Making IoT Run

2017 ◽  
Vol 1 (2) ◽  
pp. 26-44
Author(s):  
Peter Schott ◽  
Torben Schaft ◽  
Stefan Thomas ◽  
Freimut Bodendorf
Keyword(s):  
Production Systems ◽  
Smart Manufacturing ◽  
Structural System ◽  
Maturity Level ◽  
Smart Systems ◽  
Industrial Iot ◽  
Increasing Demand ◽  
Manufacturing Environments ◽  
Self Learning

This article describes how today's manufacturing environments are characterized by an increasing demand for individual products and constantly more product variants. Concomitant, developments in the fields of IT, robotics and artificial intelligence allow the realization of smart systems, which means networked, self-learning, self-regulating and versatile production systems to control this complexity. These developments are referred to as industrial IoT that is acknowledged as “next big thing” in production. Firms face the challenge of lacking guidelines for implementing IoT solutions. Neither the technological prerequisites nor generally applicable procedures for realizing an appropriate technological maturity level of the system-to-be exist. Addressing this deficit, a framework is introduced which systematically implements IoT within manufacturing. The framework presents a guideline for the establishment of structural system understanding, the determination of the target system's technological maturity level from a customer's perspective and, building on this, design implications for smart manufacturing.

Making IoT Run

2020 ◽  
pp. 377-397
Author(s):  
Peter Schott ◽  
Torben Schaft ◽  
Stefan Thomas ◽  
Freimut Bodendorf
Keyword(s):  
Artificial Intelligence ◽  
Production Systems ◽  
Smart Manufacturing ◽  
Maturity Level ◽  
Smart Systems ◽  
Industrial Iot ◽  
Increasing Demand ◽  
Manufacturing Environments ◽  
Self Learning

This article describes how today's manufacturing environments are characterized by an increasing demand for individual products and constantly more product variants. Concomitant, developments in the fields of IT, robotics and artificial intelligence allow the realization of smart systems, which means networked, self-learning, self-regulating and versatile production systems to control this complexity. These developments are referred to as industrial IoT that is acknowledged as “next big thing” in production. Firms face the challenge of lacking guidelines for implementing IoT solutions. Neither the technological prerequisites nor generally applicable procedures for realizing an appropriate technological maturity level of the system-to-be exist. Addressing this deficit, a framework is introduced which systematically implements IoT within manufacturing. The framework presents a guideline for the establishment of structural system understanding, the determination of the target system's technological maturity level from a customer's perspective and, building on this, design implications for smart manufacturing.

scholarly journals Guest Editorial: Design Engineering in the Age of Industry 4.0

2021 ◽  
pp. 1-4
Author(s):  
Janet K. Allen ◽  
Sesh Commuri ◽  
Jianxin Jiao ◽  
Jelena Milisavljevic-Syed ◽  
Farrokh Mistree ◽  
...  
Keyword(s):  
Industry 4.0 ◽  
Industrial Revolution ◽  
Production Systems ◽  
Systems Design ◽  
Smart Manufacturing ◽  
Future Research ◽  
Design Engineering ◽  
Production Environment ◽  
Special Issue ◽  
Industrial Iot

Abstract This special issue is motivated by the trend of smart factories of the future towards the fourth Industrial Revolution, which makes it possible to better leverage capabilities and resources in a human-cyber-physical production environment. This emerging paradigm of Industry 4.0 poses new systems design problems at the interface of smart manufacturing, robust and flexible automation, distributed and reconfigurable production systems industrial IoT, and supply chain integration. Recent advances of design engineering in the age of Industry 4.0 are presented in this special issue. More than forty (40) papers were received and peer-reviewed, out of which thirteen (13) papers were selected for publication. These are both theoretical and practical, as well as state-of-the-art reviews, new perspectives, and outlook for future research directions in the field. The papers span a range of design aspects and Industry 4.0 technologies. There are three intersecting clusters in this category: design principles and techniques for Industry 4.0, smart manufacturing technologies, and machine learning and data-driven techniques for Industry 4.0.

Implementation of MQTT protocol based network architecture for smart factory

2021 ◽  
pp. 095440542110144
Author(s):  
Chia-Shin Yeh ◽  
Shang-Liang Chen ◽  
I-Ching Li
Keyword(s):  
Machine Tool ◽  
Gesture Recognition ◽  
Manufacturing Process ◽  
Network Architecture ◽  
Information Management System ◽  
Edge Computing ◽  
Smart Factory ◽  
Smart Manufacturing ◽  
Industrial Iot ◽  
Computing Module

The core concept of smart manufacturing is based on digitization to construct intelligent production and management in the manufacturing process. By digitizing the production process and connecting all levels from product design to service, the purpose of improving manufacturing efficiency, reducing production cost, enhancing product quality, and optimizing user experience can be achieved. To digitize the manufacturing process, IoT technology will have to be introduced into the manufacturing process to collect and analyze process information. However, one of the most important problems in building the industrial IoT (IIoT) environment is that different industrial network protocols are used for different equipment in factories. Therefore, the information in the manufacturing process may not be easily exchanged and obtained. To solve the above problem, a smart factory network architecture based on MQTT (MQ Telemetry Transport), IoT communication protocol, is proposed in this study, to construct a heterogeneous interface communication bridge between the machine tool, embedded device Raspberry Pi, and website. Finally, the system architecture is implemented and imported into the factory, and a smart manufacturing information management system is developed. The edge computing module is set up beside a three-axis machine tool, and a human-machine interface is built for the user controlling and monitoring. Users can also monitor the system through the dynamically updating website at any time and any place. The function of real-time gesture recognition based on image technology is developed and built on the edge computing module. The gesture recognition results can be transmitted to the machine controller through MQTT, and the machine will execute the corresponding action according to different gestures to achieve human-robot collaboration. The MQTT transmission architecture developed here is validated by the given edge computing application. It can serve as the basis for the construction of the IIoT environment, assist the traditional manufacturing industry to prepare for digitization, and accelerate the practice of smart manufacturing.

scholarly journals A DIN Spec 91345 RAMI 4.0 Compliant Data Pipelining Model: An Approach to Support Data Understanding and Data Acquisition in Smart Manufacturing Environments

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 223114-223129
Author(s):  
Kevin Nagorny ◽  
Sebastian Scholze ◽  
Armando Walter Colombo ◽  
Jose Barata Oliveira
Keyword(s):  
Data Acquisition ◽  
Smart Manufacturing ◽  
Manufacturing Environments

Industrial internet of things for smart manufacturing applications using hierarchical trustful resource assignment

Work ◽  
2021 ◽  
pp. 1-11
Author(s):  
Duan Pingli ◽  
Bala Anand Muthu ◽  
Seifedine Nimer Kadry
Keyword(s):  
Internet Of Things ◽  
Manufacturing Industry ◽  
Production Systems ◽  
Intelligent Manufacturing ◽  
Smart Manufacturing ◽  
The Internet ◽  
Resource Assignment ◽  
Industrial Internet Of Things ◽  
Assignment Method ◽  
Industrial Internet

BACKGROUND: The manufacturing industry undergoes a new age, with significant changes taking place on several fronts. Companies devoted to digital transformation take their future plants inspired by the Internet of Things (IoT). The IoT is a worldwide network of interrelated physical devices, which is an essential component of the internet, including sensors, actuators, smart apps, computers, mechanical machines, and people. The effective allocation of the computing resources and the carrier is critical in the industrial internet of Things (IIoT) for smart production systems. Indeed, the existing assignment method in the smart production system cannot guarantee that resources meet the inherently complex and volatile requirements of the user are timely. Many research results on resource allocations in auction formats which have been implemented to consider the demand and real-time supply for smart development resources, but safety privacy and trust estimation issues related to these outcomes are not actively discussed. OBJECTIVES: The paper proposes a Hierarchical Trustful Resource Assignment (HTRA) and Trust Computing Algorithm (TCA) based on Vickrey Clarke-Groves (VGCs) in the computer carriers necessary resources to communicate wirelessly among IIoT devices and gateways, and the allocation of CPU resources for processing information at the CPC. RESULTS: Finally, experimental findings demonstrate that when the IIoT equipment and gateways are valid, the utilities of each participant are improved. CONCLUSION: This is an easy and powerful method to guarantee that intelligent manufacturing components genuinely work for their purposes, which want to integrate each element into a system without interactions with each other.

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.

scholarly journals Robust scheduling and dispatching rules for high-mix collaborative manufacturing systems

2021 ◽  
Author(s):  
Andrea Maria Zanchettin
Keyword(s):  
Manufacturing Systems ◽  
Production Systems ◽  
Adaptive Scheduling ◽  
Dispatching Rules ◽  
Numerical Verification ◽  
Robust Scheduling ◽  
Collaborative Manufacturing ◽  
Processing Times ◽  
Increasing Demand ◽  
Variable Production

AbstractMotivated by the increasing demand of mass customisation in production systems, this paper proposes a robust and adaptive scheduling and dispatching method for high-mix human-robot collaborative manufacturing facilities. Scheduling and dispatching rules are derived to optimally track the desired production within the mix, while handling uncertainty in job processing times. The sequencing policy is dynamically adjusted by online forecasting the throughput of the facility as a function of the scheduling and dispatching rules. Numerical verification experiments confirm the possibility to accurately track highly variable production requests, despite the uncertainty of the system.

Digital Twin for Smart Manufacturing: The Practitioner’s Perspective

2020 ◽  
Author(s):  
Maja Bärring ◽  
Björn Johansson ◽  
Goudong Shao
Keyword(s):  
Conceptual Development ◽  
Production Systems ◽  
Manufacturing Sector ◽  
Smart Manufacturing ◽  
Digital Twin ◽  
Adoption And Implementation ◽  
New Information ◽  
Digital Twins ◽  
Discrete Manufacturing ◽  
Design Production

Abstract The manufacturing sector is experiencing a technological paradigm shift, where new information technology (IT) concepts can help digitize product design, production systems, and manufacturing processes. One of such concepts is Digital Twin and researchers have made some advancement on both its conceptual development and technological implementations. However, in practice, there are many different definitions of the digital-twin concept. These different definitions have created a lot of confusion for practitioners, especially small- and medium-sized enterprises (SMEs). Therefore, the adoption and implementation of the digital-twin concept in manufacturing have been difficult and slow. In this paper, we report our findings from a survey of companies (both large and small) regarding their understanding and acceptance of the digital-twin concept. Five supply-chain companies from discrete manufacturing and one trade organization representing suppliers in the automotive business were interviewed. Their operations have been studied to understand their current digital maturity levels and articulate their needs for digital solutions to stay competitive. This paper presents the results of the research including the viewpoints of these companies in terms of opportunities and challenges for implementing digital twins.

scholarly journals Determination of critical pH and Al concentration of acidic Ultisols for wheat and canola crops

2016 ◽  
Author(s):  
Abdulaha-Al Baquy ◽  
Jiu-Yu Li ◽  
Chen-Yang Xu ◽  
Khalid Mehmood ◽  
Ren-Kou Xu
Keyword(s):  
Soil Ph ◽  
Crop Production ◽  
Soil Acidity ◽  
Production Systems ◽  
Southern China ◽  
Chemical Properties ◽  
Dry Weight ◽  
Hydrated Lime ◽  
Dry Land

Abstract. Soil acidity has become a serious constraint in dry land crop production systems of acidic Ultisols in tropical and subtropical regions of southern China, where winter wheat and canola are cultivated as important rotational crops. Regardless of other common existing concerns in acidic Ultisols of southern China, it needs to be investigated whether soil acidity has any effect on wheat and canola growth. There is little information on the determination of critical soil pH as well as aluminium (Al) concentration for wheat and canola crops. The objective of this study was to determine the critical soil pH and exchangeable aluminium concentration (AlKCl) for wheat and canola production. Two pot cultures with two Ultisols from Hunan and Anhui were conducted for wheat and canola crops in a controlled growth chamber, with a completely randomized design. A soil pH gradient ranging from 3.7 (Hunan) and 3.97 (Anhui) to 6.5, with three replications, was used as a treatment. Aluminium sulfate (Al2(SO4)3) and hydrated lime (Ca(OH)2) were used to obtain the target soil pH levels. Plant height, shoot dry weight, root dry weight, and chlorophyll content (SPAD value) of wheat and canola were adversely affected by soil acidity in both locations. The critical soil pH and AlKCl of the Ultisol from Hunan for wheat were 5.29 and 0.56 cmol kg−1, respectively. At Anhui, the threshold soil pH and AlKCl for wheat were 4.66 and 2.36 cmol kg−1, respectively. On the other hand, the critical soil pH for canola was 5.65 and 4.87 for the Ultisols from Hunan and Anhui, respectively. The critical soil exchangeable Al for canola cannot be determined from the experiment of this study. The results suggested that the critical soil pH and AlKCl varied between different locations for the same variety of crop, due to the different soil types and their other soil chemical properties. The critical soil pH for canola was higher than that for wheat for both Ultisols, thus canola was more sensitive to soil acidity. Therefore, we recommend that liming should be undertaken to increase soil pH if it falls below these critical soil pH levels for wheat and canola production.

scholarly journals Evolution and accumulation of C-CO2 in biogenic and physiogenic aggregates of different agroecological management systems

2018 ◽  
Vol 67 (4) ◽  
pp. 494-500
Author(s):  
Luiz Alberto Silva Rodrigues Pinto ◽  
Octávio Vioratti Telles Mendonça ◽  
Celeste Queiroz Rossi ◽  
Marcos Gervasio Pereira ◽  
Fabiana Costa Barros
Keyword(s):  
Production Systems ◽  
Agroforestry System ◽  
Management Systems ◽  
Formation Pathway ◽  
No Till ◽  
Testing Parameter ◽  
Mineralizable Carbon ◽  
The City ◽  
Som Decomposition

Determination of mineralizable carbon (C) is based on the evolution of C-CO2, reflecting the activity of soil biota in soil organic matter (SOM) decomposition, and can be used as a testing parameter in agroecological production systems. The objective of the present work was to quantify mineralizable C in aggregates of different biogenic and physiogenic formation pathways in agroecological management systems in the city of Seropédica, state of Rio de Janeiro. Five sampling areas were selected: (1) 10-year agroforestry system (AFS), (2) 15-year full sun coffee (C-SUN), (3) 15-year shaded coffee (C-SHA), (4) 10-year phlegm alleles (FLE), and (5) 6-year no-till planting system with corn and eggplant (NT) in Red-Yellow Argissolo in Seropédica-RJ.Morphological patterns were used to identify the formation pathway (biogenic and physiogenic) of aggregates.  In these, fertility, total organic carbon (TOC), and total nitrogen (TN) were evaluated.  The evolution and accumulation of C-CO2were determined in the laboratory after 35 days of incubation. The NT area under agroecological management present higher C-CO2 accumulation between the systems with biogenic aggregates and less accumulation in the physiogenic aggregates. 

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