The document discusses smart manufacturing and its key enablers. It describes how smart manufacturing utilizes technologies like big data analysis, industrial IoT, blockchain, robotics, and digital twins to optimize manufacturing processes. A smart factory is presented as the vision of highly automated production facilitated by cyber-physical systems and the exchange of digital information. The advantages of smart manufacturing include increased productivity and efficiency through predictive maintenance and flexibility, while the main disadvantage is the upfront cost of implementation.
Smart manufacturing is a fully integrated, collaborative manufacturing system that responds in real-time to changing demands through the connection of hardware, software, and people over the internet. It offers benefits like optimal resource use, higher customer satisfaction through customized products, and greater innovation. However, risks include safety issues, challenges with change management as new skills are needed, potential adverse social impacts, concerns over business continuity and security from increased connectivity and complexity. Digital technologies that enable smart manufacturing include machine learning, artificial intelligence, and real-time interaction across organizations.
Introduction to Smart Manufacturing & Manufacturing as a Service presentation.
Three important concepts are presented: Cloud computing, internet of things and advanced data analytics.
This document discusses Industry 4.0 and smart manufacturing. It describes how Industry 4.0 involves integrating smart devices, turning products into smart products, and transforming factories into smart, connected factories. Key aspects of Industry 4.0 include products being described by models and having standardized network interfaces. The document outlines benefits of Industry 4.0 such as helping companies keep production in countries like India and compete globally through more efficient, customized production. Barriers and enablers to smart manufacturing are also presented, such as integrating customer data and demand across supply chains.
Intelligent Manufacturing is a Smart Choice to gain on competitiveness and sustainability. Innovation technologies to boost productivity and visibility of manufacturing opearations.
Industry 4.0 is a name given to the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things, cloud computing and cognitive computing. Industry 4.0 is commonly referred to as the fourth industrial revolution.
Industry 4.0 promises great increase in productivity and profitability. This presentation covers the basics of this new manufacturing approach and it separates facts from fiction.
Smart manufacturing is a fully integrated, collaborative manufacturing system that responds in real-time to changing demands through the connection of hardware, software, and people over the internet. It offers benefits like optimal resource use, higher customer satisfaction through customized products, and greater innovation. However, risks include safety issues, challenges with change management as new skills are needed, potential adverse social impacts, concerns over business continuity and security from increased connectivity and complexity. Digital technologies that enable smart manufacturing include machine learning, artificial intelligence, and real-time interaction across organizations.
Introduction to Smart Manufacturing & Manufacturing as a Service presentation.
Three important concepts are presented: Cloud computing, internet of things and advanced data analytics.
This document discusses Industry 4.0 and smart manufacturing. It describes how Industry 4.0 involves integrating smart devices, turning products into smart products, and transforming factories into smart, connected factories. Key aspects of Industry 4.0 include products being described by models and having standardized network interfaces. The document outlines benefits of Industry 4.0 such as helping companies keep production in countries like India and compete globally through more efficient, customized production. Barriers and enablers to smart manufacturing are also presented, such as integrating customer data and demand across supply chains.
Intelligent Manufacturing is a Smart Choice to gain on competitiveness and sustainability. Innovation technologies to boost productivity and visibility of manufacturing opearations.
Industry 4.0 is a name given to the current trend of automation and data exchange in manufacturing technologies. It includes cyber-physical systems, the Internet of things, cloud computing and cognitive computing. Industry 4.0 is commonly referred to as the fourth industrial revolution.
Industry 4.0 promises great increase in productivity and profitability. This presentation covers the basics of this new manufacturing approach and it separates facts from fiction.
Impact for Educational Institutions, Internet of things, Digital Enablers, New Age Production, Smart Factory, New digital industrial technology, Interdisciplinary Thinking, Digital Work Place, 3d printing,
This document discusses Industry 4.0 and smart factories. It begins by outlining the stages of the industrial revolution and key technologies of Industry 4.0 like IoT, cloud computing, and augmented reality. It then describes the philosophy of Industry 4.0, including how new information technologies can help address sustainability issues. System architectures for smart factories are presented, involving physical resources connected through an industrial network to cloud systems and supervision terminals. Technical challenges of implementing smart factories are discussed, along with examples of smart factory prototypes and their benefits.
The document discusses Industry 4.0 and how it is changing manufacturing through increased digitization, automation, data collection and analysis. Industry 4.0 utilizes cyber-physical systems where machines can self-optimize, communicate with each other and optimize overall production. This leads to benefits like increased operational efficiency, new products/services, and an outcome-based economy where payment is tied to results rather than goods/services. By 2020, over 1 billion connected objects will equip factories, representing over 55% annual growth in connected devices.
The document discusses the four industrial revolutions: Industry 1.0 focused on mechanization, Industry 2.0 added electrical power, Industry 3.0 brought digital technology, and Industry 4.0 integrates cyber-physical systems using IoT, cloud, and cognitive computing. Industry 4.0 enables technologies like augmented reality, big data analytics, autonomous robots, additive manufacturing, simulation, system integration, and cybersecurity. It aims for interconnected smart factories through technologies that enable interoperability, transparency, assistance, and decentralized decision making.
The fourth industrial revolution Industry 4.0 represents a new paradigm shift from “centralized” to “decentralized” industry relies on cyber-physical based automation where sensors send data directly to the cloud and services such as monitoring, control and optimization automatically subscribe to necessary data in real-time. In the coming years, these technologies will be seen as a viable alternative to current manufacturing processes. According to a recent report by Markets and Markets, smart factory technology will have global market size of 74.80 Billion USD by 2022. The talk provides a comprehensive introduction to Industry 4.0 and Smart Factory. Technical challenges and social implications of smart factory will be discussed. The applicability of these emerging technologies in developing economies is highlighted in this talk as well.
IOT IN MANUFACTURING , ndustrial Internet of Things (IIoT) is going full throttle – increasing connectivity, generating data, and unlocking potential like never before. Now it’s time to capitalize on the full power of this data. Altair knows how to take full advantage of data to fuel innovation, drive new opportunities, and accelerate your smart manufacturing transformation.
This document discusses Industry 4.0, which refers to a new phase in the Industrial Revolution that focuses on interconnectivity, automation, machine learning, and real-time data. The document outlines the key aspects of Industry 4.0, including cyber-physical systems, the Internet of Things, cloud computing, cognitive computing, and how these technologies are driving changes in manufacturing through customized mass production and independent machine operations. It also discusses some of the potential benefits and challenges of Industry 4.0, such as improved productivity and optimization versus issues relating to job losses, security, and the need for retraining of workers.
This document discusses Industrie 4.0, the fourth industrial revolution bringing connectivity and intelligence to manufacturing through technologies like the Internet of Things. Key concepts are connecting physical devices to networks and machines interacting with each other to enable mass customization. This transformation integrates horizontal and vertical networking in factories. Six design principles are outlined: interoperability, virtualization, decentralization, real-time capability, service orientation, and modularity. Diagrams show examples of smart factories and supply chains enabled by Industrie 4.0.
This document discusses Industry 4.0 and the future of work and skills. It provides a historical view of the four industrial revolutions from the late 18th century to today. Industry 4.0 is characterized by technologies like cloud computing, artificial intelligence, big data analytics, the internet of things, robotics, and more. Examples are given of how companies like Siemens, Trumpf, and GE are implementing Industry 4.0. The document also discusses research findings from NASSCOM/EY on future skills and new professions needed for Industry 4.0 like analytical thinking, collaboration, and technology design. It concludes with questions about the future of work and skills.
Industry 4.0 represents the fourth industrial revolution in manufacturing and industry. Industry 4.0 is the current industrial transformation with automation, data exchanges, cloud, cyber-physical systems, robots, Big Data, AI, IoT and (semi-)autonomous industrial techniques to realize smart industry and manufacturing goals in the intersection of people, new technologies and innovation. IoT (Internet of Things), the convergence of IT and OT, rapid application development, digital twin simulation models, cyber-physical systems, advanced robots and cobots, additive manufacturing, autonomous production, consistent engineering across the entire value chain, thorough data collection and provisioning, horizontal and vertical integration, the cloud, big data analytics, virtual/augmented reality and edge computing amidst a shift of intelligence towards the edge (artificial intelligence indeed with a convergence of AI and IoT and other technologies): these are some of the essential technological components of the fourth industrial revolution. Those are quite a lot of terms and components indeed. Yet, Industry 4.0 is a rather vast vision and, increasingly, a vast reality that also stretches beyond merely these technological aspects. It is an end-to-end industrial transformation.
From the first British Industrial Revolution to the Fourth Industry Revolution otherwise known as industry 4.0, there has been continuous digitalization revolution that is changing the way we live, interact and communicates as well as transacting. Today manufacturing companies are moving away from mass production to mass customization production due to radical transformation of technological advancement which is revolutionizing the entire industry. The world is witnessing radical transformation that is changing the landscape of manufacturing industry. With the industry 4.0 begins to take shape, traditional manufacturing is in the zenith of radical digital transformation.
ARE YOU READY FOR THE RADICAL TRANSFORMATION OF THE INDUSTRY OF THE FUTURE (INDUSTRY 4.0)
This document discusses Industry 4.0, the fourth industrial revolution brought about by emerging technologies that are driving the next wave of innovation in manufacturing. It notes that there have been three previous revolutions driven by steam power, electricity, and automation. Industry 4.0 is characterized by four disruptions: digital-to-physical conversion enabled by advances in areas like 3D printing, robotics, and AI; new human-machine interfaces like augmented reality; analytics powered by machine learning and big data; and increased connectivity and data driven by lower computing and connectivity costs. The document outlines both the potential benefits of Industry 4.0, as well as challenges manufacturers face in developing necessary digital capabilities to realize this potential.
The document discusses Industry 4.0, which refers to the combination of digital technologies transforming manufacturing, including robotics, AI, sensors, IoT, analytics, and more. It describes how these technologies are poised to reshape manufacturing through interconnected global value chains and smart factories. The document outlines the main Industry 4.0 principles of interoperability, transparency, assistance, and decentralized decisions. It also discusses the impacts on employees, value chains, investments, and use cases combining Industry 4.0 with lean production. Experts comment that Industry 4.0 has great potential through data-driven applications tailored for customers to automate processes and monitoring.
This document provides an overview of Industry 4.0, which represents the fourth industrial revolution through increased automation and data exchange in manufacturing technologies. It discusses enabling technologies like cyber-physical systems, the internet of things, and cloud computing. Key principles of Industry 4.0 include interoperability, decentralization, real-time capability and modularity. Examples are given of Industry 4.0 implementations by companies like Siemens, Trumpf, and General Electric.
Intelligent Manufacturing system Final 1Harish Pant
1. The document discusses intelligent manufacturing systems and Industry 4.0, describing how increased connectivity through technologies like the Internet of Things, cyber-physical systems, and sensors is allowing for more customized, flexible production and new areas of innovation.
2. Key aspects of Industry 4.0 include deep learning, quantum computing, advanced artificial intelligence, new IOT platforms, cloud-based analytics services, and partner ecosystems to deliver IOT solutions.
3. Examples are given of new technologies like autonomous robotic systems from companies like Festo and ABB, as well as smart factory approaches from German research initiatives and automakers like Volkswagen integrating digital technologies into new products and customized, digitally-driven production.
Industry 4.0 takes automation to a new level with customized and flexible mass production technologies. It involves machines operating independently by collecting and analyzing data to advise themselves. Key building blocks include autonomous robots, simulation, integration of horizontal and vertical systems, industrial internet of things, cyber security, additive manufacturing, augmented reality, and big data analytics. ERP systems play a role in Industry 4.0 by reducing manufacturing lead times, enabling real-time data processing and decision making, reducing data processing times through IoT and cloud, and integrating communication between raw materials and equipment as well as the whole value chain with customers and suppliers.
Industry 4.0 Technology signifies the conception of the fourth industrial revolution. The previous three revolutions in the Industry sphere are Mechanical Production, Mass Production, and Digital Transformation. While it can be said that the Smart Factory Industry 4.0 is a mix of the previous three revolutions, however, it is much more effective than that.
Launching in April 2016, Smart Manufacturing will focus on advanced manufacturing technologies and tools that are driven or enhanced by integrated information technology.
IOT Development in Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations and boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
IoT Development In Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations & boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
Impact for Educational Institutions, Internet of things, Digital Enablers, New Age Production, Smart Factory, New digital industrial technology, Interdisciplinary Thinking, Digital Work Place, 3d printing,
This document discusses Industry 4.0 and smart factories. It begins by outlining the stages of the industrial revolution and key technologies of Industry 4.0 like IoT, cloud computing, and augmented reality. It then describes the philosophy of Industry 4.0, including how new information technologies can help address sustainability issues. System architectures for smart factories are presented, involving physical resources connected through an industrial network to cloud systems and supervision terminals. Technical challenges of implementing smart factories are discussed, along with examples of smart factory prototypes and their benefits.
The document discusses Industry 4.0 and how it is changing manufacturing through increased digitization, automation, data collection and analysis. Industry 4.0 utilizes cyber-physical systems where machines can self-optimize, communicate with each other and optimize overall production. This leads to benefits like increased operational efficiency, new products/services, and an outcome-based economy where payment is tied to results rather than goods/services. By 2020, over 1 billion connected objects will equip factories, representing over 55% annual growth in connected devices.
The document discusses the four industrial revolutions: Industry 1.0 focused on mechanization, Industry 2.0 added electrical power, Industry 3.0 brought digital technology, and Industry 4.0 integrates cyber-physical systems using IoT, cloud, and cognitive computing. Industry 4.0 enables technologies like augmented reality, big data analytics, autonomous robots, additive manufacturing, simulation, system integration, and cybersecurity. It aims for interconnected smart factories through technologies that enable interoperability, transparency, assistance, and decentralized decision making.
The fourth industrial revolution Industry 4.0 represents a new paradigm shift from “centralized” to “decentralized” industry relies on cyber-physical based automation where sensors send data directly to the cloud and services such as monitoring, control and optimization automatically subscribe to necessary data in real-time. In the coming years, these technologies will be seen as a viable alternative to current manufacturing processes. According to a recent report by Markets and Markets, smart factory technology will have global market size of 74.80 Billion USD by 2022. The talk provides a comprehensive introduction to Industry 4.0 and Smart Factory. Technical challenges and social implications of smart factory will be discussed. The applicability of these emerging technologies in developing economies is highlighted in this talk as well.
IOT IN MANUFACTURING , ndustrial Internet of Things (IIoT) is going full throttle – increasing connectivity, generating data, and unlocking potential like never before. Now it’s time to capitalize on the full power of this data. Altair knows how to take full advantage of data to fuel innovation, drive new opportunities, and accelerate your smart manufacturing transformation.
This document discusses Industry 4.0, which refers to a new phase in the Industrial Revolution that focuses on interconnectivity, automation, machine learning, and real-time data. The document outlines the key aspects of Industry 4.0, including cyber-physical systems, the Internet of Things, cloud computing, cognitive computing, and how these technologies are driving changes in manufacturing through customized mass production and independent machine operations. It also discusses some of the potential benefits and challenges of Industry 4.0, such as improved productivity and optimization versus issues relating to job losses, security, and the need for retraining of workers.
This document discusses Industrie 4.0, the fourth industrial revolution bringing connectivity and intelligence to manufacturing through technologies like the Internet of Things. Key concepts are connecting physical devices to networks and machines interacting with each other to enable mass customization. This transformation integrates horizontal and vertical networking in factories. Six design principles are outlined: interoperability, virtualization, decentralization, real-time capability, service orientation, and modularity. Diagrams show examples of smart factories and supply chains enabled by Industrie 4.0.
This document discusses Industry 4.0 and the future of work and skills. It provides a historical view of the four industrial revolutions from the late 18th century to today. Industry 4.0 is characterized by technologies like cloud computing, artificial intelligence, big data analytics, the internet of things, robotics, and more. Examples are given of how companies like Siemens, Trumpf, and GE are implementing Industry 4.0. The document also discusses research findings from NASSCOM/EY on future skills and new professions needed for Industry 4.0 like analytical thinking, collaboration, and technology design. It concludes with questions about the future of work and skills.
Industry 4.0 represents the fourth industrial revolution in manufacturing and industry. Industry 4.0 is the current industrial transformation with automation, data exchanges, cloud, cyber-physical systems, robots, Big Data, AI, IoT and (semi-)autonomous industrial techniques to realize smart industry and manufacturing goals in the intersection of people, new technologies and innovation. IoT (Internet of Things), the convergence of IT and OT, rapid application development, digital twin simulation models, cyber-physical systems, advanced robots and cobots, additive manufacturing, autonomous production, consistent engineering across the entire value chain, thorough data collection and provisioning, horizontal and vertical integration, the cloud, big data analytics, virtual/augmented reality and edge computing amidst a shift of intelligence towards the edge (artificial intelligence indeed with a convergence of AI and IoT and other technologies): these are some of the essential technological components of the fourth industrial revolution. Those are quite a lot of terms and components indeed. Yet, Industry 4.0 is a rather vast vision and, increasingly, a vast reality that also stretches beyond merely these technological aspects. It is an end-to-end industrial transformation.
From the first British Industrial Revolution to the Fourth Industry Revolution otherwise known as industry 4.0, there has been continuous digitalization revolution that is changing the way we live, interact and communicates as well as transacting. Today manufacturing companies are moving away from mass production to mass customization production due to radical transformation of technological advancement which is revolutionizing the entire industry. The world is witnessing radical transformation that is changing the landscape of manufacturing industry. With the industry 4.0 begins to take shape, traditional manufacturing is in the zenith of radical digital transformation.
ARE YOU READY FOR THE RADICAL TRANSFORMATION OF THE INDUSTRY OF THE FUTURE (INDUSTRY 4.0)
This document discusses Industry 4.0, the fourth industrial revolution brought about by emerging technologies that are driving the next wave of innovation in manufacturing. It notes that there have been three previous revolutions driven by steam power, electricity, and automation. Industry 4.0 is characterized by four disruptions: digital-to-physical conversion enabled by advances in areas like 3D printing, robotics, and AI; new human-machine interfaces like augmented reality; analytics powered by machine learning and big data; and increased connectivity and data driven by lower computing and connectivity costs. The document outlines both the potential benefits of Industry 4.0, as well as challenges manufacturers face in developing necessary digital capabilities to realize this potential.
The document discusses Industry 4.0, which refers to the combination of digital technologies transforming manufacturing, including robotics, AI, sensors, IoT, analytics, and more. It describes how these technologies are poised to reshape manufacturing through interconnected global value chains and smart factories. The document outlines the main Industry 4.0 principles of interoperability, transparency, assistance, and decentralized decisions. It also discusses the impacts on employees, value chains, investments, and use cases combining Industry 4.0 with lean production. Experts comment that Industry 4.0 has great potential through data-driven applications tailored for customers to automate processes and monitoring.
This document provides an overview of Industry 4.0, which represents the fourth industrial revolution through increased automation and data exchange in manufacturing technologies. It discusses enabling technologies like cyber-physical systems, the internet of things, and cloud computing. Key principles of Industry 4.0 include interoperability, decentralization, real-time capability and modularity. Examples are given of Industry 4.0 implementations by companies like Siemens, Trumpf, and General Electric.
Intelligent Manufacturing system Final 1Harish Pant
1. The document discusses intelligent manufacturing systems and Industry 4.0, describing how increased connectivity through technologies like the Internet of Things, cyber-physical systems, and sensors is allowing for more customized, flexible production and new areas of innovation.
2. Key aspects of Industry 4.0 include deep learning, quantum computing, advanced artificial intelligence, new IOT platforms, cloud-based analytics services, and partner ecosystems to deliver IOT solutions.
3. Examples are given of new technologies like autonomous robotic systems from companies like Festo and ABB, as well as smart factory approaches from German research initiatives and automakers like Volkswagen integrating digital technologies into new products and customized, digitally-driven production.
Industry 4.0 takes automation to a new level with customized and flexible mass production technologies. It involves machines operating independently by collecting and analyzing data to advise themselves. Key building blocks include autonomous robots, simulation, integration of horizontal and vertical systems, industrial internet of things, cyber security, additive manufacturing, augmented reality, and big data analytics. ERP systems play a role in Industry 4.0 by reducing manufacturing lead times, enabling real-time data processing and decision making, reducing data processing times through IoT and cloud, and integrating communication between raw materials and equipment as well as the whole value chain with customers and suppliers.
Industry 4.0 Technology signifies the conception of the fourth industrial revolution. The previous three revolutions in the Industry sphere are Mechanical Production, Mass Production, and Digital Transformation. While it can be said that the Smart Factory Industry 4.0 is a mix of the previous three revolutions, however, it is much more effective than that.
Launching in April 2016, Smart Manufacturing will focus on advanced manufacturing technologies and tools that are driven or enhanced by integrated information technology.
IOT Development in Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations and boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
IoT Development In Manufacturing A Guide to Industrial Digital Transformation...Laura Miller
IoT helps manufacturers to streamline operations & boost productivity with ease. Read the blog to know how the IoT development brings digital transformation.
Designing for Manufacturing's 'Internet of Things'Cognizant
The deeper meshing of virtual and physical machines offers the potential to truly transform the manufacturing value chain, from suppliers through customers, and at every touchpoint along the way.
This document provides definitions for various terms related to Industry 4.0, the Industrial Internet of Things (IIoT), and digital transformation in manufacturing. It includes definitions for over 50 terms in its second edition of "The MachineMetrics IIoT Manufacturing Dictionary." The dictionary is intended to help those new to digital manufacturing concepts and terminology better understand commonly used buzzwords and technologies in this field.
Industrial IoT: The Essentials of Implementing a SolutionNoman Shaikh
The Industrial Internet of Things (IIoT) is a relatively new idea that has the potential to offer value to any industrial organisation that decides to embrace it. Due to the newness of IoT in industrial operations, there has been a rise in cost and maturity in terms of data processing, as well as just a few deployments.
Industrial Internet of things has continued to create the buzz, one can’t deny that it is the one of the fastest emerging technology with humpty amount of Data getting captured daily and with every industry demanding optimisation, analytics, automations and valuable insights Industrial Internet of things is something which the need of the day.
Automated Testing Services | Verification and Validation Services | Utthunga Utthunga's automated software testing services in Industry 4.0 assures maximum test coverage and product quality with its comprehensive software testing process. We provide comprehensive verification and validation services comprising of test strategy, test automation, etc. Find out more! https://utthunga.com/product-engineering/quality-engineering/
Advanced Manufacturing – Solutions That Are Transforming the IndustryMRPeasy
Advanced manufacturing is on its way to transform the industry. And there are solutions in place already that could help even small manufacturers keep up in the rapidly changing business environments.
IIoT definition. The IIoT consists of internet-connected machinery and the advanced analytics platforms that process the data they produce. IIoT devices range from tiny environmental sensors to complex industrial robots.
Industrial IoT has many applications in manufacturing including:
1. Connecting machinery to remotely manage factory units and identify key performance areas.
2. Using sensors to monitor equipment condition and trigger maintenance alerts to reduce downtime.
3. Real-time monitoring of production lines to eliminate waste and optimize costs.
4. Tracking inventory globally to improve supply chain visibility and reduce costs.
IoT Application in Manufacturing & Advantage , Disadvantage.GHANASHYAM19
The document discusses how IoT can be applied in manufacturing. It describes how IoT enables digital/connected factories through remote monitoring and management of machinery. IoT sensors also allow for condition-based maintenance alerts and facility management. Production flow, inventory, plant safety and security, quality control, packaging, and logistics can all be optimized through IoT applications in manufacturing. The advantages include asset tracking, predictive maintenance, and process monitoring, while the disadvantages include security risks, high costs, and potential connectivity issues.
IIoT is the next level of IoT technology and is unique in the way its application has completely transformed manufacturing. Companies today that are looking for a competitive advantage need look no further than the capabilities that IIoT affords you – the benefits impact everything from maintenance to supplier logistics to employee workflows to product delivery.
Smart Manufacturing: A Revolution in Industry 4.0 | Enterprise WiredEnterprise Wired
This article explores the multifaceted landscape of smart manufacturing, delving into its key principles, transformative technologies, applications across various industries, and the profound impact it has on shaping the future of manufacturing.
this is the basic slide for the introduction of Industry 4.0. how this works and what are the foundations required for the working of the indusry as it is taking globally a huge transformation.
Informed Manufacturing: The Next Industrial RevolutionCognizant
" 'Intelligent machines' enable people, processes, products and infrastructure to seamlessly coordinate, creating cost-efficient finished goods on time, that meet, if not exceed customer expectations"
The document discusses how small businesses can benefit from using IoT technologies. It outlines several ways IoT can reduce costs and increase profits for small businesses, including remote monitoring of operations, improved inventory management through sensors and RFID chips, and overall increased efficiencies and productivity through data analytics. However, the document also notes security concerns that come with increased connectivity and the need for small businesses to have proper infrastructure and expertise to successfully integrate IoT.
The document discusses how small businesses can benefit from using IoT technologies. It outlines several ways IoT can reduce costs and increase profits, including remote monitoring of operations to allow 24/7 production, inventory management through sensors and RFID chips, and overall efficiency improvements from big data analytics. While IoT provides opportunities, small businesses need the right infrastructure and expertise to securely integrate these new technologies.
The document discusses how small business owners can benefit from using IoT technologies. It outlines several ways IoT can help small businesses, including remote monitoring of operations to allow 24/7 production, inventory management through sensors and RFID chips, and overall improved efficiencies from big data analytics. The document also notes that while IoT provides benefits, it also presents security and management challenges that businesses need to address.
ACEP Magazine edition 4th launched on 05.06.2024Rahul
This document provides information about the third edition of the magazine "Sthapatya" published by the Association of Civil Engineers (Practicing) Aurangabad. It includes messages from current and past presidents of ACEP, memories and photos from past ACEP events, information on life time achievement awards given by ACEP, and a technical article on concrete maintenance, repairs and strengthening. The document highlights activities of ACEP and provides a technical educational article for members.
Advanced control scheme of doubly fed induction generator for wind turbine us...IJECEIAES
This paper describes a speed control device for generating electrical energy on an electricity network based on the doubly fed induction generator (DFIG) used for wind power conversion systems. At first, a double-fed induction generator model was constructed. A control law is formulated to govern the flow of energy between the stator of a DFIG and the energy network using three types of controllers: proportional integral (PI), sliding mode controller (SMC) and second order sliding mode controller (SOSMC). Their different results in terms of power reference tracking, reaction to unexpected speed fluctuations, sensitivity to perturbations, and resilience against machine parameter alterations are compared. MATLAB/Simulink was used to conduct the simulations for the preceding study. Multiple simulations have shown very satisfying results, and the investigations demonstrate the efficacy and power-enhancing capabilities of the suggested control system.
Understanding Inductive Bias in Machine LearningSUTEJAS
This presentation explores the concept of inductive bias in machine learning. It explains how algorithms come with built-in assumptions and preferences that guide the learning process. You'll learn about the different types of inductive bias and how they can impact the performance and generalizability of machine learning models.
The presentation also covers the positive and negative aspects of inductive bias, along with strategies for mitigating potential drawbacks. We'll explore examples of how bias manifests in algorithms like neural networks and decision trees.
By understanding inductive bias, you can gain valuable insights into how machine learning models work and make informed decisions when building and deploying them.
KuberTENes Birthday Bash Guadalajara - K8sGPT first impressionsVictor Morales
K8sGPT is a tool that analyzes and diagnoses Kubernetes clusters. This presentation was used to share the requirements and dependencies to deploy K8sGPT in a local environment.
Using recycled concrete aggregates (RCA) for pavements is crucial to achieving sustainability. Implementing RCA for new pavement can minimize carbon footprint, conserve natural resources, reduce harmful emissions, and lower life cycle costs. Compared to natural aggregate (NA), RCA pavement has fewer comprehensive studies and sustainability assessments.
Adaptive synchronous sliding control for a robot manipulator based on neural ...IJECEIAES
Robot manipulators have become important equipment in production lines, medical fields, and transportation. Improving the quality of trajectory tracking for
robot hands is always an attractive topic in the research community. This is a
challenging problem because robot manipulators are complex nonlinear systems
and are often subject to fluctuations in loads and external disturbances. This
article proposes an adaptive synchronous sliding control scheme to improve trajectory tracking performance for a robot manipulator. The proposed controller
ensures that the positions of the joints track the desired trajectory, synchronize
the errors, and significantly reduces chattering. First, the synchronous tracking
errors and synchronous sliding surfaces are presented. Second, the synchronous
tracking error dynamics are determined. Third, a robust adaptive control law is
designed,the unknown components of the model are estimated online by the neural network, and the parameters of the switching elements are selected by fuzzy
logic. The built algorithm ensures that the tracking and approximation errors
are ultimately uniformly bounded (UUB). Finally, the effectiveness of the constructed algorithm is demonstrated through simulation and experimental results.
Simulation and experimental results show that the proposed controller is effective with small synchronous tracking errors, and the chattering phenomenon is
significantly reduced.
HEAP SORT ILLUSTRATED WITH HEAPIFY, BUILD HEAP FOR DYNAMIC ARRAYS.
Heap sort is a comparison-based sorting technique based on Binary Heap data structure. It is similar to the selection sort where we first find the minimum element and place the minimum element at the beginning. Repeat the same process for the remaining elements.
Introduction- e - waste – definition - sources of e-waste– hazardous substances in e-waste - effects of e-waste on environment and human health- need for e-waste management– e-waste handling rules - waste minimization techniques for managing e-waste – recycling of e-waste - disposal treatment methods of e- waste – mechanism of extraction of precious metal from leaching solution-global Scenario of E-waste – E-waste in India- case studies.
1. BIRLA INSTITUTE OF TECHNOLOGY
PRESENTATION OF
SMART MANUFACTURING
ON
SMART MANUFACTURING
BY,
NAWAL SINHA
MT/EE/10024/19
2. CONTENTS
INTRODUCTION
WHAT ARE ENABLERS ?
BIG DATA ANALYSIS IN SM
INDUSTRIAL INTERNET OFTHINGS
BLOCK CHAIN MANUFACTURING
ADANCED ROBOTICS
DIGITALTWIN
SMART FACTORY
ADVANTAGES AND DISADVANTAGES
CONCLUSION
REFERENCES
3. INTRODUCTION
Smart manufacturing is a broad category of manufacturing that
employs computer integrated manufacturing, high levels of
adaptability and rapid design changes, digital information
technology, and more flexible technical workforce training.
Other goals sometimes include fast changes in production
levels based on demand, optimization of the supply chain,
efficient production and recyclability
Smart manufacturing (SM) is a technology-driven approach
that utilizes Internet-connected machinery to monitor the
production process. The goal of SM is to identify opportunities
for automating operations and use data to improve
manufacturing performance.
4. SM is a specific application of the Industrial Internet of
Things (IIoT). Deployments involve embedding sensors in
manufacturing machines to collect data on their operational
status and performance. In the past, that information typically
was kept in local databases on individual devices.
Now, by analyzing the data manufacturing engineers and data
analysts can look for signs that particular parts may fail,
enabling preventive maintenance to avoid unplanned
downtime on devices.
For example, SM systems might be able to automatically
order more raw materials as the supplies, allocate other
equipment to production jobs as needed to complete orders
and prepare distribution networks once orders are completed.
5. WHAT ARE ENABLERS ?
Smart manufacturing is a combination of various technologies and
solutions which collectively, if implemented in a manufacturing
ecosystem, then termed as smart manufacturing.
We call these technologies and solutions "enablers," which help in
optimizing the entire manufacturing process and thus increase overall
profits.
Some of the prominent enablers in the current market scenario include:
Artificial intelligence
Block chain in manufacturing
Industrial internet of things
Robotics
Condition monitoring
Cyber security
6. Big Data Analysis in SM
Smart manufacturing utilizes big data, to refine complicated
processes and manage supply chain .
Big data analytics refers to a method for gathering and
understanding large data sets in terms of what are known as
the three V's, velocity, variety and volume.
Velocity informs the frequency of data acquisition, which can
be concurrent with the application of previous data.
Variety describes the different types of data that may be
handled. Volume represents the amount of data.
Big data analytics allows an enterprise to use smart
manufacturing to predict demand and the need for design
changes rather than reacting to orders placed.
7. Artificial intelligence/machine learning – The data generated from
big data processing enables automatic decision-making based on the
reams of data that manufacturing companies collect. AI/ML can
analyze all this data and make intelligent decisions based on the
inputted information.
Fig. 1:Real time monitoring using data analytics
From the above fig. we can say analyze how data analytics is being
used for the inspection of product quality. If there is any problem
with the quality then the signals are send to identify problem and
then again rework is done.
8. INDUSTRIAL IoT (IIoT)
IIoT is nothing but an ecosystem where every device, machine
and/or process is connected through data communication
systems.
Each machine and piece of industrial equipment is embedded
or connected with sensors which typically generate the
relevant data.
This is further transferred to the cloud/software systems.
This huge amount of data has lots of insight which if analyzed
may help in identifying certain dark areas within the
production process.
After the analysis of the data, it is sent as feedback to the
production systems for any corrective action.
Major forces driving IoT in market are the growing need for
centralized monitoring and predictive maintenance of
manufacturing infrastructure.
9. The increasing need for agile production, operational efficiency, and
control, and demand-driven supply chain and connected logistics are
also expected to drive the market.
Fig 2: IIoT in factories
From the above figure we can see that how the majority of work in a
factory is being done by the cobots and all the data is there in predictive
analysis. There are IoT sensors that are used to detect whether the
equipment is correct or not and then packaging is done by cobots.
10. Block Chain Manufacturing
Block chain can act as a “single source of truth” for all the entities
(subsidiaries, partners, etc.) doing purchases on your behalf and
negotiating different terms with suppliers.
A block chain-based database can store relevant data from all the
partners, giving the company a 360-view of the total volume of
purchases, regardless of who managed the purchase activity.
There will be no need for individual users to constantly share
operational data and someone else to crosscheck it — the audits will
be conducted automatically, eliminating the resource-heavy
processes such as extra price verification.
Some of the industries that are actively developing block chain
include apparel, solar energy, mining, fishing, food & beverage,
shipping (cargo transportation), fertilizer, healthcare and aviation.
11. Advanced Robotics
Advanced industrial robots, also known as smart machines operate
autonomously and can communicate directly with manufacturing
systems. In some advanced manufacturing contexts, they can work
with humans for co-assembly tasks.
By evaluating sensory input and distinguishing between different
product configurations, these machines are able to solve problems
and make decisions independent of people.
These robots are able to complete work beyond what they were
initially programmed to do and have artificial intelligence that
allows them to learn from experience.
These machines have the flexibility to be reconfigured and re-
purposed.
12. This gives them the ability to respond rapidly to design changes and
innovation, which is a competitive advantage over more traditional
manufacturing processes
There are Cobots ,the robots that can work collaboratively with the
people. So , the robots can work with the machines directly or with
the people.
Fig 3: Robots working with the machines
13. Digital Twin
Digital twin is another concept in the ecosystems of smart
manufacturing.
It creates the virtual model of an asset, process, or system
by using the data obtained from sensors in the systems or
asset and algorithms for making reasonable projections
about the process.
Predictive maintenance is one of the important systems
which will use digital twins.
The benefits of digital twins include potential reduction in
time and cost of product development and elimination of
unplanned downtime.
The rising adoption of IoT and cloud platforms, and 3D
printing and 3D simulation software are boosting the
adoption of digital twin.
14. Aerospace & defense, automotive & transportation, electronics &
electrical/machine manufacturing, and energy & utility are the major
adopter of digital twins.
Once the concept of digital twins develops and matures, then we
may see its increasing application in non-manufacturing sectors such
as retail & the consumer goods market.
Fig.4: Digital twin of human hand
From the figure we can see that the virtual hand is touching human
hand. The projections of human hand is there virtually that is known
as digital twin of human hand.
15. Smart Factory
Smart Factory is the vision of a production environment in
which production facilities and logistics systems are organized
without human intervention
The machinery and equipment are able to improve processes
through automation and self-optimization.
The benefits also extend beyond just the physical production
of goods and into functions like planning, supply chain
logistics, and even product development.
The technical foundations on which the Smart Factory - is
based on are :
cyber-physical systems that communicate with each other
using the Internet of Things and Services.
16. An important part of this process is the exchange of data
between the product and the production line.
This enables a much more efficient connection of the Supply
Chain and better organization within any production
environment.
The manufacturing information provided by the product on
an RDIF chip in machine-readable form, for example, can be
used to control the product's path through the individual
manufacturing steps.
Other transmission technologies, such as WLAN or QR codes,
are also possible.
The smart factory can reduce costs and material waste, and
requires fewer people with smaller operating costs.
It’s more agile, delivering high quality and fast production that
is responsive to customer needs, providing the business with
more granular and up-to-date information.
17. Fig:5 Cobots working in manufacturing industries
In the above figure we can see that there are only cobots that are
working in the manufacturing industry. All the process like
packaging, inspection, manufacturing is done by the cobots .
The results are automatically generated and is being stored in the
cloud. From where it is being used is ordering more materials, or
checking the faulty lines of manufacturing.
18. Advantages of smart manufacturing
Increased productivity
These extremely adaptable systems enable greater flexibility.
In terms of efficiency, one of the main savings comes from the
reduction in production downtime, hence efficiency is improved.
Predictive AI technology can highlight problems before they
occur and take steps to mitigate the financial costs. long-term
cost savings.
Disadvantages of smart manufacturing
Upfront cost of implementation. As many small to midsize
companies won't be able to afford the considerable expense of
the technology.
The technology is very complex, which means that systems that
are poorly designed or not adequate for a particular operation
could not make profits.
19. Conclusion
We have seen that how smart manufacturing is changing the world.
In next few years a lot of human jobs will be in danger as all the
works will be done in an automated matter by the robots.
As already robots have been developed to collaborate with the
humans or to collaborate directly with the machines using artificial
intelligence.
The digital twins has also changes the face of the IT world by
creating a virtual word and imitating things.
The applications of smart manufacturing are very large for eg. In
agriculture also agricultural robots can do work, there are smart
factories that are designed that includes smart buildings, smart
offices, smart industries, smart shops etc.
Smart manufacturing is also widely used in tracking system.
20. References
Zhong, R. Y., Xu, X., Klotz, E., & Newman, S. T. (2017). Intelligent
Manufacturing in the Context of Industry 4.0: A Review. Frontiers of
Mechanical Engineering. In press.
Kang HS, Lee JY, Choi SS, Kim H, Park JH, Son JY, Kim BH, Noh SD
(2016) Smart manufacturing: past research, present findings, and future
directions. Int J Precis Eng Manuf-Green Technol
Kusiak A (2018) Smart manufacturing. Int J Prod Res 56(1-2): 508–517.
https://doi.org/10.1080/00207543.2017.1351644 3. Li B-h et al (2017)
Applications of artificial intelligence in intelligent manufacturing: a
review. Front Inf Technol Elect
https://internetofthingsagenda.techtarget.com/definition/smart-
manufacturing-SM
https://blog.marketresearch.com/the-top-7-things-to-know-about-smart-
manufacturing
https://en.wikipedia.org/wiki/Smart_manufacturing
https://www.networkworld.com/article/3280225/what-is-digital-twin-
technology-and-why-it-matters.html