Manufacturing Maps, a Novel Tool for Smart Factory Management Based on Petri Nets and Big Data Mini-Terms

Abstract

This article defines a new concept for real-time factory management—manufacturing maps. Manufacturing maps are generated from two fundamental elements, mini-terms and Petri nets. Mini-terms are sub-times of a technical cycle, the time it takes for any component to perform its task. A mini-term, by definition, is a sub-cycle time and it would only make sense to use the term in connection with production improvement. Previous studies have shown that when the sub-cycle time worsens, this indicates that something unusual is happening, enabling anticipation of line failures. As a result, a mini-term has dual functionality, since, on the one hand, it is a production parameter and, on the other, it is a sensor used for predictive maintenance. This, combined with how easy and cheap it is to extract relevant data from manufacturing lines, has resulted in the mini-term becoming a new paradigm for predictive maintenance, and, indirectly, for production analysis. Applying this parameter using big data for machines and components can enable the complete modeling of a factory using Petri nets. This article presents manufacturing maps as a hierarchical construction of Petri nets in which the lowest level network is a temporary Petri net based on mini-terms, and in which the highest level is a global view of the entire plant. The user of a manufacturing map can select intermediate levels, such as a specific production line, and perform analysis or simulation using real-time data from the mini-term database. As an example, this paper examines the modeling of the 8XY line, a multi-model welding line at the Ford factory in Almussafes (Valencia), where the lower layers are modeled until the mini-term layer is reached. The results, and a discussion of the possible applications of manufacturing maps in industry, are provided at the end of this article.

Miniterm, a Novel Virtual Sensor for Predictive Maintenance for the Industry 4.0 Era

“…More recently, in [22] the data model is mixed with the complete modeling of a factory using Petri nets to develop a manufacturing map, a hierarchical construction of Petri nets in which the lowest level network is a temporary Petri net based on mini-terms, and in which the highest level is a global view of the entire plant. The user of a manufacturing map can select intermediate levels, such as a specific production line, and perform analysis or simulation using real-time data from the mini-term database.…”

A Novel Method for General Hierarchical System Modeling via Colored Petri Nets Based on Transition Extractions from Real Datasets

“…This CPN model combined elements from a series of strategies on cloud systems and resource allocation, which we developed [9][10][11][12][13]. Other fields of PN and CPN applications are mentioned below: parallel processing [14], grid computing applications [15,16], traffic control [17], analysis of safety-critical interactive Systems [18], manufacturing [19], everyday applications [20], supply chain management [21], medicine [22], industry [23], project management [24], fuzzy systems [25], and communication protocols [26,27].…”