Inspekto Case Studies How an Autonomous Machine Vision (AMV) System Increased Accuracy and Cut Waste

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	How an Autonomous Machine Vision (AMV) System Increased Accuracy and Cut Waste Inspekto

How an Autonomous Machine Vision (AMV) System Increased Accuracy and Cut Waste

Inspekto

Technology Category	Analytics & Modeling - Computer Vision Software
Applicable Industries	Consumer Goods
Applicable Functions	Discrete Manufacturing
Use Cases	Computer Vision
Services	System Integration
Challenge	QA automation is a cost-effective solution for manufacturers, as it saves time and money while reducing the risk of defective products. However, traditional QA methods are not sufficient for meeting the rigorous standards of Industry 4.0, and traditional machine vision solutions can be expensive and difficult to implement. BSH, a manufacturer of home appliances, faced this challenge and sought to improve the accuracy and efficiency of their batch inspection process without incurring high costs. They partnered with Inspekto to address the issue and reduce detection time of component defects at one of their oven manufacturing plants in Germany. Read More
About Customer	BSH Home Appliance Group is a global manufacturer of household appliances. They are known for producing a variety of products including ovens, refrigerators, dishwashers, and washing machines. The company was founded in Germany and currently operates in over 50 countries worldwide. BSH has been in operation for more than 100 years, they have an emphasis on innovation and technology, providing products that meet the changing needs of their customers. They also have a reputation for manufacturing excellence and focus on sustainability. Read More
Customer Name	BSH Home Appliance Group Read More
Solution	Inspekto has developed a new approach to industrial QA called Autonomous Machine Vision (AMV) that combines the capabilities of human vision with the reliability and repeatability of industrial machine vision. AMV systems are pre-trained for a wide range of use cases, making them easy to install and deploy independently in a short amount of time. The system uses artificial intelligence (AI) to automatically adjust image capturing parameters, such as distance, lighting, and exposure, allowing users to simply present the system with 20-30 sample items for it to learn and flag any deviations from the standards. This user-friendly approach is made possible through Inspekto's proprietary technology, AMV-AI, which combines three AI modules to mimic the human cognitive vision process from start to finish. BSH, a manufacturer of home appliances, was impressed by the user-friendliness and accuracy of the technology, and implemented Inspekto's S70 AMV system at their plant in Traunreut, Germany. Read More Log in to view content
Contents

Technology Category

Analytics & Modeling - Computer Vision Software

Applicable Industries

Consumer Goods

Applicable Functions

Discrete Manufacturing

Use Cases

Computer Vision

Services

System Integration

Challenge

QA automation is a cost-effective solution for manufacturers, as it saves time and money while reducing the risk of defective products. However, traditional QA methods are not sufficient for meeting the rigorous standards of Industry 4.0, and traditional machine vision solutions can be expensive and difficult to implement. BSH, a manufacturer of home appliances, faced this challenge and sought to improve the accuracy and efficiency of their batch inspection process without incurring high costs. They partnered with Inspekto to address the issue and reduce detection time of component defects at one of their oven manufacturing plants in Germany.

About Customer

BSH Home Appliance Group is a global manufacturer of household appliances. They are known for producing a variety of products including ovens, refrigerators, dishwashers, and washing machines. The company was founded in Germany and currently operates in over 50 countries worldwide. BSH has been in operation for more than 100 years, they have an emphasis on innovation and technology, providing products that meet the changing needs of their customers. They also have a reputation for manufacturing excellence and focus on sustainability.

Customer Name

BSH Home Appliance Group

Solution

Inspekto has developed a new approach to industrial QA called Autonomous Machine Vision (AMV) that combines the capabilities of human vision with the reliability and repeatability of industrial machine vision. AMV systems are pre-trained for a wide range of use cases, making them easy to install and deploy independently in a short amount of time. The system uses artificial intelligence (AI) to automatically adjust image capturing parameters, such as distance, lighting, and exposure, allowing users to simply present the system with 20-30 sample items for it to learn and flag any deviations from the standards. This user-friendly approach is made possible through Inspekto's proprietary technology, AMV-AI, which combines three AI modules to mimic the human cognitive vision process from start to finish. BSH, a manufacturer of home appliances, was impressed by the user-friendliness and accuracy of the technology, and implemented Inspekto's S70 AMV system at their plant in Traunreut, Germany.

Impact #1	[Management Effectiveness - Operation] The implementation of Inspekto's technology at BSH's Traunreut plant allowed for a user-friendly, immediately deployable solution without the need for a costly, inflexible bespoke project.
Impact #2	[Product Improvement - Scalability] The INSPEKTO S70 system can be trained quickly, adapt to environmental changes, and inspect multiple products and models simultaneously.

Impact #1

[Management Effectiveness - Operation]

The implementation of Inspekto's technology at BSH's Traunreut plant allowed for a user-friendly, immediately deployable solution without the need for a costly, inflexible bespoke project.

Impact #2

[Product Improvement - Scalability]

The INSPEKTO S70 system can be trained quickly, adapt to environmental changes, and inspect multiple products and models simultaneously.

Benefit #1	An impressive increase in application use cases and a significant reduction in material waste by up to 90%, resulting in cost savings while minimizing the environmental footprint.

Benefit #1

An impressive increase in application use cases and a significant reduction in material waste by up to 90%, resulting in cost savings while minimizing the environmental footprint.

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Overview

How an Autonomous Machine Vision (AMV) System Increased Accuracy and Cut Waste

Operational Impact

Quantitative Benefit