Towards Implementing a Collaborative Manufacturing Cloud Platform: Experimenting Testbeds Aiming Asset Efficiency

2020 ◽  
Author(s):  
Nuno Santos ◽  
Paula Monteiro ◽  
Francisco Morais ◽  
Jaime Pereira ◽  
Daniel Dias ◽  
...  
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Proof Of Concept ◽  
Cloud Platform ◽  
Industrial Internet Of Things ◽  
Manufacturing Environment ◽  
Collaborative Manufacturing ◽  
Manufacturing Operations ◽  
Industrial Internet ◽  
The Future

Abstract Developing Industrial Internet of Things (IIoT) systems requires addressing challenges that range from acquiring data at the level of the shopfloor, integrated at the edge level and managing it at the cloud level. Managing manufacturing operations at the cloud level arose the opportunity for extending decisions to entities of the supply chain in a collaborative way. Not only it has arisen many challenges due to several interoperability needs; but also in properly defining an effective way to take advantage of the available data, leading to Industrial Digital Thread (IDT) and Asset Efficiency (AE) implementing. This paper discusses implementation concerns for a collaborative manufacturing environment in an IIoT system in order to monitor equipment’s AE. Each concern was addressed in a separate proof of concept testbed. The demonstration is based in a project for the IIoT domain called PRODUTECH-SIF (Solutions for the Industry of the Future).

scholarly journals Responding to Failure Events in the Manufacturing Environment

2018 ◽  
Vol 188 ◽  
pp. 05006
Author(s):  
Christos Anagnostopoulos ◽  
Christos Alexakos ◽  
Apostolos Fournaris ◽  
Christos Koulamas ◽  
Athanasios Kalogeras
Keyword(s):  
Internet Of Things ◽  
Manufacturing Process ◽  
Failure Detection ◽  
Multi Agent System ◽  
Industrial Internet Of Things ◽  
Manufacturing Environment ◽  
Industrial Environment ◽  
Industrial Internet ◽  
Multi Agent ◽  
Manufacturing Resources

The manufacturing environment is characterized by increased complexity with different devices, systems and applications that need to interoperate, while residing at different layers of the classical industrial environment hierarchy. The introduction of the Industrial Internet of Things with increasingly smarter devices drives towards flatter hierarchies. This paper deals with an architecture for integration of IIoT devices in the manufacturing environment utilizing a Multi Agent System to this end. This extended architecture is utilised so as to perform failure detection of both IIoT devices and manufacturing resources, and react by altering the manufacturing process either automatically or semi-automatically.

scholarly journals Cooperative Approaches to Data Sharing and Analysis for Industrial Internet of Things Ecosystems

2021 ◽  
Vol 11 (16) ◽  
pp. 7547
Author(s):  
Henning Baars ◽  
Ann Tank ◽  
Patrick Weber ◽  
Hans-Georg Kemper ◽  
Heiner Lasi ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Data Sharing ◽  
Value Creation ◽  
Manufacturing Industries ◽  
Industrial Internet Of Things ◽  
Manufacturing Environment ◽  
Novel Approach ◽  
Industrial Internet ◽  
It Resources

The collection and analysis of industrial Internet of Things (IIoT) data offer numerous opportunities for value creation, particularly in manufacturing industries. For small and medium-sized enterprises (SMEs), many of those opportunities are inaccessible without cooperation across enterprise borders and the sharing of data, personnel, finances, and IT resources. In this study, we suggest so-called data cooperatives as a novel approach to such settings. A data cooperative is understood as a legal unit owned by an ecosystem of cooperating SMEs and founded for supporting the members of the cooperative. In a series of 22 interviews, we developed a concept for cooperative IIoT ecosystems that we evaluated in four workshops, and we are currently implementing an IIoT ecosystem for the coolant management of a manufacturing environment. We discuss our findings and compare our approach with alternatives and its suitability for the manufacturing domain.

scholarly journals Management system of smart warehouses using IIoT for optimize inventory control

2021 ◽  
pp. 1-8
Author(s):  
José Esteban Ruiz-Melo ◽  
Irma Martínez-Carrillo ◽  
Carlos Juárez Toledo ◽  
Amador Huitrón-Contreras
Keyword(s):  
Supply Chain ◽  
User Interface ◽  
Internet Of Things ◽  
Real Time ◽  
Management System ◽  
Web Application ◽  
Industrial Internet Of Things ◽  
Strategic Information ◽  
Industrial Internet ◽  
Experimental Management

In the industry, the supply chain develops activities related to the flow of goods. A nerve point of this chain is warehouses, whose operational efficiency allows to minimize product losses and reduce overall costs. This work proposes the automation of a goods warehouse through its integration and interoperation with emerging technologies based on the Industrial Internet of Things (IIoT), with the aim of knowing and planning the stock in real time to optimize its management, since a recurring problem is having outdated inventories, which impact on the lack of traceability of the product. A methodology based on the design of an experimental management system is propose, through RFID devices and a microcontroller allows to monitor the inputs and outputs of goods, the second part of the system is a web application with a user interface where information about inventories could be viewed and analyzed in real time. This research will allow to lay the foundations of automation through IIoT of a warehouse with the purpose of turning it into an intelligent unit that provide strategic information.

Industrial Internet of Things

2020 ◽  
pp. 134-155
Author(s):  
Sema Kayapınar Kaya
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Future Research ◽  
The Internet ◽  
Supply Chain Performance ◽  
Industrial Internet Of Things ◽  
Chain Processes ◽  
Industrial Internet ◽  
Literature Reviews ◽  
The Internet Of Things

Industrial Internet of Things (IIoT) refers to the extension of the Internet of Things and It is used for industrial purposes such as manufacturing, supply chain.IIoT can be connected with billions of industrial devices and machines that supported machine learning and big data technology. Because of its potential to authorize faster and better decision making, the IIoT becomes essential for supply chain processes. The IIoT is set to revolutionize the supply chain with both operational efficiencies and revenue opportunities made possible with just this type of transparency. This study attempts to fill this gap by developing a conceptual framework for predicting the advantage of the IIoT and supply chain performance. This chapter synthesizes existing literature reviews and making bibliometric analysis on the IIoT and supply chain. Additionally, It also outlines avenues and opportunities for future research aiming at the contribution of the IIoT to Supply Chain processes.

Supply Chain Design for the Industrial Internet of Things and the Industry 4.0

2019 ◽  
Author(s):  
Petar Radanliev ◽  
David C. De Roure ◽  
Jason Nurse ◽  
Rafael Mantilla Montalvo ◽  
Pete Burnap
Keyword(s):  
Supply Chain ◽  
Internet Of Things ◽  
Industry 4.0 ◽  
Supply Chain Design ◽  
Industrial Internet Of Things ◽  
Industrial Internet

scholarly journals Internet of Measurement Things Architecture: Proof of Concept with Scope of Accreditation

Sensors ◽  
2020 ◽  
Vol 20 (2) ◽  
pp. 503 ◽  
Author(s):  
M. Cagri Kaya ◽  
Mahdi Saeedi Nikoo ◽  
Michael L. Schwartz ◽  
Halit Oguztuzun
Keyword(s):  
Power Generation ◽  
Cloud Service ◽  
Middle Layer ◽  
Proof Of Concept ◽  
Cloud Platform ◽  
Industrial Internet Of Things ◽  
Industrial Internet ◽  
Architectural Framework ◽  
Measurement Devices ◽  
Calibration Laboratories

Many industries, such as manufacturing, aviation, and power generation, employ sensitive measurement devices to be calibrated by certified experts. The diversity and sophistication of measurement devices and their calibration needs require networked and automated solutions. Internet of Measurement Things (IoMT) is an architectural framework that is based on the Industrial Internet of Things for the calibration industry. This architecture involves a layered model with a cloud-centric middle layer. In this article, the realization of this conceptual architecture is described. The applicability of the IoMT architecture in the calibration industry is shown through an editor application for Scope of Accreditation. The cloud side of the implementation is deployed to Microsoft Azure. The editor itself is created as a cloud service, and IoT Hub is used to collect data from calibration laboratories. By adapting the IoMT architecture to a commonly used cloud platform, considerable progress is achieved to encompass Metrology data and serve the majority of the stakeholders.

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