ICs Manufacturing Workflow Assessment via Multiple Logs Analysis

Vincenza Carchiolo, Alessandro Longheu, Giuseppe Saccullo, Simona Sau, Renato Sortino

2020

Abstract

Today’s complexity in ICT services, consisting of several interacting applications, requires strict control over log files to detect what exceptions/errors occurred and how they could be fixed. The current scenario is harder and harder due to the volume, velocity, and variety of (big) data within log files, therefore an approach to assist developers and facilitate their work is needed. In this paper an industrial application of such log analysis is presented, in particular, we consider the manufacturing of Integrated Circuits (ICs), i.e. a set of physical and chemical processes performed by production machines onto silicon slices. We present a widely used set of open-source tools that join together a platform to allow logs mining to assess manufacturing workflow processes. We show that the proposed architecture helps in discovering and removing anomalies and slowdown in ICs production.

Paper Citation

in Harvard Style

Carchiolo V., Longheu A., Saccullo G., Sau S. and Sortino R. (2020). ICs Manufacturing Workflow Assessment via Multiple Logs Analysis.In Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS, ISBN 978-989-758-423-7, pages 801-808. DOI: 10.5220/0009517208010808

in Bibtex Style

@conference{iceis20,
author={Vincenza Carchiolo and Alessandro Longheu and Giuseppe Saccullo and Simona Sau and Renato Sortino},
title={ICs Manufacturing Workflow Assessment via Multiple Logs Analysis},
booktitle={Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS,},
year={2020},
pages={801-808},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0009517208010808},
isbn={978-989-758-423-7},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 22nd International Conference on Enterprise Information Systems - Volume 2: ICEIS,
TI - ICs Manufacturing Workflow Assessment via Multiple Logs Analysis
SN - 978-989-758-423-7
AU - Carchiolo V.
AU - Longheu A.
AU - Saccullo G.
AU - Sau S.
AU - Sortino R.
PY - 2020
SP - 801
EP - 808
DO - 10.5220/0009517208010808