EUROPEAN PROJECTS
Adaptive Scheduling of Manufacturing Processes with Artificial Intelligence Support
Partner
AT Digital, s. r. o.
AT Digital, s. r. o. Based in Žilina, the company is engaged in research and experimental development in the fields of natural and technical sciences. It is developing its own system for digital design, virtual prototyping, and the optimization of manufacturing systems, which utilizes digital enterprise technologies—object digitization, dynamic simulation, mathematical optimization, and digital twins. The company brings to the project its expertise in industrial engineering, production planning, and management, as well as its customers’ preliminary interest in testing the system even during its development.
Project Title: Adaptive Scheduling of Manufacturing Processes Using Artificial Intelligence
Project Code: 401101D205
Call for Proposals: PSK-MH-010-2024-DV-EFRR – Call for Proposals Aimed at Supporting Industrial Research and Experimental Development Projects
Program: Slovakia Program – Priority 1P1 Science, Research, and Innovation; Specific Objective RSO1.1 (ERDF)
Total eligible expenses: €1,083,592.14
Amount of NFP (EU and state budget funds): €744,668.28
Implementation period: July 2026 – June 2028 (24 months)
Recipient: exe, a.s.
Partner: AT Digital, s. r. o.
Location: Žilina Region, Žilina District, City of Žilina
Recipient
exe, a.s. is a Slovak technology company operating in the fields of artificial intelligence, cloud computing and infrastructure, cybersecurity, digitization, and virtual solutions. Part of its business model is based on the commercialization of research and development results, giving it many years of experience in preparing and managing research, development, and innovation projects. For the purposes of the project, it has IT infrastructure at its disposal, including servers, data storage, and network components; licenses for software tools for research, testing, simulations, and cloud services; as well as cybersecurity capabilities.
Partner
AT Digital, s. r. o.
Description
The actual manufacturing process is accompanied by frequent random deviations and unpredictable events that require flexibility. Traditional scheduling methods, however, focus on optimization under static conditions, which is insufficient for modern, flexible manufacturing environments. As a result, companies—especially small and medium-sized ones—face inefficient planning, low capacity utilization, limited predictive capabilities, and insufficient support for digitalization.
Available ERP systems with MRP modules and APS systems are generally complex, expensive, and lack dynamic modeling capabilities. The market lacks simple, modular solutions that would enable small and medium-sized enterprises to create plans capable of quickly adapting to new conditions. This project addresses this gap by researching algorithms and developing an innovative tool for adaptive production process planning that integrates simulation (including a digital twin), optimization, and artificial intelligence into a single modular unit, enables dynamic planning based on real-time data, and integrates easily with existing systems (ERP, MES, APS) via standard protocols.
Goal
The main objective of the project is to conduct research and development on an innovative, AI-supported adaptive scheduling system for manufacturing processes that will improve production planning, particularly in small and medium-sized enterprises. Through industrial research and experimental development activities, the project increases the level of innovation and competitiveness of exe, a.s. and AT Digital, s. r. o. The solution is divided into five interconnected work packages—ranging from industrial research on the state of the art, through the design of the structure of a comprehensive system and modules for capacity prediction and scaling as well as for adaptive production scheduling itself, to the integration and verification of the system under laboratory conditions and in industrial practice.
Project Results
The project will result in a final product—a comprehensive system for adaptive scheduling of manufacturing processes based on predictive algorithms and neural networks, verified and ready for application in industrial practice. The system integrates digital twin, artificial intelligence, simulation, and optimization technologies and is adaptable to various processes and market segments; it primarily targets small and medium-sized enterprises in the engineering, automotive, and food industries.
The expected benefits include increased efficiency and productivity through better utilization of production resources and improved on-time delivery reliability, time and cost savings through more accurate planning and reduced waste, a positive impact on employment resulting from more flexible and reliable production, improvement of human resources through the transfer of knowledge into practice, as well as environmental protection through reduced consumption of production resources. The project contributes to the fulfillment of the objectives of the Slovakia Program—Policy Objective 1 “A More Competitive and Smarter Europe,” Priority 1P1 Science, Research, and Innovation, and Specific Objective RSO1.1 Development and Expansion of Research and Innovation Capacities and the Use of Advanced Technologies (ERDF).