Senseye > Case Studies > Nissan Manufactures Vehicles in 20 Countries

Nissan Manufactures Vehicles in 20 Countries

Senseye Logo
 Nissan Manufactures Vehicles in 20 Countries - IoT ONE Case Study
Technology Category
  • Analytics & Modeling - Predictive Analytics
  • Functional Applications - Computerized Maintenance Management Systems (CMMS)
Applicable Industries
  • Automotive
Applicable Functions
  • Business Operation
Use Cases
  • Predictive Maintenance
  • Software Design & Engineering Services
The Challenge

With an abundance of sensor data but insufficient skilled resources to perform manual analysis, Nissan was keen to expand the benefits of using data and machine learning to influence maintenance. In 2016, it decided to embark on a Predictive Maintenance program to reduce production downtime by up to 50% across thousands of diverse machines.

It was attracted to Senseye by its deep domain experience and ability to scale across its sites, underpinned by its patented Artificial Intelligence technology.

The Customer

Nissan (Globally)

About The Customer

Nissan manufactures vehicles in 20 countries and areas around the world, including Japan, the USA, Russia, and the UK. Its global vehicle production volume exceeded 4.7 million in 2020, with products and services provided in more than 190 countries.

The Solution

For more than 5 years, with support from Senseye’s industry experts. Nissan has expanded its predictive maintenance capability across their global production sites where models such as the Qashqai, X-Trail, Leaf, and Rogue are produced.

Over time, Nissan has become autonomous in its adoption and scaling of its predictive maintenance journey. Together with Senseye PdM Omniverse to upskill their users, Nissan engineers can now onboard new machines and integrate with other enterprise software independent of Senseye.

Operational Impact
  • [Cost Reduction - Operation]
    • Tens of millions in saved downtime.
    • Rapid Return on Investment of less than 3 months
  • [Efficiency Improvement - Installation]

    Reduction in preventative maintenance and secondary activities

Quantitative Benefit
  • Up to 6 months advance warning of machine failure

Case Study missing?

Start adding your own!

Register with your work email and create a new case study profile for your business.

Add New Record

Related Case Studies.

Contact us

Let's talk!
* Required
* Required
* Required
* Invalid email address
By submitting this form, you agree that IoT ONE may contact you with insights and marketing messaging.
No thanks, I don't want to receive any marketing emails from IoT ONE.

Thank you for your message!
We will contact you soon.