scholarly journals Advances in Production Management Systems. Smart Manufacturing for Industry 4.0

2018 ◽  
Keyword(s):  
Industry 4.0 ◽  
Production Management ◽  
Management Systems ◽  
Smart Manufacturing

scholarly journals Axiomatic Design based Design of a Software Prototype for Smart Shopfloor Management

2018 ◽  
Vol 223 ◽  
pp. 01012 ◽  
Author(s):  
Erwin Rauch ◽  
Andrew Vickery ◽  
Manuel Garcia ◽  
Rafael Rojas ◽  
Dominik T. Matt
Keyword(s):  
Literature Review ◽  
Industry 4.0 ◽  
Production Management ◽  
Axiomatic Design ◽  
Management Systems ◽  
Shop Floor ◽  
Management Concepts ◽  
Project Smart ◽  
Definition Of ◽  
Software Prototype

Shopfloor management systems are currently undergoing a change. With the era of Industry 4.0, traditional shop floor management concepts are changing to new and digitally supported approaches for the coordination and management of production at the shop floor level. In order to investigate this change, the research project “Smart Shopfloor” is aiming to develop a software prototype for production management in the era of Industry 4.0. Requirements of industry are collected through literature review and workshops with industry and are translated into software functionalities. These functionalities lead, via an Axiomatic Design (AD) decomposition to design solutions for Smart Shop Floor Management systems. The results of the AD study form the basis for the software architecture and the definition of core and add-on functionalities of the software prototype. The focus of this paper lies on the AD decomposition of the design concept and further gives an overview of potential functionalities. In future, the developed concept will then be implemented in a lab environment before implementing and testing it in industrial case studies.

scholarly journals EVOLUTIONS OF GROUP MANAGEMENT DEVELOPMENT OF MOBILE ROBOTIC PLATFORMS IN WAREHOUSING 4.0.

2021 ◽  
pp. 57-64
Author(s):  
Igor Nevliudov ◽  
Vladyslav Yevsieiev ◽  
Oleksandr Klymenko ◽  
Nataliia Demska ◽  
Maksym Vzhesnievskyi
Keyword(s):  
Industry 4.0 ◽  
Lean Production ◽  
High Density ◽  
Management Systems ◽  
Smart Manufacturing ◽  
Warehouse Management ◽  
Group Management ◽  
Loading And Unloading ◽  
Robotic Platforms ◽  
The Impact

The subject of this research is the technology of management of mobile robot groups in the concept of Industry 4.0 and its composition. The purpose of this article is to find ways to implement an effective strategy for building and managing mobile robotic platforms in Warehousing, as a key tool of Lean Production. To achieve this goal, it is necessary to solve the following tasks: to analyze the management of supply chains in Smart Manufacturing, within Industry 4.0 and its impact on achieving the goals of Lean Production; to study the evolution of technologies used in Warehousing in the dynamics of the Industrial Revolution; to analyze the evolution of Warehouse Management Systems (WMS) as one of the most important components on the basis of which the requirements for automation of Warehousing automation in Smart Manufacturing with group management of mobile robotic platforms are implemented and achieved; to compare the impact of the technologies used by Warehousing 4.0 and Warehouse Management Systems on the key indicators of Lean Production. Results: One of the promising ways to achieve the effectiveness of the implementation of Lean Production tools in WMS systems is the use of Collaborative Robot System technology, which makes it possible to ensure a high density of product storage in Warehousing. However, modern mobile robotic platforms have their limitations both in the methods of loading and unloading products, and in the design. Therefore, the authors see the task in improving the design of mobile robotic platforms, which will develop a new intelligent group method of loading and unloading products, increasing the storage density for a variety of goods. Conclusions: The paper compares the impact of Warehousing 4.0 and Warehouse Management Systems on key Lean Production tools, which shows how the introduction of new group management technologies for robotic platforms in Warehousing 4.0 and Warehouse Management Systems (WMS) affects the effectiveness of Lean Production tools such as Heijunka, Just-in-time, 5S. This suggests that the introduction of new models and methods of managing complex warehouses with high density and chaotic storage of products, through the use of mobile robotic autonomous systems, will significantly optimize the process of supply chain management in Smart Manufacturing.

scholarly journals Connectivity as a Design Feature for Industry 4.0 Production Equipment: Application for the Development of an In-Line Metrology System

2021 ◽  
Vol 11 (3) ◽  
pp. 1312
Author(s):  
Ana Pamela Castro-Martin ◽  
Horacio Ahuett-Garza ◽  
Darío Guamán-Lozada ◽  
Maria F. Márquez-Alderete ◽  
Pedro D. Urbina Coronado ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Design Feature ◽  
Production Equipment ◽  
Smart Manufacturing ◽  
Process Data ◽  
Industrial Sectors ◽  
Advanced Manufacturing Technologies ◽  
Manufacturing Technologies ◽  
Equipment Application ◽  
The Impact

Industry 4.0 (I4.0) is built upon the capabilities of Internet of Things technologies that facilitate the recollection and processing of data. Originally conceived to improve the performance of manufacturing facilities, the field of application for I4.0 has expanded to reach most industrial sectors. To make the best use of the capabilities of I4.0, machine architectures and design paradigms have had to evolve. This is particularly important as the development of certain advanced manufacturing technologies has been passed from large companies to their subsidiaries and suppliers from around the world. This work discusses how design methodologies, such as those based on functional analysis, can incorporate new functions to enhance the architecture of machines. In particular, the article discusses how connectivity facilitates the development of smart manufacturing capabilities through the incorporation of I4.0 principles and resources that in turn improve the computing capacity available to machine controls and edge devices. These concepts are applied to the development of an in-line metrology station for automotive components. The impact on the design of the machine, particularly on the conception of the control, is analyzed. The resulting machine architecture allows for measurement of critical features of all parts as they are processed at the manufacturing floor, a critical operation in smart factories. Finally, this article discusses how the I4.0 infrastructure can be used to collect and process data to obtain useful information about the process.

scholarly journals Digital Twins Collaboration for Automatic Erratic Operational Data Detection in Industry 4.0

2021 ◽  
Vol 11 (7) ◽  
pp. 3186
Author(s):  
Radhya Sahal ◽  
Saeed H. Alsamhi ◽  
John G. Breslin ◽  
Kenneth N. Brown ◽  
Muhammad Intizar Ali
Keyword(s):  
Industry 4.0 ◽  
Manufacturing Systems ◽  
Interaction Mechanism ◽  
Semantic Knowledge ◽  
Smart Manufacturing ◽  
Data Detection ◽  
Workflow Model ◽  
Digital Twins ◽  
Potential Failure ◽  
Operational Data

Digital twin (DT) plays a pivotal role in the vision of Industry 4.0. The idea is that the real product and its virtual counterpart are twins that travel a parallel journey from design and development to production and service life. The intelligence that comes from DTs’ operational data supports the interactions between the DTs to pave the way for the cyber-physical integration of smart manufacturing. This paper presents a conceptual framework for digital twins collaboration to provide an auto-detection of erratic operational data by utilizing operational data intelligence in the manufacturing systems. The proposed framework provide an interaction mechanism to understand the DT status, interact with other DTs, learn from each other DTs, and share common semantic knowledge. In addition, it can detect the anomalies and understand the overall picture and conditions of the operational environments. Furthermore, the proposed framework is described in the workflow model, which breaks down into four phases: information extraction, change detection, synchronization, and notification. A use case of Energy 4.0 fault diagnosis for wind turbines is described to present the use of the proposed framework and DTs collaboration to identify and diagnose the potential failure, e.g., malfunctioning nodes within the energy industry.

scholarly journals Automation technology as a key component of the Industry 4.0 production development path

2021 ◽  
Author(s):  
Christian Brecher ◽  
Aleksandra Müller ◽  
Yannick Dassen ◽  
Simon Storms
Keyword(s):  
Industry 4.0 ◽  
Information Technologies ◽  
Production Systems ◽  
Product Variety ◽  
Transformation Process ◽  
Smart Manufacturing ◽  
Production Development ◽  
Flexible Production Systems ◽  
Current Production ◽  
Automation Technology

AbstractSince 2011, the Industry 4.0 initiative is a key research and development direction towards flexible production systems in Germany. The objective of the initiative is to deal with the challenge of an increased production complexity caused by various factors such as increasing global competition between companies, product variety, and individualization to meet customer needs. For this, Industry 4.0 envisions an overarching connection of information technologies with the production process, enabling smart manufacturing. Bringing current production systems to this objective will be a long transformation process, which requires a coherent migration path. The aim of this paper is to represent an exemplary production development way towards Industry 4.0 using eminent formalization approaches and standardized automation technologies.

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