Publication detail

Screening Process Mining and Value Stream Techniques on Industrial Manufacturing Processes: Process Modelling and Bottleneck Analysis

RUDNITCKAIA, J. VENKATASCHALAM, H. ESSMANN, R. HRUŠKA, T. COLOMBO, A.

Original Title

Screening Process Mining and Value Stream Techniques on Industrial Manufacturing Processes: Process Modelling and Bottleneck Analysis

Type

journal article in Web of Science

Language

English

Original Abstract

One major result of the Industrial Digitalization is the access to a large set of digitalized data and information, i.e. Big Data. The market of analytic tools offers a huge variety of algorithms and software to exploit big datasets. Implementing their advantages into one approach brings better results and empower possibilities for process analysis. Its application in the manufacturing industry requires a high level of effort and remains to be challenging due to product complexity, human-centric processes, and data quality. In this manuscript, the authors combine process mining and value streams methods for analyzing the data from the information management system, applying the approach to the data delivered by one specific manufacturing system. The manufacturing process to be examined is the process of assembling gas meters in the manufacture. This specific and important part of the whole supply-chain process was taken as suitable for the study due to almost full-automated line with data about each process activity of the value-stream in the information system. The paper applies process mining algorithms in discovering a descriptive process model that plays the main role as a basis for further analysis. At the same time, modern techniques of the bottleneck analysis are described, and two new comprehensible methods of bottlenecks detection (TimeLag and Confidence intervals methods), as well as their advantages, will be discussed. Achieved results can be subsequently used for other sources of big data and industrial-compliant Information Management Systems.

Keywords

bottleneck analysis, manufacturing process, process mining, process modelling, information management system, value stream

Authors

RUDNITCKAIA, J.; VENKATASCHALAM, H.; ESSMANN, R.; HRUŠKA, T.; COLOMBO, A.

Released

16. 2. 2022

ISBN

2169-3536

Periodical

IEEE Access

Year of study

2022

Number

10

State

United States of America

Pages from

24203

Pages to

24214

Pages count

12

URL

https://ieeexplore.ieee.org/document/9715073

BibTex

@article{BUT177411,
  author="Julia {Rudnitckaia} and Hari Santosh {Venkataschalam} and Roland {Essmann} and Tomáš {Hruška} and Armando Walter {Colombo}",
  title="Screening Process Mining and Value Stream Techniques on Industrial Manufacturing Processes: Process Modelling and Bottleneck Analysis",
  journal="IEEE Access",
  year="2022",
  volume="2022",
  number="10",
  pages="24203--24214",
  doi="10.1109/ACCESS.2022.3152211",
  issn="2169-3536",
  url="https://ieeexplore.ieee.org/document/9715073"
}