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How are Defects Impacting your Company's Bottom Line? 

Quality improvements are difficult to measure and identify, yet they are vital to the success of any product. Costs associated with poor quality products come in many forms including:

Testing and detecting defective products

testing

Repairing or replacing a product for a customer

repairing

Poor perception of quality by the end customer

award

Failure of a product at a customer site
 

Negative

Service and maintenance due to low quality products

repair

Who is using IoT Data to improve quality? 

Leading companies are leveraging automated systems and IoT data to test their products and improve quality. Tesla, Raymond, and Daimler Trucks use connected systems and remote data to improve their products.

Tesla

Tesla has become the world leader in fully electric cars in less than 10 years by leveraging their customers vehicles as test platforms through their Telemetry Solution. This information has been instrumental in giving Tesla an edge over other car manufacture in the world...

Tesla image

Battery Analysis

The production data includes everything from the exact day and time it was produced to how well it performed post manufacturing.

 

This data can be used to:

  • Compare different battery designs
  • Justify different production test limits
  • Systematically improve the quality of their energy platform

Software Verification

Tesla has been able to operate their vehicles using production software in parallel with a simultaneous instance of beta software.

 

This data can be used to:

  • Compare the output of each control system to one another reporting back the differences
  • Perform the data analysis locally, so no need for a massive cloud based AI
  • Massive simultaneous testing

Feature Improvements

Tesla can leverage their entire fleet of cars which allows them to introduce new features and test them under actual driving conditions.

 

This data can be used to:

  • Compare the performance of the auto pilot to the current driver
  • Determine why the driver made any given decision
  • Improve or even teach their auto pilot AI
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Forklift_image

Raymond

One of the highest quality forklift manufactures in the world. They introduced iWarehouse, a IoT application to improve fleet optimization, operator performance, and document forklift performance to showcase the high reliability of the product.

Raymond Pain Points before iWarehouse

  • Customers understanding the value of owning the highest performing machines in the market.
  • Documenting and showcasing their performance advantage.
  • Finding a way to measure the performance of the machines independent of a operator

Real-time Detection

Raymond and it's customers can monitor operators, detect collisions, and prevent machine misuse.

 

This data can be used to:

  • Address operator misuse quickly and efficiently
  • Identify sensor data generated during times of misuse
  • Ensure the quality team is focused on failures occurring under normal operating conditions

Cost of Ownership

This data allows management to understand how the lift is being used, specifically the average speed of the lift.

 

Cost savings for example:

  • Recording key metrics; vehicle velocity, total loads moved, distance traveled, etc.
  • Allows customers to document the value of Raymond Lithium Ion batteries which enable higher speeds for longer periods of time with less charging
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Daimler Trucks

Daimler Trucking is investing heavily in the data access solutions for their trucking products. Over the past few years Daimler has been integrating data connectivity solutions into their trucks, allowing them to liberate the sensor data trapped in the truck.

Trucks

Data Access Solutions

In this system an edge gateway with a cellular modem, is used to collect data from the Engine Control Unit (ECU) and other vehicle management systems.

 

This data can be used to:

  • Create a virtual technician to detect failures before they occur
  • Route drivers to service centers before a failure forces the driver to make an unexpected and potentially costly stop

Quality Engineers Benefits

Destructive testing is the most time consuming and costly way to verify the quality of a component and can be difficult to do.

 

 

This data can be used to:

  • Decrease the amount of destructive testing
  • Reduce testing times
  • Monitor the components until failure to determine the life of the device under normal conditions

Remote Monitoring

Without remote monitoring many component failures may go undocumented this is especially true once a product is past warranty.

 

 

This system allows:

  • Critical data to be collected for developing and improving the platform over time
  • More than 400,000 vehicles to be monitored
  • The development of a successful customer service platform under the brand name Detroit Connect

Questions about how to leverage IoT Data to improve your products quality?

Contact one of our IIoT experts:

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