TRUST-SOS - Trusted Site Optimisation Solutions

The TRUST-SOS project aimed to optimize off-road transport operations in quarries and similar environments by developing a digitalized, model-based decision support system. Traditional off-road operations relied heavily on experience-based decision-making, often involving a few skilled individuals to make critical operational decisions. This system creates inefficiencies and makes it challenging to manage the complexities of dynamic, large-scale work sites. The TRUST-SOS project sought to address these challenges by transitioning from experience-based decision-making to data driven, model-based approaches, creating a more reliable and efficient system for quarry site management. The project integrated site modelling, machine and site simulation, and optimisation techniques to develop digitalized services for off-road transport applications. By leveraging data and advanced analytics, TRUST-SOS created predictive tools and simulations that allows for the optimisation of site operations, resource utilization, and environmental impact. The system accounts for various site factors, including operator skill, asset performance, and terrain conditions, to enable simulation and decision-making that improves productivity, reduces fuel consumption, and minimizes environmental impact. A key innovation of the TRUST-SOS project was the creation of modular vehicle and mobility models. These models support decision-making for the entire site, including machine performance, operator skill, and material interaction. They enable performance monitoring of vehicles and machines, optimisation of the operating parameters, and facilitates planning and configuration of new construction sites. These models also allowed for the optimisation of construction site performance, considering various operating conditions and machine types to maximize efficiency and minimize costs and environmental impact. In addition to the technical development, the project contributed to the development of business models and digitalized services that align with customer needs and operational goals. These services were designed to offer value-added functionalities, such as predictive maintenance, performance tracking, and operational optimisation. By transitioning from experience-based processes to model-based, data-driven services, TRUST-SOS not only optimized operations but also introduced new revenue streams and business opportunities for stakeholders in the off-road transport industry. Throughout the project, there was a strong focus on sustainability and energy efficiency, aligning with the objectives of the Vinnova FFI sub-program to promote the development and market introduction of fossil-free work machines. The TRUST-SOS project’s digitalized services contribute to reducing climate emissions by optimizing machine usage, enabling the transition towards electrification, and supporting the adoption of electric machines. Additionally, by improving system efficiency and supporting automation, the project helped reduce the reliance on fossil fuels, paving the way for more sustainable and efficient quarry operations. The project focused on digital servitisation, developing business models that could transform traditional operations into service-oriented solutions. This approach allows for continuous customer engagement through digital services, such as performance optimisation and predictive maintenance. By exploring data-driven service offerings, TRUST-SOS helped create a flexible, scalable approach to managing off-road transport operations, ensuring that stakeholders can adapt to evolving market needs. The results of the TRUST-SOS project have the potential to significantly impact the off-road transport industries by optimizing site management and machine performance while reducing environmental impact. The project demonstrated how digitalization, simulation, and advanced analytics could be applied to traditional industries to create more sustainable, efficient, and cost-effective operations. With its focus on sustainability, automation, and digital servitisation, the TRUST-SOS project contributed to the broader goal of developing fossil-free work machines, positioning Sweden as a leader in the transition to more sustainable industrial practices. Continued research and development following the project could explore the development of more advanced machine learning models and greater use of artificial intelligence to enhance the decision support system’s predictive capabilities. In addition, projects could drive further innovation in electric machinery for off-road applications, enabling the industry to transition more rapidly to fossil free operations.