Predictive Quality

Would you like to learn how you can minimize high costs due to waste and rework? We will show you how to use predictive quality in your production!

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Companies are constantly under pressure to increase their profitability. This leads to the need to increase sales or reduce costs This happens year after year. In times of COVID, this is extremely difficult, as there is enormous uncertainty among customers, and investments are being held back in most industries at the moment.

The first impulse then usually goes in the direction of purchasing, with companies trying to extract the lowest prices from suppliers. This then puts suppliers in an equally difficult situation. In case of doubt, long maintained relationships suffer under this pressure. At the same time, 20% of the manufactured goods are scrapped in production or must be reworked.

Today, with available technology, we can minimize waste and rework in companies through predictive quality methods.

Advantages of Predictive Quality

  • Reduced labor, both for rework and repetitive quality assurance
  • Reduced material waste due to production processes that continue despite defective material
  • Significantly increased planning reliability, as the number of unscheduled rework operations is reduced
  • Lower lead times
  • More reliable, efficient production
  • Increased customer satisfaction
  • Positive impact on the sustainability of a company

Fields of application of Predictive Quality

Conservation of resources through exact problem diagnosis

Whether in cargo handling logistics, transportation, the automotive industry or freight traffic - the potential applications for drones and cameras for intelligent image recognition are manifold. For example, the direct detection of errors or contamination in conjunction with geolocation can be used to deploy employees and materials in a more targeted and resource-saving manner.

Innovation push in the agricultural sector

The use of intelligent image analysis technology makes it possible, for example, to control plant growth using drones or to ensure optimized, sustainable fertilizer use. Artificial intelligence supports early defect detection, ensures targeted, nature-friendly pest control, optimizes irrigation processes and ensures more reliable harvest & yield forecasts and better harvest results.

 

Quality analysis in the industry

Monitored scrap prediction through object detection in the area of parts manufacturing optimizes production processes and enables the automation of complex quality processes through intelligent algorithms. Fewer defects and returns thanks to intelligent image recognition and processing result in higher profit margins.

"PREDICTIVE QUALITY ENABLES QUALITY ANALYSIS TO MOVE FORWARD WHERE HUMANS REACH THEIR LIMITS."

- björn heinen, Chapter lead data science, inform datalab

How we work - Our Predictive Quality methodology

  • Scrap Prediction

  • Scrap Detection

  • Root Cause Analysis

Scrap Prediction – predictive

The goal of scrap prediction is to predict defects and scrap before they occur. Input is mostly sensor and machine data, other information such as material or even supplier information is also considered.

Our workshops

use case ideation workshop

In our Use Case Ideation Workshop, we take a closer look at your challenges & data. Our data experts make an initial inventory of what data is already available in your company, where and in what quality. Based on this analysis, we work with you to develop the first possible use cases for your department or company that will quickly create added value.

data quality health check

Data quality is the basis for effective data use. In our Data Quality Health Check, we take stock of your current data quality and provide you with concrete recommendations for action to improve it.

Crash Course Artificial Intelligence

This course is suitable for the qualification of employees and managers, as well as doctoral students and students who want to expand their knowledge around the topic of artificial intelligence. After the course, the participants are able to classify first use cases themselves and have developed an understanding of the basic concepts of AI.

Artificial intelligence for decision makers

This course is suitable for the qualification of decision makers, innovators and executives who want to expand their knowledge around the topic of artificial intelligence and its influence in business. After the course, participants will be able to classify initial use cases themselves and will have developed an understanding of the basic concepts of AI. Furthermore, they will be able to estimate the effort of projects and assign them to their departments.

Artificial intelligence - introduction, possibilities and limits

This course is suitable for the qualification of employees and managers, as well as doctoral students and students who want to expand their knowledge around the topic of artificial intelligence. After the course, the participants are able to classify first use cases themselves and have developed an understanding of the basic concepts of AI.

Maren Korth Inform Datalab
maren korth

Sales

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Machine learning gives indication of soiling and damage in new vehicle logistics

One of the largest German car manufacturers was faced with the problem that damage regularly occurs during the transport of new vehicles. These must be detected as quickly as possible and repaired before delivery. Current prevention measures are not appropriate, especially with regard to sustainability, and are therefore to be abolished.

Solution

Together with our data scientists, a solution was developed in which drones regularly fly over the vehicles in an automated manner to examine and document the surface with high-resolution image material. Using machine learning methods, these images are examined for damage and contamination and appropriate measures are initiated. The autonomous drone flights are controlled by GPS waypoints and the images are recognized and processed using state-of-the-art object recognition.

Highlights

  • Robust detection of damage and contamination with over 90% accuracy
  • Reduction of cost-intensive repainting and personnel deployment
  • Well-trained specialist personnel are thus once again available for higher-value tasks
  • Total costs for any necessary vehicle repairs are reduced

Data Science

Our Data Scientists delve into the depths of your data and uncover new, business-relevant information. With the help of artificial intelligence and our understanding of company-specific business processes, we transform your data into added value and uncover new opportunities and potential for your company.