Leveraging data and experience with AI

For 35 years, EDELTAMP has embodied excellence in high value-added thermoplastic injection molding. The company has built up an invaluable technical memory, thanks to its expertise in design, its mastery of the properties and behavioral laws of plastic materials, and its know-how in mold manufacturing.

Today, theEDELTAMP is to take this rich experience a step further by integrating Artificial Intelligence (AI) to accelerate innovation on behalf of its customers.

A tenfold increase in technical memory

Every project realized by EDELTAMP over the decades constitutes a unique source of data: material compositions, injection parameters, mold geometries, observed thermal and mechanical behaviors, not to mention the quality results of the parts produced.

By structuring, historizing and modeling all this data from all departments - purchasing, production, quality, logistics, management - the teams atEDELTAMP teams will soon be able to obtain a global vision of the lifecycle of an item and its mold.

In addition, the synthesis of experimental designs for raw materials, by cross-referencing data from all parts historically produced with these materials, in order to assess their costs and their impact on the development of articles, will give its full measure.

The correlation of input parameters (material composition, temperatures, pressures, injection speeds) with output results (part quality, defect rate, mechanical strength) will pave the way for precise, ongoing process optimization.

AI will thus identify the links between production parameters and final part characteristics, detecting the optimum combinations to maximize quality and minimize defects.

Optimizing intangible assets

One of the pillars ofEDELTAMP expertise lies in our teams' perfect understanding of the physico-chemical properties of thermoplastics: rheology, viscosity, crystallization kinetics, and behavior under mechanical and thermal stress.

TheEDELTAMP project is to revisit the way thermoplastic materials are selected and combined, by simulating polymer behavior according to precise constraints.

Using this production knowledge base, artificial intelligence will fine-tune injection machine settings: mold temperature, injection speed and pressure, cooling time, etc. In real time, it will analyze sensor data to dynamically adjust these parameters, with a view to reducing cycle times and reject rates for manufactured parts.

Enhanced intelligence

Innovation doesn't stop here. EDELTAMP traditionally relies on the empirical approach and experience of its engineers.

From now on, algorithms will assist the design office by generating predictive models capable of anticipating the thermal deformation of molds, the distribution of material flows, and potential stress zones.

This approach will make it possible to design higher-performance molds by exploiting complex geometries that are more difficult to imagine without these digital tools.

A predictive guarantee

Thanks to AI, equipment maintenance will also move from a curative logic to a predictive strategy. Sensors integrated into injection molding machines and molds, which continuously collect data on vibration, temperature and pressure, will be analyzed to detect the first signs of degradation and trigger intervention before a breakdown occurs.

Responsible, sustainable innovation

At EDELTAMPbetting on AI doesn't mean denying our values. The company is taking a responsible approach to this transformation, ensuring that algorithms are transparent, sensitive data is secure and artificial intelligence is used ethically.

By leveraging its 35 years of experience and enriching it with the power of algorithms, EDELTAMP doesn't just optimize production: it paves the way for a new generation of thermoplastics and industrial processes.

A bold way to write the future... while remaining faithful to its technical and human heritage.

With AI, EDELTAMP is more than ever a driver of innovation and future value creation for its customers.

(AI) Artificial Intelligence relies on statistical and probabilistic principles to learn and predict outcomes. By analyzing vast data sets, it identifies hidden patterns and relationships, which enable predictions to be made on new information, relying on algorithms that adjust their models according to past data and errors. So, with the help of AI, it becomes possible to make informed decisions, quickly....

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