scholarly journals Model-Driven Design and Development of Flexible Automated Production Control Configurations for Industry 4.0

2021 ◽  
Vol 11 (5) ◽  
pp. 2319
Author(s):  
Unai Gangoiti ◽  
Alejandro López ◽  
Aintzane Armentia ◽  
Elisabet Estévez ◽  
Marga Marcos
Keyword(s):  
Control System ◽  
Production System ◽  
Industry 4.0 ◽  
Production Control ◽  
Production Systems ◽  
Normal Operation ◽  
Functional Requirements ◽  
Multi Agent Systems ◽  
Design And Development ◽  
Automation Systems

The continuous changes of the market and customer demands have forced modern automation systems to provide stricter Quality of service (QoS) requirements. This work is centered in automation production system flexibility, understood as the ability to shift from one controller configuration to a different one, in the most quick and cost-effective way, without disrupting its normal operation. In the manufacturing field, this allows to deal with non-functional requirements such as assuring control system availability or workload balancing, even in the case of failure of a machine, components, network or controllers. Concretely, this work focuses on flexible applications at production level, using Programmable Logic Controllers (PLCs) as primary controllers. The reconfiguration of the control system is not always possible as it depends on the process state. Thus, an analysis of the system state is necessary to make a decision. In this sense, architectures based on industrial Multi Agent Systems (MAS) have been used to provide this support at runtime. Additionally, the introduction of these mechanisms makes the design and the implementation of the control system more complex. This work aims at supporting the design and development of such flexible automation production systems, through the proposed model-based framework. The framework consists of a set of tools that, based on models, automate the generation of control code extensions that add flexibility to the automation production system, according to industry 4.0 paradigm.

scholarly journals Simulation von Cyber-Physischen Produktionssystemen in einer Forschungsinfrastruktur

2020 ◽  
Author(s):  
Iris Gräßler
Keyword(s):  
Communication Technology ◽  
Information Acquisition ◽  
Industry 4.0 ◽  
Production Control ◽  
Production Systems ◽  
General Concept ◽  
Radio Network ◽  
Systems Research ◽  
Digital Twins ◽  
Cyber Physical Production Systems

The article describes the setup of an experimentation and validation environment by extending a production laboratory: All relevant elements of the production laboratory were equipped with computer systems, so-called "industry 4.0 boxes", and interconnected via a peer-to-peer radio network. The "industry 4.0 boxes" are used to upgrade dedicated sensors for recording machine behaviour and communication technology to be integrated into decentralized production control. In addition, digital twins were implemented to map machine and user behaviour, enable control and support information acquisition and processing. Thereby, a research infrastructure is created for research on potentials of cyber-physical production systems. Research outcomes will be used as a decision basis for companies and for validation of production optimizations. This paper describes the concept and implementation of industry 4.0 functionalities and derives a general concept of simulation platforms for CPPS.

scholarly journals MODERNIZATION OF THE TRANSPORT SYSTEM CONTROL OF THE PRODUCTION SYSTEM

2019 ◽  
pp. 141-147
Author(s):  
Patrik Šarga ◽  
Tomáš Záboly
Keyword(s):  
Transport System ◽  
Production System ◽  
Industry 4.0 ◽  
New Technologies ◽  
Production Systems ◽  
Control Program ◽  
Original System ◽  
System Control ◽  
Modular Production ◽  
Education Of Students

Urgency of the research. Nowadays, it is crucial to keep up with modern technologies. Therefore, this work aims to modernize the production system Festo MPS 500. Thanks to this, it will be possible to apply to the system technologies meeting the latest trends in Industry 4.0. The MPS 500 system prepared in this way can be used to research new trends in accordance with Industry 4.0. The modernized MPS 500 system will also find use in the education of students in the field of automation and mechatronics so that they are sufficiently prepared for practice. Target setting. The goal of the research was to modernize the transport system of the modular production system Festo MPS 500 according to Industry 4.0 platform. Actual scientific researches and issues analysis. When upgrading the system MPS 500 and preparing this paper, we took into account both current sources – publications and papers dealing with the current state of Industry 4.0 and modular production systems as well as existing modular production systems based on Industry 4.0 platform. Uninvestigated parts of general matters defining. At this stage of the research, data acquisition from the system MPS 500 and interconnection with the cloud was not realized. The research objective. The purpose of this article is to modernize the MPS 500, which will allow focusing on Industry 4.0 research specifically for the deployment of Cyber-physical systems, Internet of Things, Big Data, Cloud Computing. The statement of basic materials. Effective research of the new technologies in the industry requires to use modern systems which meet the criteria of Industry 4.0 platform. So the original system Festo MTS 500 was upgraded by systems from Siemens. Conclusions. The main aim of this work was to modernize the transport system of the production system MPS 500. Elements of the system management were changed, and a new control program was created in the TIA Portal environment. The functionality of the MPS 500 was subsequently verified, where the full functionality of the system was confirmed. It makes the MPS 500 ready for further expansion in accordance with Industry 4.0.

scholarly journals A case study of robotic simulations using virtual commissioning supported by the use of virtual reality

2019 ◽  
Vol 299 ◽  
pp. 02006
Author(s):  
Roman Ružarovský ◽  
Radovan Holubek ◽  
Daynier Rolando Delgado Sobrino ◽  
Karol Velíšek
Keyword(s):  
Virtual Reality ◽  
Control System ◽  
Production System ◽  
Production Systems ◽  
Control Program ◽  
Human Interaction ◽  
Digital Model ◽  
The Real ◽  
Virtual Commissioning

Virtual Commissioning (VC) is a method and tool for verifying and testing the PLC control program on a virtual digital model of the manufacturing system. It allows to visualize and test the control system before the real commissioning of the production systems. The aim of the research is to implement virtual reality (VR) into the VC method and to verify the mutual interaction of signals between the simulation in VR environment, the digital model of the production system and the control system. The introduction of VR in VC increases the concept by adding more realistic visualization and tracking, which extends its validation capabilities. The changes made in VR virtual environment are transferred to the simulation model and can be validated in a real production system. The real production robotic system transformed into a virtual form will be a case study with its verification. Also will be tested security protocols and proven human interaction with the system to control the system through the virtual HMI (virtual user interface) using VR.

scholarly journals Personalization of the MES System to the Needs of Highly Variable Production

Sensors ◽  
2020 ◽  
Vol 20 (22) ◽  
pp. 6484
Author(s):  
Bożena Zwolińska ◽  
Agnieszka Anna Tubis ◽  
Norbert Chamier-Gliszczyński ◽  
Mariusz Kostrzewski
Keyword(s):  
Bayesian Inference ◽  
Production System ◽  
Industry 4.0 ◽  
Production Systems ◽  
Current System ◽  
Business Systems ◽  
Level Of Automation ◽  
Technological Structure ◽  
Mes System ◽  
High Level

The new generation Manufacturing Executions System (MES) is considered as one of the most important solutions supporting the idea of Industry 4.0. This is confirmed by research conducted among companies interested in the implementation of the Industry 4.0 concept, as well as the publications of researchers who study this issue. However, if MES software is a link that connects the world of machines and business systems, it must take into account the specifics of the supported production systems. This is especially true in case of production systems with a high level of automation, which are characterised by flexibility and agility at the operational level. Therefore, personalization of the MES software is proposed for this class of production systems. The aim of the article is to present the MES system personalization method for a selected production system. The proposed approach uses the rules of Bayesian inference and the area of customisation is the technological structure of production, taking into account the required flexibility of the processes. As part of the developed approach, the variability index was proposed as a parameter evaluating the effectiveness of the production system. Then, the results of evaluation of the current system effectiveness by use of this index are presented. The authors also present the assumptions for the developed MES personalization algorithm. The algorithm uses the rules of Bayesian inference, which enable multiple adjustments of the model to the existing environmental conditions without the need to formulate a new description of reality. The application of the presented solution in a real facility allowed for determining production areas which are the determinants of system instability. The implementation of the developed algorithm enabled control of the generated variability in real time. The proposed approach to personalization of MES software for a selected class of production systems is the main novelty of the presented research and contributes to the development of the described area of research.

scholarly journals Manufacturing operational management modeling using interpreted Petri nets

2020 ◽  
Vol 27 (2) ◽  
Author(s):  
Diego Nogueira Guirro ◽  
Osvaldo Luis Asato ◽  
Givanildo Alves dos Santos ◽  
Francisco Yastami Nakamoto
Keyword(s):  
Petri Nets ◽  
Enterprise Resource Planning ◽  
Production System ◽  
Lean Manufacturing ◽  
Industry 4.0 ◽  
Production Systems ◽  
Resource Planning ◽  
Complex Nature ◽  
Manufacturing Execution Systems ◽  
Level 3

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.

scholarly journals Evaluation of Manufacturing Process Performance by CONWIP Hybridization of Pull Controlled Production Systems

2018 ◽  
Vol 144 ◽  
pp. 05006
Author(s):  
O. Srikanth ◽  
A. V. Sita Rama Raju ◽  
B. V. Ramana Murty
Keyword(s):  
Control System ◽  
Production Control ◽  
Production Systems ◽  
Control Policy ◽  
Line Production ◽  
Event Simulation ◽  
Work In Process ◽  
Multi Stage ◽  
Modeling Analysis ◽  
Kanban Control

The main objective of this paper is pioneering an innovative tactic for the synchronization of multi-stage, multi-line, production system. This tactic is mainly depends on the optimization policy, by means of distinct event simulation process for modeling, analysis and distinction of the execution of two alternatives of Kanban control mechanism namely SEKCS (Simultaneous Extended Kanban Control System) and IEKCS (Independent Extended Kanban Control System). At this juncture the authors putting forward the two variants of Extended Kanban control system with the hybridization of CONWIP control policy to incite HSEKCS (Hybrid Simultaneous Extended Kanban Control System) and HIEKCS (Hybrid Independent Extended Kanban Control System) to make use of pooled benefits of a representative production situation in addition to improve the outcome. Therefore in this study the comparison in between different systems of proposed HEKCS specifically are HSEKCS and HIEKCS compared with the Extended Kanban Control Systems variants SEKCS and IEKCS. Simulation studies were conducted for all the five control policies considered and modeled on a multi-line, multi-stage assembly production control system. The relative performance parameters like Throughput or Production rate, Average Waiting Time and Average Work-in-Process, were assessed by means of exponentially varying demands.

Production control strategy inspired by neuroendocrine regulation

2016 ◽  
Vol 232 (1) ◽  
pp. 67-77 ◽  
Author(s):  
Haitao Zhang ◽  
Dunbing Tang ◽  
Kun Zheng ◽  
Adriana Giret
Keyword(s):  
Production System ◽  
Production Control ◽  
Production Systems ◽  
Control Model ◽  
Hormone Regulation ◽  
Work In Progress ◽  
Manufacturing Enterprises ◽  
Perfect System ◽  
Modern Manufacturing ◽  
Demand Variation

Due to the international business competition of modern manufacturing enterprises, production systems are forced to quickly respond to the emergence of changing conditions. Production control has become more challenging as production systems adapt to frequent demand variation. The neuroendocrine system is a perfect system which plays an important role in controlling and modulating the adaptive behavior of organic cells under stimulus using hormone-regulation principles. Inherited from the hormone-regulation principle, an adaptive control model of production system integrated with a backlog controller and a work-in-progress controller is presented to reduce backlog variation and keep a defined work-in-progress level. The simulation results show that the presented control model is more responsive and robust against demand disturbances such as rush orders in production system.

scholarly journals Industry 4.0 and Decision Making

2021 ◽  
pp. 400-405
Author(s):  
Frédéric Rosin ◽  
Pascal Forget ◽  
Samir Lamouri ◽  
Robert Pellerin
Keyword(s):  
Decision Making ◽  
Production System ◽  
Industry 4.0 ◽  
Production Systems ◽  
Lean Production ◽  
Management Training ◽  
Decision Making Process ◽  
Use Case ◽  
Lean Management ◽  
Different Types

AbstractIndustry 4.0 is an ubiquitous term that suggests significant impacts on the productivity and flexibility of production systems. But to what extent do the various technologies associated with Industry 4.0 contribute to enhance autonomy of operational teams by helping them make better and faster decisions, particularly in the context of Lean production system? This paper proposes a model of different types of autonomy in the decision-making process, depending on whether or not the steps in the decision-making process are enhanced by technologies. This model will be tested afterwards in a use case implemented in a learning factory offering Lean management training before being tested in a real production unit.

scholarly journals Case Study of Building a Digital Twin for a Production System

2021 ◽  
Vol 29 (49) ◽  
pp. 51-58
Author(s):  
Fedor Burčiar ◽  
Pavel Važan ◽  
Simona Pulišová
Keyword(s):  
Production System ◽  
Industry 4.0 ◽  
Production Systems ◽  
Simulation Models ◽  
Cyber Physical Systems ◽  
Production Data ◽  
Physical Systems ◽  
Production Processes ◽  
Gathering Data

Abstract As the term of Industry 4.0 becomes more and more relevant with each passing day, it is up to researchers and companies to find solutions to integrating all the technologies it covers. One of those technologies, even though not highly developed, is simulation and building Cyber-Physical Systems for gathering data and improving the production processes. In the research described in this paper, we focused on integrating production data with simulation models in order to make the process of understanding and learning about complex production systems as simple and as quick as possible. This paper contains three sections. The first one introduces the theoretical fundamentals of our research. The second one focuses on the methods used to create a digital model of production system. The final one discusses the results of the conducted experiments, and their impact on further research.

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