What AI could do for your Orthodontic Laboratory
AI is revolutionizing business. In this article, we explore what it could soon change in the way orthodontic laboratories operate, and how it will impact the entire digital treatment process, improve planning and organizations, create considerable time savings and productivity gains.
Please note: Although this is a prospective article with some features not yet operational, they will undoubtedly be available so very soon. Stay tuned so you don’t miss this opportunity for your laboratory!
1. Automated order collection
Today, retrieving intra-oral scans is a tedious task. Many laboratories have to manually connect to proprietary platformsseveral times a day to download the files. Some practitioners still send their scans by FTP or e-mailwhich adds complexity. Scanner manufacturers sometimes offer APIS (Application Programming Interfaces) to automate data integration, but these APIs are not always accessible to all laboratories, although software is beginning to emerge to solve this problem.
Another solution should quickly solve this problem: AI agents. They can interpret a user request and then act autonomously on the user’s workstation. It allows us be able to automate all kinds of interactions between software or with web sites without using an API. AI agents will make it possible to automate order collection.
2. Interpreting and structuring commands
Once the scans have been retrieved, we need to understand the practitioner’s order. Given that today’s cloud-based scanning platforms are not designed for orthodontics,practitioners generally provide their instructions in an unstructured comment field, and the information cannot be directly integrated into a database.
This forces laboratories to to manually read each message and re-enter orders in their information systems, or even on paper.This is a major waste of time and a source of errors. Thanks to AI and automatic natural language processing (NLP)orders can be automatically interpreted :
– Identification of type of device to be manufactured
– Extraction of requested delivery date
– Recognition of the practitioner and related information
– Detection of order peculiarities
All this information is then structured and automatically integrated into the laboratory’s database, ready to be used for the rest of the treatments.
3. Order verification and validation
The AI can then ensure that all the elements required for manufacturing are present before launching production. For example, it could check:
– Scans are complete and usable.
– That all the necessary information has been entered.
– Or even that the laboratory has the resources and time available to produce the order.
The AI does not make any decisions at this level, but it does immediately alerts you to any problems allowing you to react quickly and avoid delays.
4. CAD realization
Once the order has been validated, the digital model or orthosis must be created in CAD. This can be done using assisted CAD software requiring the intervention of a user or automatically with specialized AI software. Here, AI enables :
– Faster, more cost-effective modeling
– Model standardization to ensure consistent quality
– Improved laboratory responsiveness
Above all, it frees up the user’s time to perform less repetitive, higher value-added tasks.
5. 3D printing optimization
3D printing is a crucial step in the process. Efficiently placing models on the printing plate allows speed up production with:
– Optimized printing times
– Improved utilization rate of 3D printers
– Improved laboratory responsiveness
It also ensuresgrouping of arcadesof the same order on a tray, or to prepare grouped shipments for the same practice.
6. Production planning
Once the models have been printed, AI can help to better prosthesis production according to :
– Some requests from practitioners
– team team constraints and available resources
– From the existing planning
For example, it can learn to group together the production of certain prostheses in order to optimize logistics. In the case of urgent orders or early delivery requests, an AI system could better production planning.
It can also detect complex or high-risk ordersIt can also detect complex or high-risk orders, anticipating potential problems and optimizing workloads.
7. Outsourcing automation
Some laboratories subcontract certain manufacturing stepssuch as the machining of certain parts. Thanks to a API or AI agentagent, the laboratory can automatically :
– Order an external service without manual intervention
– Monitor the progress in real time
This enables greater fluidity and optimized resource management.
8. Optimizing logistics and shipping
AI will also facilitate delivery managementby :
– Grouping shipments from the same practitioner to limit costs
– Automatic generation of labels and shipping documents
– Optimizes delivery rounds
Thanks to this intelligent management, the laboratory gains in logistical efficiency and optimizes costs.
9. Billing and accounting
Data on digitally-managed orders is already available in the laboratory’s information system. We could therefore avoid double entries by automatically retrieving this information to generate invoices and then importing these invoices into the accounting system. The API link has long been an existing solution, but it requires IT development between applications, which is holding back its widespread use.
Here too AI agents agents will offer a much simpler alternative to implement, and should become widespread for intelligent copying between applications in place of the user. The laboratory gains in efficiency, eliminates repetitive tasks with little added value and optimizes costs.
10. Real-time communication with practitioners
AI makes it possible to streamline the exchange of information between the laboratory and practitioners.
Thanks to its natural language processing capabilities, and by being connected to the laboratory’s information system, the AI can, among other things:
– Provide information on the progress of orders in the form of e-mail, chat or voice integration
– answer practitioners’ questions in real time
– Automatically request clarification in the event of missing information or doubt.
A practitioner could simply ask his voice assistant about the status of an order and receive an instant responsewithout having to call or send an e-mail. Here, AI provides better service to the practitioner while while minimizing the workload laboratory’s workload in handling their inquiries.
11. Continuous analysis and performance improvement
Provided that information is available at all stages of the production process, AI enables real-time analysis of laboratory activity. It can :
– Identify production bottlenecks
– Suggest organizational improvements
– Analyze the profitability of various services
– Detect trends to adjust strategy
Thanks to this information, the laboratory manager benefits from a clear and objective of the business and can make make strategic decisions based on accurate data.
Conclusion: An inevitable transformation for all laboratories
Artificial intelligence is revolutionizing revolutionizing orthodontic laboratory workflow. Automating repetitive tasks, optimizing order management, intelligent planning and better communication with practitioners the benefits are immense. In the next few years, all laboratories will need to adopt these technologies to remain competitive.. Those who do it today get a head start on the market. The future of the orthodontic laboratory is automated, connected and intelligent. AI is no longer an optionit is an essential strategic lever to guarantee performance and profitability.
Innovative solutions are emerging to support this transformation. At AI4Dental, we are preparing the launch of EasyFlow, a solution that will integrate automated order collection and a seamless link with EasyModel to speed up production.
🚀 Stay tuned, the future of orthodontic laboratories is being written now!
