Challenges in Implementing Human-Centered AI for Time Data Management in Industry
Paper in proceeding, 2027

Accurate time data are critical for industrial process planning but are often produced through manual, expertise-dependent practices. This paper investigates challenges associated with implementing human-centered artificial intelligence (HCAI) to support Time Data Management (TDM) during process planning for manual assembly. A qualitative multi-case study was conducted at three industrial companies with differing production contexts and digital maturity. The results show that TDM is characterized by late validation, fragmented system support, and a strong reliance on human judgment. While HCAI can enhance efficiency and transparency, significant human, organizational, and data-related challenges remain. The study identifies conditions under which HCAI can responsibly support industrial TDM and at what system levels these can be found.

Time data management

Industry 5.0

Human-centeredness

AI

Human-centered AI

Author

Sandra Mattsson

RISE Research Institutes of Sweden

Peter Almström

Chalmers, Technology Management and Economics, Supply and Operations Management 00

Yongkuk Jeong

Royal Institute of Technology (KTH)

Bernt Spielberger

Folkuniversitetet

IFIP Advances in Information and Communication Technology

1868-4238 (ISSN) 1868-422X (eISSN)

Vol. 811 IFIPAICT 377-390
9783032386137 (ISBN)

45th IFIP WG 5.7 International Conference on Advances in Production Management Systems, APMS 2026
Bergamo, Italy,

Subject Categories (SSIF 2025)

Artificial Intelligence

DOI

10.1007/978-3-032-38614-4_25

More information

Latest update

10/26/2026