Gurtam Case Studies Monitoring of apparel factory workers in Sri Lanka

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	Monitoring of apparel factory workers in Sri Lanka Gurtam

Monitoring of apparel factory workers in Sri Lanka

Gurtam

Technology Category	Networks & Connectivity - NFC Sensors - GPS
Applicable Industries	Apparel
Applicable Functions	Human Resources Logistics & Transportation
Use Cases	Personnel Tracking & Monitoring Vehicle Telematics
Services	System Integration
Challenge	The client, a large apparel manufacturer from Sri Lanka, was facing issues with optimizing the planning system of production and transport departments. They needed to monitor employees across 14 factories located in Sri Lanka, Bangladesh, and India. The number of workers at each factory varied from 300 to 3,000, and the employees lived in the neighborhood and arrived at their work on special buses. The challenge was to develop a system that could accurately track the movement of these employees and provide real-time data to the production planning team. Read More
About Customer	The customer is one of the largest apparel manufacturers from Sri Lanka. They operate 14 factories located in Sri Lanka, Bangladesh, and India. The number of workers at each factory varies from 300 to 3,000. The employees live in the neighborhood and arrive at their work on special buses. The company was facing challenges in optimizing the planning system of production and transport departments due to the large number of employees and their scattered residences. Read More
Solution	KLOUDIP, a partner of Gurtam, implemented a test solution at a plant with 300 workers. The solution involved the use of Wialon, WiaTag, NimBus, and NFC tags. WiaTag, a mobile workforce management app, was installed on mobile devices in buses or connected to specialized NFC-readers. Employees were given NFC tags which they scanned when boarding and getting off the bus. This data was sent to Wialon, providing the production planning team with passenger reports one hour before the working shift starts. This allowed the team to know the exact time and location where a particular worker boarded and got off the shuttle bus, and adjust the production plan accordingly. NimBus was used to count the total number of passengers for every bus, determine the most popular and crowded stopping points, and build the most efficient route. Read More Log in to view content
Contents

Technology Category

Networks & Connectivity - NFC

Sensors - GPS

Applicable Industries

Apparel

Applicable Functions

Human Resources

Logistics & Transportation

Use Cases

Personnel Tracking & Monitoring

Vehicle Telematics

Services

System Integration

Challenge

The client, a large apparel manufacturer from Sri Lanka, was facing issues with optimizing the planning system of production and transport departments. They needed to monitor employees across 14 factories located in Sri Lanka, Bangladesh, and India. The number of workers at each factory varied from 300 to 3,000, and the employees lived in the neighborhood and arrived at their work on special buses. The challenge was to develop a system that could accurately track the movement of these employees and provide real-time data to the production planning team.

About Customer

The customer is one of the largest apparel manufacturers from Sri Lanka. They operate 14 factories located in Sri Lanka, Bangladesh, and India. The number of workers at each factory varies from 300 to 3,000. The employees live in the neighborhood and arrive at their work on special buses. The company was facing challenges in optimizing the planning system of production and transport departments due to the large number of employees and their scattered residences.

Solution

KLOUDIP, a partner of Gurtam, implemented a test solution at a plant with 300 workers. The solution involved the use of Wialon, WiaTag, NimBus, and NFC tags. WiaTag, a mobile workforce management app, was installed on mobile devices in buses or connected to specialized NFC-readers. Employees were given NFC tags which they scanned when boarding and getting off the bus. This data was sent to Wialon, providing the production planning team with passenger reports one hour before the working shift starts. This allowed the team to know the exact time and location where a particular worker boarded and got off the shuttle bus, and adjust the production plan accordingly. NimBus was used to count the total number of passengers for every bus, determine the most popular and crowded stopping points, and build the most efficient route.

Impact #1	The company adheres to the production schedule and distributes the amount of work between working shifts rationally. This helps to avoid material losses because there is no downtime in apparel manufacturing anymore.
Impact #2	The transport routes and their distribution by districts were optimized according to the number of passengers. It saves drivers time and fuel, improves the usability of transport for factory workers.
Impact #3	The client’s HR department in the head office uses Wialon for calculating staff attendance. The data received enables the client making decisions that increase discipline in the workplace.

Impact #1

The company adheres to the production schedule and distributes the amount of work between working shifts rationally. This helps to avoid material losses because there is no downtime in apparel manufacturing anymore.

Impact #2

The transport routes and their distribution by districts were optimized according to the number of passengers. It saves drivers time and fuel, improves the usability of transport for factory workers.

Impact #3

The client’s HR department in the head office uses Wialon for calculating staff attendance. The data received enables the client making decisions that increase discipline in the workplace.

Benefit #1	Reduced costs: Now it is possible to calculate the average time the workers spend on the road. If the employee lives far from the factory, it would be more profitable to provide him with the hostel facilities; it this way the company reduces the cost of delivering employees to work.

Benefit #1

Reduced costs: Now it is possible to calculate the average time the workers spend on the road. If the employee lives far from the factory, it would be more profitable to provide him with the hostel facilities; it this way the company reduces the cost of delivering employees to work.

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Overview

Monitoring of apparel factory workers in Sri Lanka

Operational Impact

Quantitative Benefit