Advancing Precision Manufacturing with IoT-Driven Quality Control

Industry:
about paysafe

A prominent global manufacturer specializing in precision components for the aerospace and automotive industries, this client is dedicated to pushing the boundaries of manufacturing excellence. With a reputation for quality and innovation, they faced the challenge of maintaining unparalleled precision and efficiency in production amidst growing demand and complex engineering specifications.

Reviewed on
5/5
98
%

Precision Rate in Production

40
%

Reduction in Waste

95
+

Automated Quality Assurance Processes

30
%

Increased Production Capacity

The Challenge

In the fast-paced and precision-critical manufacturing sectors of aerospace and automotive, even the slightest deviations can have significant repercussions. Our client was contending with the dual pressures of escalating demand and the imperative for flawless quality.

Traditional quality control methods, reliant on manual inspections and reactive adjustments, were no longer viable for meeting the high-volume, high-precision requirements.

The client needed a proactive approach that could preemptively identify and correct discrepancies in real-time, minimize waste, and streamline production processes without compromising on quality.

What did
Entiko do

Entiko deployed a comprehensive IoT-based solution tailored to elevate the client’s manufacturing operations to new heights of precision and efficiency. We initiated the project by outfitting the production lines with high-precision IoT sensors capable of detecting the minutest anomalies in product dimensions and material integrity.

These sensors provided continuous data streams to an AI-driven analytics platform, which analyzed the data in real-time to identify trends, predict potential faults, and prescribe corrective actions before defects occurred. To further enhance quality control, we integrated automated inspection systems using advanced imaging and robotics, enabling round-the-clock monitoring and assessment of production quality.

Our system facilitated immediate feedback loops, allowing for the dynamic adjustment of machinery and processes to maintain optimal production conditions. Additionally, we developed a custom dashboard that gave the client real-time insights into production metrics, quality control outcomes, and efficiency gains, empowering them to make informed decisions swiftly.

The Results

The technology that we use to support Paysafe

High-Precision IoT Sensors
TypeScript
Node.JS
Artificial Intelligence and Machine Learning
Swift
Java
Objective-C
RxJava

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