The project will explore how an interactive overview, a “digital mirror” of production, can be designed and made available in a production environment to support production staff, increase work motivation and increase efficiency.
Protective equipment, dust and high noise levels are common phenomena in the production environment and can prevent easy and user-friendly interaction with classic digital interfaces. The project aims to explore and rethink ideas for interfaces using techniques such as informative sounds, sensors, leading color or interactive surfaces to help production professionals easily interact and capture digital content. Such a service can also increase the understanding of production staff for their role in the production system.
Recent research from Chalmers have shown that by slightly tuning robot motions, the energy use can be reduced by 10 –30%, with preserved cycle time.
Increased digitalization brings new possibilities for Swedish manufacturing companies. This project focuses on what data are needed to feed assembly variation simulation and how this data can be captured and stored efficiently and effectively. The project contributes to increased geometrical quality. The technical value chain from part inspection, to extraction of relevant data, storage of data, usage of data in variation simulation (as a digital twin) and to visualization of simulation results as decision support will be covered. This has the potential to replace prototypes/test series and saves cost, time and reduces the environmental impact.
The objective is to bring together expertise from AI and LCE to Product/Service Systems for Swedish manufacturing firms in a multidisciplinary research effort to utilise latest techniques efficiently for Swedish production industry. The goal is to make a plan of developing demonstrators in production and maintenance using artificial intelligence techniques, digital technologies and lifecycle engineering methods
TriBlade is a new ground-breaking technology for rotor blades in wind turbines, which have the potential to affect the entire wind power market. The technology has been developed by Winfoor in collaboration with Lund University and is based on each rotor blade designed as a truss.
The aim of the project is to demonstrate utilization of additive manufacturing for copper-based products and process solutions and faster adaption
The aim is to develop new models for visualizing and predicting delivery schedule variations in supply chains.
Industrial production systems typically include many process steps performed by automatic or semi-automatic machines. Depending on the different variables, these machines age and thereby affecting both the quality of the manufacturing step and the resource requirements
The long-term goal of the research project is to develop hardware and software platform, i.e. modular systems that enables production workers to easily build and implement IoT-aided improvement solutions at the production shop floor