Our Technology

In situ distributed property monitoring combined with data mining and predictive modeling for dynamic processes optimization and preventive control
Predictive Modeling: AccuStrata’s technology platform is based on continuous data mining from multiple monitoring sensors using multivariate analysis for dynamic physical, phenomenological, and statistical modeling of the ongoing processes and phenomena, as well as forecasting of the outcome.

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Predictive modeling is already being implemented for preventive control of surface modification processes, biological and environmental applications and others. However, it can go far beyond product manufacturing. It is used for optimization of energy distribution and consumption (smart grid), broad public hazard awareness networks, autonomous vehicle and aircraft operation, intelligence and crime prevention, prediction of consumer sentiments, etc. 

Manufacturing Efficiencies: Our technology has the potential to make a significant impact on the new generation advanced thin film  product manufacturing. By reducing process tuning time, eliminating product rejects and improving product performance AccuStrata’s solution reduces product cost, making the  manufacturing processes cost effective and leading to the waste-free product manufacturing needed for the 21st century economy.

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The next-generation, advanced lean manufacturing aims to reduce usage and completely eliminate waste of material, energy, and labor by introducing predictive and adaptive process control based on in situ multi-spot process monitoring, data fusion, and advanced modeling techniques such as machine learning and forecasting. Manufacturing processes can be guided similarly to the aircraft on-board autopilot systems and achieve close to 100% manufacturing yield.

It can be stated that the predictive modeling and dynamic process control is the technology of the future.

Thin Film Processing: Our intelligent, real-time multi-spot optical monitoring of surface properties, predictive modeling, and know-how are used to adaptively optimize and control physical properties of thin films such as thickness, uniformity, homogeneity, composition, color, texturing, and patterning as layers of material are being formed and removed from the surface of the product.

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The new generation of thin-film deposition technologies struggle with problems resulting from the lack of adequate process control capability. Insufficient process control leads to high costs of process tuning and scale-up plus increased product cost due to the inherent waste of energy, material, labor, and intellectual effort. The implementation of advanced process control is especially challenging for extremely thin layers (below 5-10 nanometers) and very thick (over 25 microns) multilayer coatings, frequently used in the nanotechnology, as well as compound thin films where the chemical composition is critical for the film properties. Additionally, thin-film deposition processes typically tend to deviate from their optimal conditions, leading to deviation from the intended product specification.

Atomic Absorption Spectroscopy (AAS): A new development in this industry, in situ AAS promises to resolve most of the existing process control problems and become a viable candidate for the gradual replacement of traditional process control methods used today. By monitoring and controlling the element concentration in the vicinity of the product surface AAS allows control of the individual components that form the thin film. This unique technique is able to control extremely thin films (thickness < 10 angstrom), extremely thick multilayer coatings (thickness > 50 microns), compound semiconductors and metal alloys, patterned thin films and complex structured nanolayers.

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Modern process control is predominantly “after-the-fact”, based on “snapshot” in-line metrology and run-to-run control. When used, the in situ process control, typically based on quartz crystal photometric and/or electron diffraction monitoring, is unable to provide the needed deposition rate accuracy and adequate preventive control for many of the new generation of thin-film-based products. AAS is a promising method for accurately determining the deposition rate and film composition by correlating the atomic flux density of the deposited material in the plasma to the attained film thickness and film composition on the substrate.

Biotechnology: Our real-time broadband UV-VIS-NIR monitoring and predictive modeling know-how are applied in adaptive control and process optimization in bioreactors, monitoring for environmental contamination of ballast waters, and identification of hazards in the food supply chain needed for creating advanced awareness system.