$50 Million Saved
937 False Claimmants Identified
50% Reduction in Claims

Application of Big Data in Manufacturing Industry

About Client

Client is a manufacturer of spare parts for Commercial Vehicles, with a sizeable market share in the country. They lose a fair share of Revenue to warranty fraud.

Value Added

The Analytics solution has helped reduce total claims against poor quality products by 50%, and profit margin has increased by $250 million.

Discuss your Business Challanges


Client Overview

The Client is a leading Spare Part Manufacturing Company for Commercial Vehicles and Trucks, with a sizeable market share in the country. The Company earns a sizable sum of annual revenue amounting to $2 Billion but loses a fair share of its Revenue to claims made by Fraud claimants. In the past year, it faced losses totaling to $500 Million to pay out such fraudulent claimants.

Given this situation the Client is looking for a Big Data advanced analytics solution that will pull sensor data from the Datalog of the server to determine:

  • Which Product comes back with repeated complaints.
  • On which particular routes vehicles break down most number of times.

Business Solution

We developed a Big Data analytics platform using Golang, Python, and Hadoop to pull data from Teradata. The Platform can produce Historical data analysis based on Historical Data, and at the same time, it offers Predictive Analytics based on The Hadoop Data storage. The client has a Data volume turnover of 2PB annually.

This Data is in the form of Structured as well as Unstructured Data which is sourced from Sales, Marketing, Purchase, Claims paid/made, Dealers/Customer Information, GPS information and much more.

Our Analytics solution collects, stores and analyses data collected from this Terra Data by scheduling job to pull relevant data. The job scheduling lasts 15-18 hours.

Deciphering this massive amount of data and previous GPS information the platform can determine.

Historical Data Analytics

Clients who have made false claims

Reasons for breakdown of vehicles

Which product reported most complains

Predictive Analytics

Which spare part or product will report most number of breakdowns

Which route will cause most breakdowns

The predictive/ Big Data Analytics platform thus provides the Client with crucial information. This prediction aids them in taking accurate actions to avoid fraudulent claims.

13 Servers

1 is a master node with 32GB RAM, Hard Disk 2GB, Octa-core Processor

12 Data Nodes with 12 GB RAM and Quad Core Processors

Business Benefits

937 Vendors were found to be making False Claims

Total claims against poor quality products have reduced by 50%, and profit margin has increased by $250 million

$ 250 Million was saved from being paid to false claimants

There was a Cost Saving of 50%

Analytics tool in Manufacturing industry can help to significantly improve operations and save millions of dollars. Everything from product quality, production processes, production line, supply chains and more can be analyzed with the help of Big Data in Technology solutions. Machine learning algorithms, when applied to Big Data, can provide actionable insights which lead to successful manufacturing. One of the biggest advantages of such applications being predictive maintenance. By analyzing data regarding equipment operational parameters businesses can prevent equipment downtime which paralyzes manufacturing operations. It can also analyze such data to give real-time alerts. Thus, to sum it Big data analytics in manufacturing industry has a lot of scope. To understand more about it, drop us a message here.


Hadoop Hdfs

Apache Spark

Google Cloud

Hadoop Hive