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.


Peter Almström (contact)

Chalmers, Technology Management and Economics, Supply and Operations Management


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



Project ID: Dnr2021-02524
Funding Chalmers participation during 2021–2024

Related Areas of Advance and Infrastructure


Areas of Advance



Renaissance for Time Data Management

Paper in proceeding

More information

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