SENTIENT Case Study

Hardware manufacturer reduces
factory downtime

Customer

Industrial tool & household hardware manufacturer

Industry

Hardware Manufacturing

Function

Maintenance & Service

Problem

Factory loses 5% to 25% of its manufacturing capacity due to downtime. Traditional preventive maintenance processes require machine repairs at regular time intervals or after a set amount of usage, and leads to equipment failure. This in turn, has resulted in idle workers, lost revenues, and increase in scrap rates. Sometimes, traditional preventive maintenance results in good parts that still have significant working life being replaced.

Solution

Data from IoT sensors embedded in equipment, data from manufacturing operations, and environmental data are used by an AI tool for predictive maintenance. The tool predicts which component should be replaced before breakdown. 

AI models can look for patterns in data that indicate failure modes for specific components or generate more accurate predictions of the lifespan for a component given environmental conditions. When specific failure signals are observed, or component aging criteria are met, the components can then be replaced during scheduled maintenance windows. 

Result

AI based predictive maintenance generates a 10% reduction in annual maintenance costs, up to a 25% downtime reduction and a 25% reduction in inspections costs.

More Use Cases

For the Manufacturing Industry

Automotive

Automotive service provider uses historical repair order data to improve customer service

Food

Fruit producer ensures optimal quality of products during transportation and delivery

Electrical

Electrical equipment manufacturer saves $9.32 Million in Supply Chain Management

2263, KAUST Tech Park Headquarters, 

4700 KAUST, Thuwal, Saudi Arabia 22935

Contact

Call : +966 54 312 3734

Email : info@unitx.tech

© Copyright 2020   |   UnitX Technologies  |   All Rights Reserved 

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