Synergizing Artificial Intelligence with Product Recall Management Process

2023-01-0867

04/11/2023

Event
WCX SAE World Congress Experience
Authors Abstract
Content
There are a multitude of dynamics faced by any industry. There is also a consistent search and development of technological platforms and services to address these changes. This necessitates a shared work philosophy which involves multiple stakeholders. Verification and validation are integral part of any development irrespective of product, process, or services. Also, every industry has a regulatory compliance to adhere too. But the extent of complexity and the level of dependencies or interactions between modules as well as stakeholders involved, creates slippage at some or other level.
Nowadays the industries are also driven by reuse for cost effectiveness. Though it marks the significant improvement in the capability to compete, compatibility is a key measure to a successful product or service launch and sustainability. In many cases, there is a propagation and ripple effect of an issue at unit level to the product level and this induces safety concerns at times and necessitates massive recalls.
This paper discusses on the major concerns industries face due to recalls. It also details on the current methods adopted towards recall handling and highlights the key challenges associated with the recall with respect to all the stakeholders involved. It discusses on an Artificial Intelligence based strategy for automation of product recall management process.
This paper presents a different facet for product recall management that employs Artificial Intelligence technique and brings out the efficiency and benefits achieved by the proposed strategy.
Meta TagsDetails
DOI
https://doi.org/10.4271/2023-01-0867
Pages
11
Citation
Krishnamoorthy, B., "Synergizing Artificial Intelligence with Product Recall Management Process," SAE Technical Paper 2023-01-0867, 2023, https://doi.org/10.4271/2023-01-0867.
Additional Details
Publisher
Published
Apr 11, 2023
Product Code
2023-01-0867
Content Type
Technical Paper
Language
English