Process modeling with multi-level categorical inputs via variable selection and level aggregation

Huihui Miao, Andi Wang, Bing Li, Tzyy-Shuh Chang and Jianjun Shi

IISE Transactions, 2023, vol. 55, issue 4, 363-376

Abstract: An Industrial IoT-enabled manufacturing system often involves multiple categorical variables, denoting the process configurations and product customizations. These categorical variables lead to a flexible relationship between the input process variables and output quality measurements, as there are many potential configurations of the manufacturing process. This causes significant challenges for data-driven process modeling and root cause diagnosis. This article proposes a data-driven additive model to address the effects of different categorical variables on the relationship between process variables and quality measurements. The estimation algorithm automatically identifies the variables that have significant effects on the product quality, aggregates the levels of each categorical variable based on a priori knowledge of level similarity, and provides an accurate model that describes the relationship between the process variables and quality measurements. The simulation study validates the accuracy and effectiveness of the proposed method, and a case study on a hot rolling process shows that the method provides useful guidance on the understanding of the production system.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/24725854.2021.2004626 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:uiiexx:v:55:y:2023:i:4:p:363-376

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/uiie20

DOI: 10.1080/24725854.2021.2004626

Access Statistics for this article

IISE Transactions is currently edited by Jianjun Shi

More articles in IISE Transactions from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().