Manufacturing operational management modeling using interpreted Petri nets

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.

Design Science Research in practice: review of applications in Industrial Engineering

“…For instance, among the class of emerging problems in Industry is the lack of a digital strategy for Industry 4.0 (Raj et al, 2020). On the other hand, the DSR has the potential to develop artifacts to support the decision system (Goecks et al, 2020), optimize resources to reduce time in hospitals (Flórez et al, 2020), decentralize production control through autonomous, intelligent and interconnected devices (Guirro et al, 2020). Finally, we are very confident that the RSD can forward artifacts that resolve conflicts in human relations within organizations.…”

“…Big Data and IoT (Flórez et al, 2020;Campos & Alves, 2020) Decentralization of the productive system's control by autonomous and intelligent devices interconnected by a communication system (Guirro et al, 2020).…”

“…Enterprise Resource Planning (ERP); Big Data, Artificial Intelligence, Machine Learning (Guirro et al, 2020).…”