Production and logistics are highly complex due to dependencies among many interacting systems, dynamics, and frequent changes. A consequence is frequent deviations from production plan despite systematic work to increase process stability. The project is aimed at supporting the handling of deviations and re-scheduling of tasks by solutions that automate relevant information flows and processes. The project develops a model framework that identifies and describes needs for support, information and automation, and a methodology that guides companies to specify their needs.
Impact and Results
Competitiveness is expected to increase as result of more automated and efficient handling of deviations within production. The expected impact from implementing such information automation is faster reaction and flexibility to deviations and changes of production plans, as well as reduced propagated effects. The methodology can give companies a good base for future investments that employ technological solutions, thereby increasing automation use. Furthermore, increased automation will give access to relevant information and increase knowledge of events.
Framework and methodology is formed by experiences from case studies in industrial partner companies, which cover different needs and aspects. The intention is to enhance the state-of-art and provide important solutions for increased digitalization and information automation. A crucial part of the project is the knowledge dissemination of solutions to Swedish industry, especially SMEs. The 30-month project is lead by Swerea IVF together with Chalmers Univ. of Techn., Royal Inst. of Techn., Brogren Industries, Federal-Mogul, Volvo Penta, Tyri Lights, and Marcus Komponenter.
The project aims at facilitating the implementation of Smart Maintenance through extended collaboration within the maintenance community.
The project aims to reduce the lead time for sheet metal die tryout by optimizing the value stream and develop methods for numerical compensation of die and press deflections.
The project aims to digitalize established tools for production disturbance handling.
The paintshop is often a bottleneck in production and the processes are fine-tuned based on testing on numerous prototypes. To meet the future demands there is a great need to improve the product preparation process. The aim is to develop methods, techniques and software, and supporting measurement methodology, for simulation of paint curing in IR and convective ovens. The goal is to assist the industry to further develop and optimize their surface treatment to be more energy and cost efficient; to have a shorter lead time in product development; and to give a higher product quality.
Målet var att förstå de utmaningar som den svenska och japanska industrin står inför studiebesök.
The overall goal of DiSAM is to create a unique test AM Hub in Sweden for metal and polymer based additive manufacturing processes.
Improve the efficiency of sawmills, including improved monitoring and maintenance of the production line. This by sharing data via digital twin between the actors in the maintenance chain.
The project aims a digitising the temperatures during the casting of rolls and suggest actions to the casting manager to reduce the variability of the process
The project will develop a concept for production workers to easily build simple low-cost IoT-aided improvement solutions at the production shop floor.
This project aims to contribute to the development of future ERP-systems. The project will explore how to offer work, redefine work roles and challenge companies to make use of advanced systems support and the technology within and around these. Overall, the project aims to contribute to the development of both the next generation of ERP-systems and a complementary change in the way firms see upon work organization, so that technology can support and meet the needs of the humans within organisations rather than enforcing structures upon them.
The project aims at radically improving the working environment and the employee security within the heavy manufacturing industries by using and adapting the latest technology for low and ultraprecise positioning and decision support systems. The target is to increase security and safety by adapting the decision-support and positioning system for the heavy manufacturing industries.
SCARCE will investigate the needs, possibilities and obstacles in value chains up- and down-stream from a focal SME company. SCARCE will explore what data to measure and visualize, and how this data can enable more automated execution, as well as, more dynamic and proactive planning of production capacity and material flows across the companies in the value chain. In addition, we will study organizational capabilities, especially the future human role, for implementing and managing in a digital and data-driven value chain.
DiLAM strengthens the competitiveness of the Swedish manufacturing industry by aligning the digital and physical supply chains for additive manufacturing of large parts.
To demonstrate the new technology with robots that enable Swedish companies to develop innovative new products for automated production o maintenance.