Artificial intelligence for throughput bottleneck analysis – State-of-the-art and future directions

• DOI: 10.1016/j.jmsy.2021.07.021
• Publication Date: 2021-08-11T01:01:58Z
• Authors: Mukund Subramaniyan; Anders Skoogh; Jon Bokrantz; Muhammad Azam Sheikh; Matthias Thürer; Qing Chang
• Keywords: Factory (object-oriented programming)

Identifying, and eventually eliminating throughput bottlenecks, is a key means to increase productivity in production systems. In the real world, however, bottlenecks challenge. This due landscape of complex factory dynamics, with several hundred machines operating at any given time. Academic researchers have tried develop tools help identify eliminate bottlenecks. Historically, research efforts focused on developing analytical discrete event simulation modelling approaches However, rise industrial digitalisation artificial intelligence (AI), academic explored different ways which AI might be used based vast amounts digital shop floor data. By conducting systematic literature review, this paper aims present state-of-the-art into use for bottleneck analysis. To make work solutions more accessible practitioners, are classified four categories: (1) identify, (2) diagnose, (3) predict (4) prescribe. was inspired by real-world management practice. The categories, diagnose focus analysing historical whereas prescribe future also provides topics practical recommendations may further push boundaries theoretical