What is Digital Transformation?
Machine Learning & Statistic
Industry Process is Important for Data Analytics
How to do AI application? Topic ! Team !!
How to build an AI solution team !!!
Digital transformation involves integrating digital technology into all areas of a business to change how the business operates and delivers value to customers. It is a complex process that requires establishing a vision, identifying opportunities, engaging stakeholders, developing solutions, and transforming the business. Many transformations fail due to insufficient resources, lack of executive support, inadequate skills, outdated technologies, and data security concerns. To accelerate transformation, businesses should partner with experts, take incremental steps, and focus on cultural changes to embed digital capabilities.
Sokszor találkozol a digital thread kifejezéssel, de nem tudod hogy pontosan micsoda? Kíváncsi lenné rá, hogyan használják a cégek? Olvasd el prezentációnkat, amit előadtunk az idei Simonyi Konferencián!
Being a Digital Industrial By Anthony Thomas, Group Chief Information Officer...Rahul Neel Mani
This document discusses GE's strategy around digital industrial transformation. It outlines that GE is building digital content and reforming IT to simplify culture and leverage trusted partnerships between industrial companies. GE is meeting customers with digital twins and physics analytics to drive productivity gains. The value to customers is huge through connected machines that can eliminate billions in waste. GE is executing both vertically within industries like aviation and horizontally across them with solutions on its Predix operating system.
1. Manufacturers are facing the challenge of managing complex supply networks in industries like aerospace, defense, and electronics. A digital thread unifying design, manufacturing, and ERP data can help address this complexity by providing a single source of product truth.
2. Realizing a digital thread requires integrating ERP, PLM, and new product lifecycle execution (PLE) systems to close the loop between design, engineering, production, quality, and resources. iBASEt's Solumina suite connects these systems to create a seamless flow of data.
3. Solumina collects data from PLM systems and flows it into manufacturing, while changes made are fed back to engineering. It closes the loop across the
Digital Transformation for Manufacturing IndustriesMargot Heiligman
What are some of the trends that driving the manufacturing industries in this digital economy era? What do these mean for the manufacturing businesses and how can they run and sell smarter? Download this presentation deck and learn more. You can also watch the On-Demand Webinar here: http://tinyurl.com/bcrmAPJ216
A Digital transformation leader with more than 20 years of IT experience and 10+ years of experience, presenting and implementing digital strategies for multiple fortune 100 companies. Collaborated with multiple customer entities to conceptualize and implement digital factories, innovation factories, Mobile office and a complete end-to-end digital enablement road-map. Conducted multiple digital innovation workshops to identify the digital (mobile, social and cloud) disruptions and the transformation approach (business and technology) for the same. Conceptualized and implemented various IP Solutions / Products with niche business value proposition and a very high ROI.
Digital transformation involves integrating digital technology into all areas of a business to change how the business operates and delivers value to customers. It is a complex process that requires establishing a vision, identifying opportunities, engaging stakeholders, developing solutions, and transforming the business. Many transformations fail due to insufficient resources, lack of executive support, inadequate skills, outdated technologies, and data security concerns. To accelerate transformation, businesses should partner with experts, take incremental steps, and focus on cultural changes to embed digital capabilities.
Sokszor találkozol a digital thread kifejezéssel, de nem tudod hogy pontosan micsoda? Kíváncsi lenné rá, hogyan használják a cégek? Olvasd el prezentációnkat, amit előadtunk az idei Simonyi Konferencián!
Being a Digital Industrial By Anthony Thomas, Group Chief Information Officer...Rahul Neel Mani
This document discusses GE's strategy around digital industrial transformation. It outlines that GE is building digital content and reforming IT to simplify culture and leverage trusted partnerships between industrial companies. GE is meeting customers with digital twins and physics analytics to drive productivity gains. The value to customers is huge through connected machines that can eliminate billions in waste. GE is executing both vertically within industries like aviation and horizontally across them with solutions on its Predix operating system.
1. Manufacturers are facing the challenge of managing complex supply networks in industries like aerospace, defense, and electronics. A digital thread unifying design, manufacturing, and ERP data can help address this complexity by providing a single source of product truth.
2. Realizing a digital thread requires integrating ERP, PLM, and new product lifecycle execution (PLE) systems to close the loop between design, engineering, production, quality, and resources. iBASEt's Solumina suite connects these systems to create a seamless flow of data.
3. Solumina collects data from PLM systems and flows it into manufacturing, while changes made are fed back to engineering. It closes the loop across the
Digital Transformation for Manufacturing IndustriesMargot Heiligman
What are some of the trends that driving the manufacturing industries in this digital economy era? What do these mean for the manufacturing businesses and how can they run and sell smarter? Download this presentation deck and learn more. You can also watch the On-Demand Webinar here: http://tinyurl.com/bcrmAPJ216
A Digital transformation leader with more than 20 years of IT experience and 10+ years of experience, presenting and implementing digital strategies for multiple fortune 100 companies. Collaborated with multiple customer entities to conceptualize and implement digital factories, innovation factories, Mobile office and a complete end-to-end digital enablement road-map. Conducted multiple digital innovation workshops to identify the digital (mobile, social and cloud) disruptions and the transformation approach (business and technology) for the same. Conceptualized and implemented various IP Solutions / Products with niche business value proposition and a very high ROI.
Digital Transformation in the Manufacturing sectorArun Natarajan
Traditionally, manufacturers have been slow to adopt digital transformation, despite the sector holding great potential for digital outcomes. However, digital transformation is gaining momentum in the manufacturing sector, as seen with companies like GE aggressively pursuing digital opportunities. Digital transformation offers manufacturers possibilities to reimagine business models, recast value chains, enhance customer engagement, digitally enhance products, and optimize operations. These possibilities extend to the factory floor with Industry 4.0 initiatives. If exploited fully, digital transformation could disrupt and transform the industrial landscape.
From a session at OMEP's Manufacturing the Future Summit, January 14, 2014. By: Katie Moore Global Industry Manager – Food & Beverage GE Intelligent Platforms
The Digital Lab for Manufacturing: How Digital Design & Digital Manufacturing...Decision Lens
innovation.decisionlens.com
What if design talked to manufacturing BEFORE production What if information flowed across the full product life cycle? Or throughout the entire supply chain?
DMDII’s Digital Lab for Manufacturing brings together the best minds in academia, high tech and government to accomplish exactly that.
Learn how digital innovation is integrating design, development, and manufacturing to cut time to production and spur long-term job creation.
The document discusses how internet of things (IoT) technologies can enable smart, connected products and manufacturing operations. It describes how sensors, software, connectivity and data analytics can transform individual products into smart products and manufacturing assets into connected systems with increased visibility, automation, and productivity. The document provides examples of companies that have implemented IoT solutions to improve operations and increase productivity in manufacturing by 8-10%.
This document discusses ISG's engineering services and solutions for transforming businesses. It outlines ISG's approach of assessing clients' operations and strategies, developing target operating models, and setting up global engineering centers. ISG focuses on industries like automotive, high tech, and aerospace. The document promotes follow up workshops to discuss how ISG's offerings can support customers' businesses by building agility, scaling operations, and identifying new revenue streams.
2015 12-01 digital transformation in industrial automation sanitizedThorsten Schroeer
1. The document discusses digital transformation in manufacturing, providing examples of current initiatives and trends like Industry 4.0, IoT, cloud computing, mobile, analytics, and security.
2. It notes that digital transformation is driving changes in business models, moving companies from product manufacturers to service providers paid based on usage.
3. The document argues that companies must develop digital strategies across their factories, products, supply chains, and partnerships to remain competitive in the digital era.
Aricent is the world’s leading engineering, services and software company. We specialize in inventing, developing and maintaining our clients’ most ambitious initiatives in the communications domain. Combining more than 20 years of communications expertise with a force of more than 10,000 dedicated software engineers, Aricent is the only company in the world that offers the scale, experience and proven technologies necessary to deliver for a growing list of global companies, bringing the next generation of breakthrough, connected products to market.
Based in San Francisco, frog, the global leader in innovation and design, is part of Aricent. The company’s key investors are Kohlberg Kravis Roberts & Co. and Sequoia Capital.
Digital transformation in the manufacturing industryBenji Harrison
The document discusses how digital transformation through technologies like Industry 4.0, IoT, big data, VR/AR, and artificial intelligence can benefit manufacturers. Industry 4.0 uses advanced technologies like smart sensors to increase visibility, minimize costs, and speed up production. IoT networks connect intelligent devices to gather and analyze data for cost control, efficiency, and innovation. Big data and advanced analytics provide insights from historical data to optimize processes. VR/AR technologies improve product design and help workers perform tasks faster and more accurately. Artificial intelligence and analytics help integrate systems for greater speed and scale.
Key Imperatives for the CIO in Digital Age By Lalatendu Das Digital VP, Assoc...Rahul Neel Mani
Ravi Shankar Prasad, India's Minister of Information & Technology, stated that India is on the cusp of a digital revolution. India has the 2nd largest number of internet users in the world, which is growing rapidly. Mobile data prices in India have fallen sharply by 56% per year on average. Initiatives like Jan Dhan bank accounts, Aadhaar digital ID, and the growth of mobile are ushering in a more paperless era. Rapid digitization can unlock substantial value for organizations through improvements in areas like customer satisfaction, stock performance, and operating income. However, most organizations are not ready for the speed and flexibility required to become digital leaders.
C.A. Carnevale Maffè - chiudete le fabbriche, investite nell'orgware
tecnologia, scenari e scelte strategiche per la transizione digitale dell'industria manifatturiera
Ge’s journey to becoming a digital industrial companySriram Murali K J
GE has created an Industrial Internet of Things (IIoT) platform called Predix to connect industrial equipment and analyze collected data. Predix allows GE and partners to build applications that gather machine data to help customers and operators make better business decisions. GE aims to become a digital industrial company and generate $15 billion in software revenue by 2020 by aggregating and analyzing large amounts of IoT and machine data through Predix. Case studies demonstrate how Predix has helped companies in industries like energy improve operations and outcomes.
[GE Innovation Forum 2015] The Industrial Internet by Bill RuhGE코리아
[GE Innovation Forum 2015] The Industrial Internet by Bill Ruh
The Industrial Internet by Bill Ruh
GE의 산업인터넷: 제 3차 산업혁명
GE글로벌소프트웨어 총괄 빌 루 부사장
GE’s Industrial Internet: the 3rd Industrial Revolution
by Bill Ruh, Vice President, GE Global Software
GE코리아 뉴스레터를 구독하세요! http://goo.gl/IE8WS8
GE코리아 YouTube 채널을 구독하세요! http://goo.gl/M2gc8m
상상을 현실로 만듭니다. Imagination at work.
GE가 꿈꾸는 가치입니다. 아니, GE는 단지 꿈만 꾸고 있는 것이 아닙니다. 상상을 현실로 만들기 위해, 불가능했던 것을 가능하게 만들기 위해 쉬지 않고 움직이고 있습니다. GE는 에너지, 의료, 항공, 수송, 금융 등의 여러 분야에서 고객과 인류사회의 진보를 위해 더 편리하고 빠르며 친환경적인 솔루션을 찾아냅니다.
Connect with GE Online:
GE코리아 웹사이트: http://www.ge.com/kr/
GE리포트코리아: http://www.gereports.kr/
GE코리아 페이스북 페이지: hhttps://www.facebook.com/GEKorea
GE코리아 슬라이드쉐어: http://www.slideshare.net/GEKorea
Event Report - IBM Think 2021 - There is more than hybrid cloud at IBMHolger Mueller
Constellation Research's Holger Mueller shares his top 4 takeaways from IBM's Think 2021 conference held earlier in May. IBM is adding offerings with AI across the stack, is fastly maturing the quantum software ecosystem and accelerating the monetization of research.
Leveraging Cloud and APIs as a Platform for InnovationMikael Puittinen
This document discusses how companies can leverage cloud technologies and APIs to tackle challenges with digital transformation. It provides examples of how SC5 has helped customers overcome issues like slow legacy systems and a lack of focus on the customer experience by building scalable cloud-native backends with APIs and serverless architecture. Emphasis is placed on using an experimental culture and rapid prototyping to explore new digital business opportunities and interfaces in an agile way.
Top 5 digital transformation trends in manufacturing https://www.forbes.com/sites/danielnewman/2017/08/08/top-5-digital-transformation-trends-in-manufacturing/
Collaborating with partners to inspire business innovations for an intelligen...Huawei Technologies
This document discusses how a medium-sized polyurethane manufacturer faces problems with raw material quality, product quality, and customer/employee management that cost over CNY 2.75 million per year. It proposes using new technologies like supply chain management, production process control, and CRM/ERP systems to address these issues but notes the costs are unaffordable and they lack IT skills. The highest priority requests are eliminating poor quality materials and gaining new sales channels. The document then discusses how SMEs can benefit from technologies like digitalization and the cloud to improve quality and reputation at lower costs than developing solutions internally. It proposes collaboration within an open ecosystem to help all players overcome weaknesses. The cloud provides opportunities for globalization
This document discusses trends in industrial IoT and how equipment companies can respond. It outlines Cathy Yeh's agenda which includes trends in industrial IoT and Microsoft's strategy, smart manufacturing use cases, and an innovative business model example using AOI cloud. It describes challenges facing global manufacturing from trends like shortened product lifecycles, rapidly changing operating environments, and industry ecosystem changes. It then provides examples of how industrial IoT solutions from Microsoft and partners can provide insights, reduce costs, and enable new revenue streams for customers through solutions like predictive maintenance and remote monitoring.
Vertex perspectives ai optimized chipsets (part i)Yanai Oron
Businesses are increasingly adopting AI to create new applications to transform existing operations, driving big data with the growth of IoT and 5G networks and increasing future process complexities for human operators. In this new environment, AI will be needed to write algorithms dynamically to automate the entire programming process. Fortunately, algorithms associated with deep learning are able to achieve enhanced performance with increasing data, unlike the rest associated with machine learning.
Digital Transformation in the Manufacturing sectorArun Natarajan
Traditionally, manufacturers have been slow to adopt digital transformation, despite the sector holding great potential for digital outcomes. However, digital transformation is gaining momentum in the manufacturing sector, as seen with companies like GE aggressively pursuing digital opportunities. Digital transformation offers manufacturers possibilities to reimagine business models, recast value chains, enhance customer engagement, digitally enhance products, and optimize operations. These possibilities extend to the factory floor with Industry 4.0 initiatives. If exploited fully, digital transformation could disrupt and transform the industrial landscape.
From a session at OMEP's Manufacturing the Future Summit, January 14, 2014. By: Katie Moore Global Industry Manager – Food & Beverage GE Intelligent Platforms
The Digital Lab for Manufacturing: How Digital Design & Digital Manufacturing...Decision Lens
innovation.decisionlens.com
What if design talked to manufacturing BEFORE production What if information flowed across the full product life cycle? Or throughout the entire supply chain?
DMDII’s Digital Lab for Manufacturing brings together the best minds in academia, high tech and government to accomplish exactly that.
Learn how digital innovation is integrating design, development, and manufacturing to cut time to production and spur long-term job creation.
The document discusses how internet of things (IoT) technologies can enable smart, connected products and manufacturing operations. It describes how sensors, software, connectivity and data analytics can transform individual products into smart products and manufacturing assets into connected systems with increased visibility, automation, and productivity. The document provides examples of companies that have implemented IoT solutions to improve operations and increase productivity in manufacturing by 8-10%.
This document discusses ISG's engineering services and solutions for transforming businesses. It outlines ISG's approach of assessing clients' operations and strategies, developing target operating models, and setting up global engineering centers. ISG focuses on industries like automotive, high tech, and aerospace. The document promotes follow up workshops to discuss how ISG's offerings can support customers' businesses by building agility, scaling operations, and identifying new revenue streams.
2015 12-01 digital transformation in industrial automation sanitizedThorsten Schroeer
1. The document discusses digital transformation in manufacturing, providing examples of current initiatives and trends like Industry 4.0, IoT, cloud computing, mobile, analytics, and security.
2. It notes that digital transformation is driving changes in business models, moving companies from product manufacturers to service providers paid based on usage.
3. The document argues that companies must develop digital strategies across their factories, products, supply chains, and partnerships to remain competitive in the digital era.
Aricent is the world’s leading engineering, services and software company. We specialize in inventing, developing and maintaining our clients’ most ambitious initiatives in the communications domain. Combining more than 20 years of communications expertise with a force of more than 10,000 dedicated software engineers, Aricent is the only company in the world that offers the scale, experience and proven technologies necessary to deliver for a growing list of global companies, bringing the next generation of breakthrough, connected products to market.
Based in San Francisco, frog, the global leader in innovation and design, is part of Aricent. The company’s key investors are Kohlberg Kravis Roberts & Co. and Sequoia Capital.
Digital transformation in the manufacturing industryBenji Harrison
The document discusses how digital transformation through technologies like Industry 4.0, IoT, big data, VR/AR, and artificial intelligence can benefit manufacturers. Industry 4.0 uses advanced technologies like smart sensors to increase visibility, minimize costs, and speed up production. IoT networks connect intelligent devices to gather and analyze data for cost control, efficiency, and innovation. Big data and advanced analytics provide insights from historical data to optimize processes. VR/AR technologies improve product design and help workers perform tasks faster and more accurately. Artificial intelligence and analytics help integrate systems for greater speed and scale.
Key Imperatives for the CIO in Digital Age By Lalatendu Das Digital VP, Assoc...Rahul Neel Mani
Ravi Shankar Prasad, India's Minister of Information & Technology, stated that India is on the cusp of a digital revolution. India has the 2nd largest number of internet users in the world, which is growing rapidly. Mobile data prices in India have fallen sharply by 56% per year on average. Initiatives like Jan Dhan bank accounts, Aadhaar digital ID, and the growth of mobile are ushering in a more paperless era. Rapid digitization can unlock substantial value for organizations through improvements in areas like customer satisfaction, stock performance, and operating income. However, most organizations are not ready for the speed and flexibility required to become digital leaders.
C.A. Carnevale Maffè - chiudete le fabbriche, investite nell'orgware
tecnologia, scenari e scelte strategiche per la transizione digitale dell'industria manifatturiera
Ge’s journey to becoming a digital industrial companySriram Murali K J
GE has created an Industrial Internet of Things (IIoT) platform called Predix to connect industrial equipment and analyze collected data. Predix allows GE and partners to build applications that gather machine data to help customers and operators make better business decisions. GE aims to become a digital industrial company and generate $15 billion in software revenue by 2020 by aggregating and analyzing large amounts of IoT and machine data through Predix. Case studies demonstrate how Predix has helped companies in industries like energy improve operations and outcomes.
[GE Innovation Forum 2015] The Industrial Internet by Bill RuhGE코리아
[GE Innovation Forum 2015] The Industrial Internet by Bill Ruh
The Industrial Internet by Bill Ruh
GE의 산업인터넷: 제 3차 산업혁명
GE글로벌소프트웨어 총괄 빌 루 부사장
GE’s Industrial Internet: the 3rd Industrial Revolution
by Bill Ruh, Vice President, GE Global Software
GE코리아 뉴스레터를 구독하세요! http://goo.gl/IE8WS8
GE코리아 YouTube 채널을 구독하세요! http://goo.gl/M2gc8m
상상을 현실로 만듭니다. Imagination at work.
GE가 꿈꾸는 가치입니다. 아니, GE는 단지 꿈만 꾸고 있는 것이 아닙니다. 상상을 현실로 만들기 위해, 불가능했던 것을 가능하게 만들기 위해 쉬지 않고 움직이고 있습니다. GE는 에너지, 의료, 항공, 수송, 금융 등의 여러 분야에서 고객과 인류사회의 진보를 위해 더 편리하고 빠르며 친환경적인 솔루션을 찾아냅니다.
Connect with GE Online:
GE코리아 웹사이트: http://www.ge.com/kr/
GE리포트코리아: http://www.gereports.kr/
GE코리아 페이스북 페이지: hhttps://www.facebook.com/GEKorea
GE코리아 슬라이드쉐어: http://www.slideshare.net/GEKorea
Event Report - IBM Think 2021 - There is more than hybrid cloud at IBMHolger Mueller
Constellation Research's Holger Mueller shares his top 4 takeaways from IBM's Think 2021 conference held earlier in May. IBM is adding offerings with AI across the stack, is fastly maturing the quantum software ecosystem and accelerating the monetization of research.
Leveraging Cloud and APIs as a Platform for InnovationMikael Puittinen
This document discusses how companies can leverage cloud technologies and APIs to tackle challenges with digital transformation. It provides examples of how SC5 has helped customers overcome issues like slow legacy systems and a lack of focus on the customer experience by building scalable cloud-native backends with APIs and serverless architecture. Emphasis is placed on using an experimental culture and rapid prototyping to explore new digital business opportunities and interfaces in an agile way.
Top 5 digital transformation trends in manufacturing https://www.forbes.com/sites/danielnewman/2017/08/08/top-5-digital-transformation-trends-in-manufacturing/
Collaborating with partners to inspire business innovations for an intelligen...Huawei Technologies
This document discusses how a medium-sized polyurethane manufacturer faces problems with raw material quality, product quality, and customer/employee management that cost over CNY 2.75 million per year. It proposes using new technologies like supply chain management, production process control, and CRM/ERP systems to address these issues but notes the costs are unaffordable and they lack IT skills. The highest priority requests are eliminating poor quality materials and gaining new sales channels. The document then discusses how SMEs can benefit from technologies like digitalization and the cloud to improve quality and reputation at lower costs than developing solutions internally. It proposes collaboration within an open ecosystem to help all players overcome weaknesses. The cloud provides opportunities for globalization
This document discusses trends in industrial IoT and how equipment companies can respond. It outlines Cathy Yeh's agenda which includes trends in industrial IoT and Microsoft's strategy, smart manufacturing use cases, and an innovative business model example using AOI cloud. It describes challenges facing global manufacturing from trends like shortened product lifecycles, rapidly changing operating environments, and industry ecosystem changes. It then provides examples of how industrial IoT solutions from Microsoft and partners can provide insights, reduce costs, and enable new revenue streams for customers through solutions like predictive maintenance and remote monitoring.
Vertex perspectives ai optimized chipsets (part i)Yanai Oron
Businesses are increasingly adopting AI to create new applications to transform existing operations, driving big data with the growth of IoT and 5G networks and increasing future process complexities for human operators. In this new environment, AI will be needed to write algorithms dynamically to automate the entire programming process. Fortunately, algorithms associated with deep learning are able to achieve enhanced performance with increasing data, unlike the rest associated with machine learning.
Vertex Perspectives | AI-optimized Chipsets | Part IVertex Holdings
Businesses are increasingly adopting AI to create new applications to transform existing operations, driving big data with the growth of IoT and 5G networks and increasing future process complexities for human operators. In this new environment, AI will be needed to write algorithms dynamically to automate the entire programming process. Fortunately, algorithms associated with deep learning are able to achieve enhanced performance with increasing data, unlike the rest associated with machine learning. To date, deep learning technology has primarily been a software play. Existing processors were not originally designed for these new applications. Hence the need to develop AI-optimized hardware.
AIDC NY: Applications of Intel AI by QuEST Global - 09.19.2019Intel® Software
QuEST Global is a global engineering company that provides AI and digital transformation services using technologies like computer vision, machine learning, and deep learning. It has developed several AI solutions using Intel technologies like OpenVINO that provide accelerated inferencing on Intel CPUs. Some examples include a lung nodule detection solution to help detect early-stage lung cancer from CT scans and a vision analytics platform used for applications in retail, banking, and surveillance. The company leverages Intel's AI Builder program and ecosystem to develop, integrate, and deploy AI solutions globally.
6G WILL UNLOCK THE POWER OF AI-FOR-EVERYTHINGMahbubul Alam
We envision 6G to offer revolutionary transformation which will usher in an era of connected built-in intelligent applications, services, and networks that will auto-provision end-to-end systems to guaranteed quality of services for an agreed service level agreement, ultra-high-speed data rate, surpassing that of last-mile wired connectivity, perceived zero-latency & deterministic jitter for human safety and mission-critical applications, extremely high reliability for essential services, high spectrum-bands for haptic, holographic, extensive multimedia streaming and more, connected artificial intelligence for autonomous functions and future unknown use cases, etc.
6G will be a key enabler for equitable wealth distribution and a major driver for the green economy. It will unleash the full potential for Industrial Revolution IE 5.0 which will focus on the co-operation between human and machine, as human intelligence works in harmony with cognitive computing and machines performs mundane, repetitive, error-prone tasks. By putting humans back into industrial production with 6G enabled collaborative robots a.k.a Cobots, workers will be upskilled to provide value-added tasks in production such as setting the strategy, provide oversight and add creative input, leading to massive customization & personalization for customers. In this talk, we will examine the state of AI and its potential role in 6G.
Dell NVIDIA AI Roadshow - South Western OntarioBill Wong
- Artificial intelligence (AI) is mimicking human intelligence through machine algorithms like those used for chess and facial recognition. Machine learning (ML) is a subset of AI that uses algorithms to parse data, learn from data, and make predictions. Deep learning (DL) uses artificial neural networks to develop relationships in data and is used for applications like driverless cars and cybersecurity.
- AI technologies are enabling digital transformation and require infrastructure like edge computing, GPUs, FPGAs, deep learning accelerators, and specialized hardware to power applications of AI, ML, and DL. Dell Technologies provides platforms and solutions to accelerate AI workloads and support digital transformation.
Compounding Business Value Through Big Data & Advanced Analytics, v2denesuk
This document discusses how industrial companies can leverage big data and advanced analytics. It argues that applying data science approaches to industrial sectors like power, aviation, and manufacturing can yield large efficiency gains and cost savings estimated at over $276 billion across various industries. The key is taking an "industrial data science" approach that combines domain expertise in engineering and physics with techniques like machine learning, predictive analytics, and software-defined machines. This will transform how industrial equipment is monitored and optimized to extract more value. The document provides examples of how rules-based systems can be improved using machine learning on operational data combined with outcomes. It also discusses using physical models to generate new predictive features for machine learning models.
Presented at 2018 Smart Manufacturing Summit, Bangalore.
Shared Pov on Digital Transformation strategies for Industrie 4.0, Breaking Legacy Walls, , Building Smart teams for Digital Shopfloor, Inducing Customer Centric Factory, Data Driven Approach, Roadmap for Paper to Product in a Connected World,
Arocom is a consulting and solution engineering company with expertise in providing engineering services for AI & Machine Learning, Data Operations & Analytics, MLOps and Cloud Computing.
Our clients include companies within biotech, drug discovery, therapeutics, manufacturing, retail and startups. Our consultants are best in their skills and offer hands-on talent to our clients in achieving their goals.
AI for Manufacturing (Machine Vision, Edge AI, Federated Learning)byteLAKE
Artificial intelligence and machine learning technologies are transforming key industries like manufacturing, finance, retail, and healthcare. Edge computing and federated learning are emerging approaches that can help address challenges around data privacy, bandwidth constraints, and latency. Edge AI runs optimized models directly on devices to analyze data and only send results rather than raw data. Federated learning leverages local AI models across edge devices to improve performance while keeping sensitive data private. Together these approaches help make AI more scalable, responsive and privacy-preserving for industries.
This document discusses future trends in big data. It notes that the amount of data produced grows enormously every year due to new technologies and devices. Big data provides businesses with better sources of analysis and insights. Key trends discussed include the growth of open source tools like Hadoop and Spark, increased use of machine learning and predictive analytics, edge computing and analytics to process IoT data more efficiently, integration of big data and cloud computing, use of big data for cybersecurity, and growing demand for data science jobs. The conclusion states that big data will significantly impact businesses and 15% of IT organizations will move services to the cloud by 2021.
The document discusses IBM's AI tools and capabilities. It summarizes IBM's suite of AI products including Watson Studio, Watson Machine Learning, Watson OpenScale, and the Watson Knowledge Catalog which help with data preparation, building and training models, deploying and managing models, and ensuring trusted AI. It also discusses IBM's strategy around automating the AI lifecycle through capabilities like transfer learning, neural network search, and AutoAI experiments.
IRJET- Impact of AI in Manufacturing IndustriesIRJET Journal
This document discusses the impact of artificial intelligence in manufacturing industries. It begins by defining AI and explaining that AI is becoming a mainstream technology that any organization can use, including in manufacturing. It then discusses several ways AI is revolutionizing manufacturing, including enabling predictive maintenance to reduce downtime, using AI to help maintain high product quality, facilitating human-robot collaboration on production floors, and allowing for improved product design through generative design algorithms. The document also notes challenges of industrial AI include issues with data quality, needing solutions that can work in real-time, and requiring very high accuracy from AI systems used in manufacturing.
Dell NVIDIA AI Powered Transformation in Financial Services WebinarBill Wong
Digital transformation through data analytics and AI can help financial services firms address business, technology, and labor challenges caused by COVID-19. Key trends include increased reliance on remote work and digital platforms, and the importance of data analytics for decision making. By 2025, 90% of new apps will use AI. The document discusses NVIDIA and Dell Technologies' partnership and strategies for providing infrastructure to support AI workloads through solutions like the DGX A100 system, which can support training, inference, and analytics on one platform through technologies like GPUs and MIG. This helps provide a more flexible and efficient infrastructure compared to traditional siloed approaches.
How could OpenAI, a small organization of just 200 employees, managed to shake the foundations of large companies like Google and Meta? Everyone dreams about being a unicorn – having razor sharp focus, high talent-density , rapid speed of innovation but in reality, even startups end up becoming slow organizations very quickly. Why does this happen?
The document discusses Dell Technologies' artificial intelligence (AI) and data analytics solutions portfolio. It provides an overview of Dell's solutions for AI/machine learning, IoT/streaming data, augmented analytics/data warehousing, data lakes, and high-performance computing (HPC). The solutions leverage Dell infrastructure along with partner technologies and are designed to address various analytical use cases such as digital manufacturing, life sciences research, and retail loss prevention.
The document discusses how AWS can help manufacturers with their digital transformation and Industry 4.0 initiatives. It outlines how AWS enables smart factories and smart products through connectivity, sensors, cloud computing, analytics and AI. This allows for increased efficiency, data-driven decision making, and products that improve over time. The document also provides an example of how AWS technologies like IoT, machine learning and analytics can help optimize manufacturing operations and meet business goals. Finally, it presents an AWS reference architecture for integrating manufacturing systems with the cloud.
Industry pundits are predicting up to 50 billion connected devices by 2020, generating more data than in all of human history to date and connected via ubiquitous, connectivity such as 5G, Sigfox and NBIoT. With this comes the promise of business opportunities to deploy your Internet of Things solution. Ganga will walk you through the trends in computing that you need to be aware of, how you can get started and how working with Intel can accelerate your development and time to market.
Speaker: Ganga Varatharajan, IoT & New Technologies Manager, Intel
Download our special report, IoT Tech for the Manager: http://bit.ly/report1-slideshare
Hey IT, Meet OT as presented at the IoT Inc Business' fifteenth Meetup. See: http://www.iot-inc.com/hey-it-meet-ot-meetup/
In our fifteenth Meetup we have Hima Mukkamala, Head of Engineering at Predix, GE Digital presenting “Hey IT, Meet OT”.
Presentation Abstract
Software has been the domain of information technology, but it is quickly becoming key to operations technology as well. Operating smart, networked machines from wind turbines to jet engines requires an intricate understanding of both the machines and the data and information that flows through them. The combination of these two disciplines is bringing new efficiencies and capabilities that do more—faster and cheaper. The key is leveraging connectivity, data, and mobility to optimize efficiency and deliver new services to customers. Join Hima Mukkamala of GE Digital to hear how software technology can help companies bridge the divide between IT and OT and how IT can help industrial companies build, deploy, and manage Industrial Internet applications that bring game-changing efficiencies to businesses.
This document discusses how telecom companies can leverage artificial intelligence and analytics to drive digital transformation. It identifies key opportunities for AI including improving the customer experience, fraud mitigation, and predictive maintenance. It then outlines the components of a telecom data lake that can support these advanced analytics initiatives. Examples of AI use cases for different telecom business functions like marketing, network operations, and security are also provided. The document argues that a data lake platform optimized for analytics can help telecom companies achieve business and innovation goals through improved operations, new revenue streams, and lower costs.
Similar to Digital Transformation and AI in Smart Manufacturing (20)
We are pleased to share with you the latest VCOSA statistical report on the cotton and yarn industry for the month of March 2024.
Starting from January 2024, the full weekly and monthly reports will only be available for free to VCOSA members. To access the complete weekly report with figures, charts, and detailed analysis of the cotton fiber market in the past week, interested parties are kindly requested to contact VCOSA to subscribe to the newsletter.
06-18-2024-Princeton Meetup-Introduction to MilvusTimothy Spann
06-18-2024-Princeton Meetup-Introduction to Milvus
tim.spann@zilliz.com
https://www.linkedin.com/in/timothyspann/
https://x.com/paasdev
https://github.com/tspannhw
https://github.com/milvus-io/milvus
Get Milvused!
https://milvus.io/
Read my Newsletter every week!
https://github.com/tspannhw/FLiPStackWeekly/blob/main/142-17June2024.md
For more cool Unstructured Data, AI and Vector Database videos check out the Milvus vector database videos here
https://www.youtube.com/@MilvusVectorDatabase/videos
Unstructured Data Meetups -
https://www.meetup.com/unstructured-data-meetup-new-york/
https://lu.ma/calendar/manage/cal-VNT79trvj0jS8S7
https://www.meetup.com/pro/unstructureddata/
https://zilliz.com/community/unstructured-data-meetup
https://zilliz.com/event
Twitter/X: https://x.com/milvusio https://x.com/paasdev
LinkedIn: https://www.linkedin.com/company/zilliz/ https://www.linkedin.com/in/timothyspann/
GitHub: https://github.com/milvus-io/milvus https://github.com/tspannhw
Invitation to join Discord: https://discord.com/invite/FjCMmaJng6
Blogs: https://milvusio.medium.com/ https://www.opensourcevectordb.cloud/ https://medium.com/@tspann
Expand LLMs' knowledge by incorporating external data sources into LLMs and your AI applications.
Discovering Digital Process Twins for What-if Analysis: a Process Mining Appr...Marlon Dumas
This webinar discusses the limitations of traditional approaches for business process simulation based on had-crafted model with restrictive assumptions. It shows how process mining techniques can be assembled together to discover high-fidelity digital twins of end-to-end processes from event data.
2. 2Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
Dr. Chun-Yi (Squall) Wu
• Massachusetts Institute of Technology
– Smart Manufacturing Program 2019
• Taiwan AI Academy, Hsinchu 2018
• Glass Manufacturing Industry
– Image Classification, Text Mining, Deep Learning
• IBM Research Almaden 2017
– Nature Language Processing (SystemT)
• System Integration Company
– Feature Engineering, Predictive Maintenance, Industry 4.0
• Intellectual Property Service
– Patent Map (Visualization) & Patent Quality (PCA, BPANN)
• NTHU IEEM
– Neural Network, Clustering Algorithm, Genetic Algorithm, etc.
3. 3Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
What is Digital Transformation?
Mechanism
Robot Measurement
Sensors
Data Scientist
Machine
Learning
IT
Cyber Security
Control
PLC
Quality
Computer
Vision
4. 4Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
The Technology of Digital Transformation
5. 5Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
Smart
Manufacturing
Digital
Transformation
Artificial
Intelligence
Smart
Logistic
Smart
HR
Smart
Sales
Machine
Learning
Cloud /
Edge
Computing
The ecosystem of Digital Transformation
12. 12Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
製造業流程
Data Lake
PLC, OPC Server, Sensor, etc.
13. 13Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
Industry Process is Important for Data Analytics
電商
製造
消費者
設備
Industry Process
Website
MES
SCADA
PLC
Data Lake
Data
Market
Data
Analytics
Quality Prediction
Recommendation商
品
產
品
推薦到消費者
要的
消費者要的不
推薦
推薦消費者不
想要的
消費者不要的
不推薦
成本:資
料與運算
成本:
人機物料
14. 14Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
How to do AI application? Topic ! Team !!
• 產業利用性
• 再現性
• 技術新穎性
• 進步性
• AI Scientist
• Software engineer
• Data engineering
• Hardware
• Bridger
• Domain expert
Leader
Manager
Defect
Inspection
Transfer
Learning
Accuracy
Predictive
Maintenance
Machine
Learning
Preventive to
Prognosis
15. 15Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
How to build an AI solution team !!!
Computer
Vision
PM
Image
AOI
Hybrid
CNN
Robot Arm
PM
Vibra
tion
Automa
tion
Edge
Computing
Reinforcement
Learning
Power
Transformer
PM
Oil Gas
Facility
Cloud
Computing
Dissolved
Gas Analysis
NLP/NLU
PM
Text
R&D
HPC
BERT
Project Manager
Data Source
Domain Expert
Data Analytics
Software & IT
16. 16Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
Data Analysis Processing
In 3-direction
X
Y
Z
Vibration
Signal
Time
Domain
Freq.
Domain
TS
FFT
Feature
Extraction
Health
Score
Learning the
baseline
Smart Alert
SPC rule
Building
Baseline
5 features (RMS, Mean, kurtosis, peak2peak,
skewness) of time domain
5 features (1X, 2X, 3X, 4X,
and 5X FFT) of frequency
domain
17. 17Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
Using the health score and the model, the critical event
can be predicted for predictive maintenance.
• The critical time of the good to poor status can be calculated and the result is
able to provide decision support.
Equipment A
Equipment B
Health score will
lower than 35
after 2023.
Should be
maintained before
2021.
There will be
no immediate
problems in
recent years.
Equipment C
18. 18Manufacturing Technology & Engineering Corning RestrictedDr. Squall Wu 2019
Smart Manufacturing Suggestion
• A great tool in the wrong hands is a waste.
• Provide solution not just only data analytics
• From Auto Process to Auto Modeling
• Data Quality to Model Quality
• Model evaluation : Overkill & Leakage
• Standard data preprocess tool
• Such as : Text labeling