Time Data Management Automation for Manual Assembly - TIMEBLY
Research Project, 2021
– 2024
Purpose and goal
The digitalization of the manufacturing industry puts focus on the input data. One of the most challenging processes to acquire accurate time for, is manual assembly and materials handling. The TIMEBLY project will address these challenges with the ultimate goal to increase the competitiveness, enhance the digital readiness and at the same time create a sustainable work environment. The technological development with better sensors and more computing power enables new ways of determine the times and new possibilities to do simulations of workplaces.
Expected results and effects
TIMEBLY’s improved collection and analysis of data for manual tasks will have four major impacts: 1. Better planning conditions, through better time bases where deviations can be separated from the normal state. 2. Enable product introduction and volume change, through simulations using digital human models (DHM) and efficient process planning. 3. Accurate product life cycle cost calculations to prioritize improvement efforts and make correct offers to customers. 4. Fair work load and better workplace design, by having more accurate time data.
Planned approach and implementation
The challenge of creating time bases for low volume and high variety production will be addressed through a design science approach where the researchers together with the participating companies design and test new methods to efficiently develop TDM systems. The aim is to generalize this knowledge and disseminate to other companies through several channels such as a handbook and workshops.
Participants
Peter Almström (contact)
Chalmers, Technology Management and Economics, Supply and Operations Management
Collaborations
BAE Systems Bofors
Karlskoga, Sweden
Fraunhofer-Chalmers Centre
Göteborg, Sweden
RISE Research Institutes of Sweden
Göteborg, Sweden
Royal Institute of Technology (KTH)
Stockholm, Sweden
Scania CV AB
Södertälje, Sweden
Solme AB
Göteborg, Sweden
Strömsholmen AB
Tranås, Sweden
Swegon Operations AB
Kvänum, Sweden
University of Skövde
Skövde, Sweden
Funding
VINNOVA
Project ID: Dnr2021-02524
Funding Chalmers participation during 2021–2024
Related Areas of Advance and Infrastructure
Production
Areas of Advance