AQ-ZirkonDent-HFB Automated quality control for rare earth stabilised zirconium dioxide dental implants with high strength and fracture toughness

Quality control at Moje Keramik-Implantate GmbH & Co. KG is currently carried out manually and is divided into several steps. First, the implants are stained using UV-fluorescent penetrant and inspected for defects. Implants without any abnormalities are then washed. Second, a HIP process (hot isostatic pressing) is used to improve the mechanical properties of the implants and remove any remaining penetrant residues. Finally, a visual quality check is carried out using the dual control principle. Each implant is checked by two employees in a 100% inspection. This is a time-consuming and therefore cost-intensive process. In addition, production is limited by the number of parts that can be inspected per day. Quality control therefore has a significant impact on the company's turnover and profits.

Objectives

The project therefore aims to develop an automated test bench for quality control. To this end, research is being conducted into a handling system and a method for image-based defect detection. The handling system rotates the implants in front of a camera system. The images are automatically evaluated and defects detected. Implants without defects are considered good parts. In a first step, the test bench will eliminate the need for double checking. If the system proves to be highly robust, the inspection can also be 100% automated in the long term. Another advantage is that the quality control is documented by the images taken. This greatly simplifies traceability in the event of complaints.

Benefits

• Increases the level of automation
• Reduces the workload on staff
• Leads to increased throughput and thus increased production capacity
• Reduces costs
• Reduces complaints
• Enables transparent documentation and traceability

Approach

The project will first develop a camera and lighting system that is capable to capture defects on images. This camera and lighting system will then be combined with the handling system to enable 100% coverage of the implant. Subsequently, a method will be researched to automatically detect defects in the images. The handling system will then sort out implants with defects. Furthermore, a user interface is planned that can be used to parameterise the test bench and visualise the system's decisions.  

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Contact Paul Krombach via email at krombach@ifw.uni.hannover.de or by phone at +49 511 762 18311.