Sheet metal forming dies are advanced products under massive global competition. The time to develop, produce and run-in the dies also constitutes an important part of the time to market for new vehicles. Therefore, the project aims to reduce the lead time by improving and optimizing the value stream, and introducing new research results, developed partly by industrial PhD work and Master Projects.
The lead time will be shortened by improved communication, geometry assurance and new methods tor numerical analysis or the tool design that will drastically reduce the try-out time.
Finally, the influence of the machine dynamics on the forming processes will be studied both physically and numerically. This work will lead to proposals for amendments in corporate standards and communication, as well as industrial guidelines and education for academic and industrial individuals.
Demonstrate solutions for visibility in production logistics, for dynamic abilities and resource efficiency.
DiLAM strengthens the competitiveness of the Swedish manufacturing industry by aligning the digital and physical supply chains for additive manufacturing of large parts.
Method to understand how to automate information handling to get more efficient handling of production deviations.
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.
The project aims to digitalize established tools for production disturbance handling.
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 aims at facilitating the implementation of Smart Maintenance through extended collaboration within the maintenance community.
To provide understanding of the direct and indirect cost and CO2 effects of packaging principles for industrial packaging in the automotive industry.
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.
The aim is to develop new models for visualizing and predicting delivery schedule variations in supply chains.
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 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.
To demonstrate the new technology with robots that enable Swedish companies to develop innovative new products for automated production o maintenance.
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.
The project will develop a concept for production workers to easily build simple low-cost IoT-aided improvement solutions at the production shop floor.