Manufacturing operational management modeling using interpreted Petri nets

Guirro, Diego Nogueira;Asato, Osvaldo Luis;Givanildo Alves Dos Santos;Nakamoto, Francisco Yastami

Description

Abstract: The dynamics of the interaction between different levels in production system is the study of many research groups to seek a better understanding of the complex nature of such systems to propose an effective and efficiency from rational use of available resources and required inputs. Demand for products increasingly customized by a dynamic and competitive market has reduced considerably the life cycle of such products and flexibility of production processes has become essential for companies. Flexibility is not only one attribute, but a set of attributes that provides the flexibility for production systems. The interactions between the flexible sub-systems are sources of waste and rework, causing high costs in the production process. In this sense, the concept of Lean Manufacturing has promoted a restructuring of some processes of the MES (Manufacturing Execution Systems), responsible for managing the activities of production, integrate data from the ERP (Enterprise Resource Planning) and synchronize production tasks the flow of materials, making them oriented by the demand. One other important aspect in the industrial context is the new future vision promoted by Industry 4.0 paradigm that is envisioned a complete decentralization of control of the production system by autonomous and intelligent devices interconnected by a communication system, that contribute to the global goals of the enterprise. The ANSI/ISA S95 presents a conceptual model that may contribute to the implementation of the industry 4.0 concept. The objective of this study is to present a proposal for modeling of objects in level 3 of the S95 standard using interpreted Petri nets.

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Mentions (0)

Metrics

Dataset Index

0.4

FAIR Score

85%

Citations

0

Mentions

0

Metrics Over Time

Publication Details

DOI

Publisher

SciELO journals

License

Creative Commons Attribution 4.0 International

Assigned Domain

Subfield

Industrial and Manufacturing Engineering

Field

Engineering

Domain

Physical Sciences

Confidence Score

59%

Source

Scholar Data Model

Keywords

91099 Manufacturing Engineering not elsewhere classifiedFOS: Electrical engineering, electronic engineering, information engineering

Normalization Factors

FT

64.42

CTw

1.00

MTw

1.00