The Use of Artificial Intelligence in Manufacturing

Every year, industrial organizations are increasingly exploring the use of artificial intelligence in manufacturing processes. Artificial intelligence is finding unique use cases in almost every aspect of manufacturing, and its adoption is expected to grow exponentially over the next decade.

USAGE OF ARTIFICIAL INTELLIGENCE FOR QUALITY CONTROL

Artificial intelligence enhances quality control through several key avenues. It provides automated product inspections, analysis of visual datasets, and real-time detection of quality defects. For instance, machine learning algorithms can instantly identify deviations from quality specifications. Predictive maintenance systems use artificial intelligence to detect potential equipment failures before they occur. Such applications reduce human error and enhance compliance with quality standards. In our project with YPS Automotive, we developed a system using artificial intelligence and image processing technologies to detect defects that have not yet occurred and to ensure quality control. Thanks to this system, quality control was successfully conducted without exceeding the 4-second cycle time of production, thereby achieving efficiency in quality control.

USAGE OF ARTIFICIAL INTELLIGENCE IN PRODUCT DEVELOPMENT AND ENGINEERING

Product development and engineering teams often utilize artificial intelligence to expedite processes such as design, testing, and prototype optimization.

Manufacturers can accelerate product development cycles by using AI-supported design tools that assess real-world applicability while creating innovative designs. Engineers and developers can also employ machine learning applications to analyze prototyped and existing products for defects and propose solutions for improvements.

APPLICATIONS OF ARTIFICIAL INTELLIGENCE IN MAINTENANCE

One of the most popular applications of artificial intelligence in manufacturing is predictive maintenance. Predictive maintenance takes a proactive approach to equipment maintenance by collecting machine data using data analytics and interpreting the "story" of the data through machine learning.

This process, known as predictive analytics, allows maintenance teams to identify patterns and irregularities that could lead to mechanical failures. This helps manufacturers take action before costly breakdowns occur.

USAGE OF ARTIFICIAL INTELLIGENCE IN SUPPLY CHAIN MANAGEMENT

Artificial intelligence is transforming supply chain management for manufacturers. Manufacturers can track shipments in real-time, forecast demand fluctuations, overcome disruptions, and maintain stable inventory levels. The advantages of using artificial intelligence in supply chain management were evident in our project with Turkey's leading automotive manufacturer, TOFAŞ. The system we implemented enabled a gain of 16 minutes of labor per vehicle, resulting in a significant increase in supply process efficiency.