IoT Enabled Digital Transformation in Automotive

TVS group leverages IoT to connect a complex and heterogeneous assembly line and gain deep insights into multiple aspects of their manufacturing process.

The Customer

TVS Motor Company is a public listed company headquartered in India. TVS Motor Company is a reputed two and three-wheeler manufacturer, and the flagship company of the USD 8.5 billion TVS Group. The only two-wheeler company to have received the prestigious Deming Prize, it’s the third largest two-wheeler manufacturer in India and also ranked in the top 10 globally. The company has an excellent track record with innovation and quality and is the market leader in customer service.
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The Problem

TVS wished to drive IoT-enabled digital transformation by connecting machines on the assembly line. The idea was to integrate machine data with related information from other IT systems on the shop floor to build a manufacturing data lake. Analysis of this data would bring visibility and predictability into its manufacturing value chain. There were several critical aspects that the implementation needed to address.

The Solution

The complete Datonis suite was deployed at TVS with custom integrations and custom analytics and reports. The solution deployed was a hybrid in nature with Datonis Edge deployed in a fail-safe configuration inside the customer’s network. Altizon’s IoT platform and Datonis Digital Factory were deployed on the cloud.
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Benefits

Productivity Improvement

Get an insight into parameters that impact line productivity, such as line rates, loss, and quality analysis at multiple levels.

Traceability

Trace a product through its manufacturing life cycle, and derive insights around critical quality, condition, and production data at every stage.

Quality

Perform root cause analysis of parameters that govern product quality using statistical techniques. Correlate this with machine condition.

Machine Condition Monitoring

Monitor and analyze parameters that are critical to machine health. Optimize machine downtime by predicting failure before it occurs.

Consumption

Analyze energy and other consumables that are part of the production process and discover ways to optimize their utilization.

Skill Matrix

Maintain a digital trace of operator performance. Enable the identification of a skill matrix and identify any exceptions that could impact product quality.

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