benefits of the Project

The Benefits of the Project Include:

1. Development of Generic Assessment Tool that will help the business community in Pakistan to import affordable electric vehicles' parts without compromising on the quality.
2. The project will play a pivotal role in implementing electric vehicle policy proposed by the Government of Pakistan.
3. The project will ultimately contribute towards economic growth by cutting down dependency on fossil fuels.
4. It will also contribute to a clean and sustainable environment with fewer greenhouse gas emissions from conventional vehicles.

Technical Details of Final Deliverable

To develop a Generic Assessment Tool for convenient evaluation of EV vendors for a common man in Pakistan in the light of the recent Government of Pakistan's policy concerning EVs and their parts.

Final Deliverable of the Project Software SystemCore Industry TransportationOther Industries Energy , Transportation , Security Core Technology Internet of Things (IoT)Other Technologies OthersSustainable Development Goals Affordable and Clean Energy, Decent Work and Economic Growth, Responsible Consumption and ProductionRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	79999
Online Paid Subscriptions	Equipment	6	5000	30000
High Speed Internet	Equipment	12	1500	18000
Online Library Database	Equipment	4	5500	22000
Prints and Stationary	Miscellaneous	3	3333	9999