A data-driven approach to diagnosing throughput bottlenecks from a maintenance perspective
Journal article, 2020

Show more

Throughput bottlenecks

Machine learning

Maintenance

Manufacturing system

Production system

Data science

Author

Mukund Subramaniyan

Chalmers, Industrial and Materials Science, Production Systems

Anders Skoogh

Chalmers, Industrial and Materials Science, Production Systems

Muhammad Azam Sheikh

Chalmers, Computer Science and Engineering (Chalmers), CSE Verksamhetsstöd

Jon Bokrantz

Chalmers, Industrial and Materials Science, Production Systems

Björn Johansson

Chalmers, Industrial and Materials Science, Production Systems

Christoph Roser

Karlsruhe University of Applied Sciences

Published in

Computers and Industrial Engineering

0360-8352 (ISSN)

Vol. 150 art. no 106851

Research Project(s)

DAIMP - Data Analytics in Maintenance Planning

VINNOVA (2015-06887), 2016-03-01 -- 2019-02-28.

Categorizing

Subject Categories (SSIF 2011)

Production Engineering, Human Work Science and Ergonomics

Reliability and Maintenance

Software Engineering

Driving Forces

Sustainable development

Areas of Advance

Production

Identifiers

DOI

10.1016/j.cie.2020.106851

More information

Latest update

12/4/2020