Challenge:
JK Tyre aimed to cut QA issues, inefficiencies, and scrap using AI-driven solutions.
JK Tyre aimed to cut QA issues, inefficiencies, and scrap using AI-driven solutions.
Solution:
Ikigai provided ML and Python training, followed by mentoring on plant-specific use cases.
Ikigai provided ML and Python training, followed by mentoring on plant-specific use cases.
Impact:
Participants built defect prediction models and dashboards, applied insights to reduce defects, collaborated to scale results, and initiated predictive maintenance and energy optimization use cases.
Participants built defect prediction models and dashboards, applied insights to reduce defects, collaborated to scale results, and initiated predictive maintenance and energy optimization use cases.