AITOcSwedish national consortium
The Swedish consortium
The Swedish consortium is composed of a mix of partners from universities, research institutes, SMEs, suppliers and vendors, and OEMs, supporting the overall value chain for manufacturing engineering in the automotive and similar type of industries.
The Volvo Group
The Volvo Group is one of the world’s leading manufacturers of trucks, buses, construction equipment, drive systems for marine and industrial applications, and services. In the AIToC project, Volvo will focus on developing initial requirements and provide inputs to concepts and solutions, as well as relevant data for use cases to demonstrate how a future efficient manufacturing engineering tool chain can be applied.
University of Technology Chalmers
Chalmers, within the automation research area, conducts a wide range of research in industrial methods and tools. The focus is mainly on planning, optimization, supervision and control of production systems, especially discrete event and logical systems, where complexity and information integration are two main challenges. Artificial Intelligence is becoming important and is highly relevant in this application area. Through Chalmers AI Research Center (CHAIR) a broad competence and experience is available and will be utilized in the AIToC project.
Fraunhofer-Chalmers Research Centre for Industrial Mathematics
The Fraunhofer-Chalmers Research Centre for Industrial Mathematics (FCC) is offering contract research, services, algorithms and software based on advanced mathematics within Modeling, Simulation and Optimization (MSO). In AIToC, FCC will contribute with research and development within modelling and simulation related to layout planning and optimization.
AFRY (formerly known as ÅF) is an engineering and consulting company with assignments in the energy, industrial and infrastructure sectors. During the last few years, the company has put significant efforts to integrate engineering methods and functionality of simulation tools, especially to achieve full virtual commissioning. Their experience and knowledge will be important for the integration of tools in AIToC, to realize the use cases and demonstrations.
ABB is a word-leading manufacturer of industrial robots and robot systems and can provide state of the art automation knowledge to the project, especially virtual models that represents the true behavior of equipment’s in a production system. With the combination of Artificial Intelligence methods to fine tune models with data, and deep knowledge of the equipment and their control systems, they have capabilities to make optimized, trained and programmed virtual devices.
Algoryx Simulation is a leading provider of software and services for visual and interactive physics-based simulation. Algoryx have designed and developed a next generation physics engine with fidelity, performance, functionality and extensibility that surpasses all comparable solutions on the market. Their contribution will be particularly important for the creation of the models and simulations of processes and resources.
Solme AB develops software tools and provides services for industrial engineering. This includes methods and tools for effective analysis of manual assembly processes, by combining video analysis with time and motion studies, visualization and optimization of line balancing from the aspects of time, ergonomic stress, material access and operator work zone. Solme AB will contribute with competence and tools for data acquisitions and how to make use of the AIToC approach for process and operations planning to generate information and visualizations that will be used in production.
Univrses is a fast-growing start-up company with a highly qualified team of scientists and engineers within computer vision and machine learning as key competence. One key area is 3D computer vision creating and delivering technologies for 3D Positioning, 3D Mapping, 3D Localization, Spatial Deep Learning and Sensor Fusion. Their competence and products can be used in combination with physically based methods to create more complete and realistic system models for both geometry and function.