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Digital Biomanufacturing Market – Distribution by Type of Technology, Deployment Options, Types of Biologics Manufactured, and Key Geographical Regions: Industry Trends and Global Forecasts, 2023-2035
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New York, May 25, 2023 (GLOBE NEWSWIRE) — Reportlinker.com announces the release of the report “Digital Biomanufacturing Market – Distribution by Type of Technology, Deployment Options, Types of Biologics Manufactured, and Key Geographical Regions: Industry Trends and Global Forecasts, 2023-2035” – https://www.reportlinker.com/p06458562/?utm_source=GNW
Further, a surge in morbidity across the globe and enhanced interconnectivity of equipment and technologies has led to an increased burden on manufacturing operations. Other factors that influenced the market include higher competition, competitive pricing, inflation rate, technological advancements and evolving regulatory guidelines. These factors demanded a fundamental shift from conventional manufacturing operations, which subsequently led to the introduction of industry 4.0 technologies. Digital biomanufacturing has emerged as a promising alternative to mitigate a number of bioprocessing related concerns, as well as significantly promote process robustness and product quality.
Digital biomanufacturing, popularly known as bioprocessing 4.0, refers to the integration of physical equipment with digital software and platforms, such as process analytical technologies (PAT), data analysis software (DAS), manufacturing execution systems (MES) and digital twins, in order to streamline the overall biomanufacturing process. Implementation of these technologies in monitoring, analytics and computing capabilities is expected to revolutionize current biomanufacturing practices. Further, digital bioprocessing is believed to have transformed manufacturing principles in areas, such as process development, operational activities, logistics and supply chain management, when used in combination with advanced technologies, including artificial intelligence (AI), machine learning and internet of things (IoT).
SCOPE OF THE REPORT
The Digital Biomanufacturing Market: Distribution by Type of Technology (PAT, DAS, MES and Digital Twins), Deployment Options (Cloud-based and On-premises), Type(s) of Biologic(s) Manufactured (Antibodies, Cell Therapies and Gene Therapies, Proteins, Vaccines, and Others), and Key Geographical Regions (North America, Europe, Asia-Pacific, Latin America, and Middle East and North Africa): Industry Trends and Global Forecasts, 2023-2035 report features an extensive study of the current market landscape and the likely future potential of the digital biomanufacturing market, over the next 12 years. It highlights the efforts of several stakeholders engaged in this rapidly emerging segment of the pharmaceutical industry. Key inclusions of the report are briefly discussed below:
Growing Demand for Biologics
Breakthroughs in the biotechnology industry, over the last few decades, has provided a considerable boost to the overall development landscape of biopharmaceutical drugs. In 2022, a milestone was witnessed when the number of approvals received by biologics narrowly outpaced those reported by small molecules. Further, in the same year, nearly half of the biologic approvals were allotted to novel class of modalities, including antibody drug conjugates (ADCs), bispecific antibodies, cell therapies and gene therapies. This can be attributed to the fact that the demand for biologics has been constantly increasing and is supported by continuous innovation in this field. Specifically, advancements in niche segments is expected to culminate in accelerated growth of the biologics market.
Need for Digital Biomanufacturing
According to a recent report, the development of a new drug takes 10-15 years, with an overall investment of USD 1-2 billion. Despite the significant investment of resources, over 90% of the candidates fail at different stages of clinical trials, resulting in huge financial losses for biomanufacturers.
As a direct consequence of the consistently growing demand for biologics and the existing challenges, there is an increase in the requirement for solutions that help in establishment of a digitally enabled and connected end-to-end process, in order to optimize bioprocess operations. Research suggests that, at present, 20% of the organizations have already adopted digitalized approaches for biomanufacturing. Such approaches are expected to enable an uninterrupted and accessible supply of cost-effective drugs that are likely to be launched commercially, with reduced development timelines. In fact, several leading biopharma players have claimed to achieve 40% increase in quality, 15% reduction in cost, 80% decrease in process variability and 20% shorter operational timelines by leveraging digital biomanufacturing advances. , , ,
Key Advantages of Digital Biomanufacturing
Currently, batch-to-batch variation and product validation are considered as major bottlenecks faced by the biologic industry. Digital biomanufacturing harnesses various advancements, such as real-time monitoring, data analytics, automation, modelling, process optimization and other digital tools to transform the available information into actionable insights. This is expected to help in the creation of a uniform process, which is capable of decreasing the deviation in quality of each batch. Other key benefits of digital biomanufacturing include improved efficiency, higher product yield, better product quality, data integrity, reduced manual intervention and limited risk of contamination. It is worth noting that digitalization in biopharmaceutical manufacturing is becoming an essential requirement, given its potential to develop enhanced quality products, with high speed, agility and sustainability.
Current Market Landscape of Digital Biomanufacturing
The digital biomanufacturing providers landscape features a mix of large, mid-sized and small companies, which have the required expertise and offer various digital services for the production of biologics. At present, more than 140 digital technologies have been / are being developed by over 100 industry stakeholders to enable the manufacturing of biologics. Further, various types of technologies currently facilitate smart biomanufacturing; of these, 48% are based on the principles of PAT, followed by those using MES (28%), DAS (14%) and digital twins (10%).
Key Trends in the Digital Biomanufacturing Market
Many stakeholders are undertaking initiatives to forge alliance with other industry / non-industry players. It is worth highlighting that over 75 strategic partnerships related to digital biomanufacturing have been inked since 2018, indicating that software providers are actively upgrading their technology related capabilities and accommodating the current and anticipated demand for digital biomanufacturing. Given the inclination towards cutting-edge technologies, along with innovative approaches to tailor the bioprocessing, we believe that the digital biomanufacturing technologies market is likely to evolve at a rapid pace, over the coming years. ,
Market Size of the Digital Biomanufacturing Market
Driven by improved data analytics, better product yield, faster production timelines, access to real time operations and rising interest in paperless manufacturing amongst innovators, lucrative opportunities are expected to emerge for players offering bioprocessing 4.0 services. The digital biomanufacturing market is anticipated to grow at a CAGR of 11%, during the period 2023-2035. In terms of type of technology, the digital biomanufacturing market for digital twins is expected to grow at a relatively faster pace (19%), till 2035. Further, currently, the market for on-premise deployment options is expected to capture the majority share, however, this trend is likely to change in the foreseen future with the rising popularity of cloud-based technologies.
Example Players in the Digital Biomanufacturing Market
Examples of players engaged in this domain include (which have also been captured in this report) AspenTech, Bioreactors.net, Dassault Systèmes, FUJIFILM Diosynth Biotechnologies, GE Healthcare, Körber, Merck, Sartorius and Thermo Fisher Scientific.
The report presents an in-depth analysis, highlighting the capabilities of various stakeholders engaged in this domain, across different regions. Amongst other elements, the report includes:
An executive summary of the insights captured during our research, offering a high-level view on the current state of the digital biomanufacturing market and its likely evolution in the mid-long term.
A general introduction to digital biomanufacturing, featuring a detailed discussion on various types of technologies that support digital bioprocessing. In addition, it presents the key challenges and future perspectives associated with the employment of digital technologies in the field of biomanufacturing.
A detailed assessment of the overall market landscape of companies offering digital biomanufacturing technologies (PAT, DAS, MES and digital twins), based on several relevant parameters, such as year of establishment, company size (in terms of number of employees), location of headquarters, type of company (CDMO provider and software provider), number of platforms offered, deployment options (cloud based, on-premises, corporate datacenter and hybrid), platform capabilities (process automation, bioprocess optimization and controls, process connectivity, scalability, data integration, process monitoring and visualization, performance analysis, report generation and documentation, smart manufacturing, document control, production tracking, performance analysis and data integration), software capabilities (process intelligence, data integration, real-time process monitoring, data visualization, performance analysis and control prediction, reporting and data management), type(s) of biologic(s) manufactured, other compatible platforms (artificial intelligence / machine learning / cloud based, big data, internet of things, augmented reality and virtual reality) and type of end user(s) (industry and non-industry), integrating software (enterprise resource planning (ERP), manufacturing operation management (MOM), product lifecycle management (PLM), human resource management (HRM)), type of service(s) offered (training, implementation / upgradation and general support), area(s) of application (asset / process management, clinical trials, personalized treatment, medical training, surgical planning, health monitoring and diagnosis).
A detailed competitiveness analysis of digital biomanufacturing technologies (PAT, DAS, MES and digital twins), based on supplier strength (in terms of years of experience and company size), technology portfolio (considering deployment options, number of platform capabilities, type of end user(s), software capabilities, area(s) of application, type(s) of twin(s)) and type(s) of biologic(s) manufactured.
Elaborate profiles of key players (companies offering more than one platform and established before 2012) engaged in the digital biomanufacturing domain, which are actively providing software based on PAT, DAS, MES and digital twins. Each profile includes a brief overview of the company, along with information on capabilities of digital technologies offered by these firms, recent developments and an informed future outlook.
A benchmark analysis highlighting the capabilities of companies (in terms of their expertise across various platforms related to the manufacturing of biologics) engaged in this domain, across key peer groups.
An analysis featuring information on recent partnerships inked between stakeholders engaged in this domain, based on several relevant parameters, such as year of partnership, type of partnership, type of technology, most active players (in terms of number of deals inked) and regional distribution of partnership activity, during the period 2018-2022.
A detailed analysis highlighting the market concentration of key industry stakeholders (companies offering more than one platform) across various regions, based on prevalent parameters, such as years of entrance, company size, type of technology, number of platforms offered and number of partnerships inked.
A detailed industry lifecycle analysis that indicates various stages, including emergence, growth, maturation and eventual decline for the digital biomanufacturing industry. The primary purpose of this analysis is to develop a better understanding of the current position / phase of the industry on the lifecycle chart (based on historical trends, partnership activity and various investments made by players engaged in this domain) and predict the upcoming events that are likely to drive the growth of this domain. Further, it presents short-term and long-term impacts of various key parameters that are expected to highly impact the wider adoption of digitalization in the field of biomanufacturing.
One of the key objectives of the report was to estimate the current opportunity and future growth potential of the digital biomanufacturing market. We have provided an informed estimate on the likely evolution of the market for the period, 2023-2035. Our year-wise projections of the current and forecasted opportunity have been further segmented based on relevant parameters, such as type of technology (PAT, DAS, MES and digital twins), deployment options (cloud based and on-premises), type(s) of biologic(s) manufactured (antibodies, cell therapies and gene therapies, proteins, vaccines and others) and key geographical regions (North America, Europe, Asia-Pacific, Middle East and North Africa, and Latin America). In order to account for future uncertainties associated with some of the key parameters and to add robustness to our model, we have provided three market forecast scenarios, portraying the conservative, base and optimistic scenarios of the industry’s evolution.
The opinions and insights presented in this study were influenced by discussions conducted with multiple stakeholders in this domain. The report features detailed transcripts of interviews held with the following individuals:
Joel Sirois (President and Chief Executive Officer, BioIntelligence Technologies)
Klaus Mauch (Managing Director and Chief Executive Officer, Yokogawa Insilico Biotechnology)
Ciaran O’Keeffe (Director, Business Development and Channel Sales, MasterControl) and Isura Sirisena (Quality and Manufacturing Digitization Specialist, MasterControl)
Yaron Halfon (Director of Sales, Trunovate)
Barbara Holtz (Business Consultant, Dassault Systèmes)
All actual figures have been sourced and analyzed from publicly available information forums and primary research discussions. Financial figures mentioned in this report are in USD, unless otherwise specified.
RESEARCH METHODOLOGY
The data presented in this report was gathered via primary and secondary research. For all our projects, we conduct interviews / surveys with reputed domain experts (academia, industry, medical practice and other associations) to solicit their opinions on emerging trends in the market. This is primarily useful for us to draw out our own opinion on how the market will evolve across different regions and technology segments. Wherever possible, the available data has been checked for accuracy from multiple sources of information.
The secondary sources of information include:
Annual reports
Investor presentations
SEC filings
Industry databases
News releases from company websites
Government policy documents
Industry analysts’ views
While the focus has been on forecasting the market till 2035, the report also provides our independent view on various technological and non-commercial trends emerging in the industry. This opinion is solely based on our knowledge, research and understanding of the relevant market gathered from various secondary and primary sources of information.
KEY QUESTIONS ANSWERED
Question 1: What is the global market size of digital biomanufacturing?
Answer: The current global digital biomanufacturing market is anticipated to be worth around USD 15 billion.
Question 2: Which are the top players in the global digital biomanufacturing market?
Answer: Presently, more than 100 companies are engaged in digital biomanufacturing, worldwide. The top players engaged in this domain (which have also been captured in this report) include AspenTech, Bioreactors.net, Dassault Systèmes, FUJIFILM Diosynth Biotechnologies, GE Healthcare, Körber, Merck, Sartorius and Thermo Fisher Scientific.
Question 3: What are the factors driving the digital biomanufacturing market?
Answer: Increasing number of approved biologics, growing number of biologics-related clinical trials, rise in R&D activity and a shift in preference for cloud-based processes, over the traditional biomanufacturing operations, has bolstered the demand for digital biomanufacturing software.
Question 4: Which region has the highest market share in the global digital biomanufacturing market?
Answer: North America and Europe capture around 75% share in the current global digital biomanufacturing market, followed by Asia-Pacific.
Question 5: What are the leading market segments in digital biomanufacturing market?
Answer: Currently, in terms of type of technology, process analytical technology captures the largest share (close to 50%) in the global digital biomanufacturing market. However, digital twins are likely to witness higher annual growth rates in the upcoming years, owing to their rising popularity. Further, in terms of type of company, software providers hold the largest share in the digital biomanufacturing market as compared to CDMOs.
Question 6: Which segment, in terms of deployment options, accounts for the largest share in the global digital biomanufacturing market?
Answer: At present, the global biomanufacturing market is dominated by the players providing on-premises deployment options, while the market is anticipated to shift towards the use of cloud-based technologies in the near future.
Question 7: What are the partnership and collaboration trends in the digital biomanufacturing domain?
Answer: At present, service alliances, technology utilization agreements and acquisitions are the most prominent types of partnerships inked between various stakeholders engaged in the digital biomanufacturing domain.
Question 8: What is the growth rate (CAGR) in the global digital biomanufacturing market?
Answer: The global digital biomanufacturing market size is projected to grow at a CAGR of ~11% in the coming years.
CHAPTER OUTLINES
Chapter 1 is a preface providing an introduction to the full report, Digital Biomanufacturing Market, 2023-2035.
Chapter 2 is an executive summary of the insights captured during our research, offering a high-level view on the current state of the digital biomanufacturing market and its likely evolution in the mid-long term.
Chapter 3 provides a general introduction to digital biomanufacturing. It further includes a detailed discussion on the various types of technologies that support digital bioprocessing. In addition, it presents the key challenges and future perspectives associated with the employment of digital technologies in the field of biomanufacturing.
Chapter 4 includes a detailed assessment of the overall market landscape of companies offering digital biomanufacturing technologies (PAT, DAS, MES, digital twins), based on several relevant parameters, such as year of establishment, company size (in terms of number of employees), location of headquarters, type of company (CDMO provider and software provider), number of platforms offered, deployment options (cloud based, on-premises, corporate datacenter and hybrid), platform capabilities (process automation, bioprocess optimization and controls, process connectivity, scalability, data integration, process monitoring and visualization, performance analysis, report generation and documentation, smart manufacturing, document control, production tracking, performance analysis and data integration), software capabilities (process intelligence, data integration, real-time process monitoring, data visualization, performance analysis and control prediction, reporting and data management), area(s) of application (asset / process management, clinical trials, personalized treatment, medical training, surgical planning, health monitoring and diagnosis), integrating software (enterprise resource planning (ERP), manufacturing operation management (MOM), product lifecycle management (PLM), human resource management (HRM)), type of service(s) offered (training, implementation / upgradation and general support), type(s) of biologic(s) manufactured, other compatible platforms (artificial intelligence / machine learning / cloud based, big data, internet of things, augmented reality and virtual reality) and type of end user(s) (industry and non-industry).
Chapter 5 presents a detailed competitiveness analysis of digital biomanufacturing technologies (PAT, DAS, MES and digital twins) based on company strength (in terms of years of experience and company size), technology portfolio (considering deployment options, number of platform capabilities, type of end user(s), software capabilities, area(s) of application, type(s) of twin(s)), and type(s) of biologic(s) manufactured.
Chapter 6 features elaborate profiles of key players (companies offering more than one platform and established before 2012) engaged in the digital biomanufacturing domain, which are actively providing software based on PAT, DAS, MES and digital twins. Each profile includes a brief overview of the company, along with information on the capabilities of digital technologies offered by these firms, recent developments and an informed future outlook.
Chapter 7 presents benchmark analysis of the capabilities of companies (in terms of their expertise across various platforms related to the manufacturing of biologics) engaged in this domain, across key peer groups.
Chapter 8 features information on recent partnerships inked between stakeholders engaged in this domain, based on several relevant parameters, such as year of partnership, type of partnership, type of technology, most active players (in terms of number of deals inked) and regional distribution of partnership activity, during the period 2018-2022.
Chapter 9 highlights our opinion on the market concentration of key industry stakeholders (companies offering more than one platform) across various regions, based on prevalent parameters, such as years of entrance, company size, type of technology, number of platforms offered and number of partnerships inked.
Chapter 10 presents a detailed industry lifecycle analysis that indicates various stages, including emergence, growth, maturation and eventual decline for the digital biomanufacturing industry. The primary purpose of this analysis is to develop a better understanding of the current position / phase of the industry on the lifecycle chart (based on historical trends, partnership activity and various investments made by players engaged in this domain) and predict the upcoming events that are likely to drive the growth of this domain. Further, it presents short-term and long-term impacts of various key parameters that are expected to highly impact the wider adoption of digitalization in the field of biomanufacturing.
Chapter 11 presents a comprehensive market forecast analysis, highlighting the future potential of the market till 2035. Our year-wise projections of the current and forecasted opportunity have been further segmented based on relevant parameters, such as type of technology (PAT, DAS, MES and digital twins), deployment options (cloud based and on-premises), type(s) of biologic(s) manufactured (antibodies, cell therapies and gene therapies, proteins vaccines, and others), and key geographical regions (North America, Europe, Asia-Pacific, Middle East and North Africa, and Latin America).
Chapter 12 is a summary of the overall report. The chapter provides the key takeaways from the report, and presents facts and figures described in the previous chapters. The chapter also highlights important evolutionary trends that were identified during the course of the study and are expected to influence the future of the digital biomanufacturing market.
Chapter 13 is a collection of transcripts of interviews conducted with various stakeholders in the industry. We have presented details of interviews held Joel Sirois (President and Chief Executive Officer, BioIntelligence Technologies), Klaus Mauch (Managing Director and Chief Executive Officer, Yokogawa Insilico Biotechnology), Ciaran O’Keeffe (Director, Business Development and Channel Sales, MasterControl), Isura Sirisena (Quality and Manufacturing Digitization Specialist, MasterControl), Yaron Halfon (Director of Sales, Trunovate) and Barbara Holtz (Business Consultant, Dassault Systèmes).
Chapter 14 is an appendix, which contains tabulated data and numbers for all the figures included in this report.
Chapter 15 is an appendix, which contains a list of companies and organizations mentioned in this report.
Read the full report: https://www.reportlinker.com/p06458562/?utm_source=GNW
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Artificial Intelligence
Data Center Chip Market Size was Valued at USD 11.7 Billion in 2022 and is Expected to Reach USD 45.3 Billion by 2032 at a CAGR of 14.6% | Valuates Reports
BANGALORE, India, July 26, 2024 /PRNewswire/ — Data Center Chip Market By Chip Type (GPU, ASIC, FPGA, CPU, Others), By Data Center Size (Small and Medium Size, Large Size), By Industry Verticals (BFSI, Manufacturing, Government, IT and Telecom, Retail, Transportation, Energy and Utilities, Others): Global Opportunity Analysis and Industry Forecast, 2023-2032.
The Data Center Chip Market was valued at USD 11.7 Billion in 2022, and is estimated to reach USD 45.3 Billion by 2032, growing at a CAGR of 14.6% from 2023 to 2032.
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Major Factors Driving the Growth of Data Center Chip Market
Because of the growing need for data processing and storage solutions brought about by the quick development of cloud computing, artificial intelligence, and big data analytics, the data center chip market is expanding significantly. High-performance chips are necessary for data centers to process massive volumes of data quickly and efficiently. As a result, advances in chip technology, including CPUs, GPUs, and specialist AI processors, have been made. The need for more resilient and scalable data center infrastructure is fueled in part by the expansion of digital services and Internet of Things (IoT) devices. The market is expanding due to key areas including Asia-Pacific, with its investments in technology and fast digital transformation, and North America, with its top tech businesses and vast data center networks.
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TRENDS INFLUENCING THE GROWTH OF THE DATA CENTER CHIP MARKET:
In data centers, Graphics Processing Units (GPUs) are essential for speeding up computing operations and data processing. They are perfect for managing workloads related to artificial intelligence (AI), machine learning, and large-scale data analytics because of their parallel processing capabilities. The need for GPUs in data centers is growing as these technologies become increasingly essential to corporate operations. Businesses are purchasing GPUs in order to increase the effectiveness of their data processing, lower latency, and boost overall performance. The need for data center chips is being driven by the increasing reliance on GPUs for sophisticated computing activities, which is considerably contributing to the market’s rise. This need is further increased by the growing use of AI and machine learning in a variety of sectors, which puts GPUs at the forefront of the data center semiconductor industry.
Compared to general-purpose chips, Application Specific Integrated Circuits (ASICs) provide better performance and efficiency since they are designed specifically for a given application. ASICs are extensively utilized in data centers for specific tasks including networking, data compression, and encryption. ASICs are becoming more and more common as a result of the growth of cloud computing, big data analytics, and blockchain technology, which has increased demand for high-performance, energy-efficient processors. Their capacity to provide tailored performance for certain applications aids data centers in better workload management, power conservation, and operating expense reduction. The market is expanding as a result of the increased preference for ASICs in data centers, which is fueling the need for specialized data center chips.
Large data centers are important users of data center chips; they are run by well-known IT firms and cloud service providers. To manage enormous volumes of data and provide a wide range of services, these facilities need a great deal of processing power and sophisticated computing skills. High-performance data center chips are becoming more and more necessary as a result of the growth of massive data centers and the rising demand for online streaming, cloud services, and digital transactions. These chips are necessary to ensure effective data management, processing, and storage, which helps big data centers fulfill the increasing expectations of its clientele. Large data center proliferation is anticipated to considerably boost the data center chip industry as the digital economy continues to grow.
Data centers are becoming more and more important to the Banking, Financial Services, and Insurance (BFSI) industry as a means of safely and effectively managing high transaction volumes, consumer data, and financial records. The need for sophisticated data center processors is being driven by the sector’s requirement for real-time data processing, high-performance computing, and strong security measures. BFSI organizations may improve their operational efficiency, guarantee data integrity, and deliver superior client services by utilizing data centers fitted with robust chips. The BFSI sector’s need for data center chips is being driven by the increasing use of online banking, digital banking, and financial analytics tools, all of which increase the requirement for sophisticated data center infrastructure.
The market for data center chips is significantly influenced by the cloud computing industry’s explosive growth. There is a growing need for scalable, effective, and high-performance data center infrastructure as more companies move their operations to the cloud. In order to handle enormous volumes of data, facilitate virtualization, and guarantee flawless service delivery, cloud service providers need sophisticated data center chips. Sturdy data center chips are becoming more and more necessary as cloud-based solutions become more and more popular. Benefits like cost savings, flexibility, and scalability are driving this trend. In places like North America and Europe, where cloud adoption rates are high and data center chip demand is rising rapidly, this tendency is especially significant.
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DATA CENTER CHIP MARKET SHARE
In 2022, North America gained a sizable portion of the market.
In 2022, the GPU made up the largest portion of the market share.
Throughout the projection period, large data centers are expected to gain a significant portion.
The BFSI market is anticipated to be one of the most profitable markets.
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Key Companies:
Advanced Micro Devices IncTaiwan Semiconductor Manufacturing Company LimitedBroadcomHuawei Technologies Co LtdIntel CorporationNVidia CorporationSamsung Electronics Co LtdQualcomm Technologies IncGlobalFoundriesARM LIMITED (SOFTBANK GROUP CORP.)Purchase Chapters @ https://reports.valuates.com/request/chaptercost/ALLI-Auto-2B326/Data_Center_Chip_Market
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Industry 4.0 Market to Surpass USD 513.89 Billion by 2031 with Automation Surge | SkyQuest Technology
WESTFORD, Mass., July 26, 2024 /PRNewswire/ — According to SkyQuest, the global Industry 4.0 Market size was valued at USD 133.05 billion in 2022 and is poised to grow from USD 154.6 billion in 2023 to USD 513.89 billion by 2031, growing at a CAGR of 16.2% during the forecast period (2024-2031).
Industry 4.0 or the fourth industrial revolution emphasizes the use of automation and interconnectivity. Employment of advanced technologies such as artificial intelligence, machine learning, robotics, and connected devices to improve the productivity and efficiency of industries. Rapid digitization and advancements in technology are forecasted to bolster the Industry 4.0 market growth over the coming years. The global Industry 4.0 market is segmented into technology, industry vertical, and region.
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Industry 4.0 Market Overview:
Report Coverage
Details
Market Revenue in 2023
$ 154.6 billion
Estimated Value by 2031
$ 513.89 billion
Growth Rate
Poised to grow at a CAGR of 16.2%
Forecast Period
2024–2031
Forecast Units
Value (USD Billion)
Report Coverage
Revenue Forecast, Competitive Landscape, Growth Factors, and Trends
Segments Covered
Technology, Industry and Region
Geographies Covered
North America, Europe, Asia Pacific, Latin America, and Middle East and Africa.
Report Highlights
Internet of Things (IoT) technology takes centerstage for Industry 4.0 adoption
Key Market Opportunities
Adoption of smart manufacturing and additive manufacturing practices
Key Market Drivers
Rising demand for automation across all industry verticals
Segments covered in Industry 4.0 Market are as follows:
TechnologyRobots (Traditional Industrial Robots {Articulated robots, Cartesian Robots, Selective Compliance Assembly Robot Arm (SCARA), Cylindrical Robots, Others}, Collaborative Robots), Blockchain in Manufacturing, Industrial Sensors (Level Sensors, Temperature Sensors, Flow Sensors, Position Sensors, Pressure Sensors, Force Sensors, Humidity & Moisture Sensors, Gas Sensors), Industrial 3D Printing, Machine Vision (Camera {Digital Camera, Smart Camera}, Frame Grabbers, Optics, and LED Lighting, Processor and Software), HMI (Offering {Hardware [Basic HMI, Advanced Panel-based HMI, Advanced PC-based HMI, Others], Software [On-premises HMI, Cloud-based HMI], Services}), Configuration ({Embedded HMI, Standalone HMI}, Technology {Motion HMI, Bionic HMI, Tactile HMI, Acoustic HMI}, End-user Industry {Process industries [Oil & Gas, Food & beverages, Pharmaceuticals, Chemicals, Energy & power, Metals & mining, Water & wastewater, Others], Discrete industry [Automotive, Aerospace & defense, Packaging, Medical devices, Semiconductor & electronics, Others]}), AI In Manufacturing (Offering {Hardware [Processor MPU, GPU, FPGA, ASIC, Memory, Network], Software [AI solutions- | On-premises, Cloud |, AI platform- | Machine learning framework, Application program interface |], Services [Deployment & integration, Support & maintenance]}, Technology {Machine learning [Deep learning, Supervised learning, Reinforcement learning, Reinforcement learning, Others], Natural language processing [Context-aware computing, Computer vision]}, Application {Predictive maintenance and machinery inspection, Material movement, Production planning, Field services, Quality control, Cybersecurity, Industrial robots, Reclamation}, Digital Twin {Technology [Internet of Things (IOT), Blockchain, Artificial intelligence & machine learning, Artificial intelligence & machine learning, Big data analytics, 5G], Usage Type [Product digital twin, Process digital twin, System digital twin], Application [Product design & development, Performance monitoring, Predictive maintenance, Inventory management, Business optimization, Others]}, Automated Guided Vehicles (AGV) {Type [Tow vehicles, Unit load carriers, Pallet trucks, Assembly line vehicles, Forklift trucks, Others], Navigation Technology [Laser guidance, Magnetic guidance, Inductive guidance, Optical tape guidance, Vision guidance, Others]}, Machine Condition Monitoring {Monitoring Technique [Vibration monitoring, Embedded systems, Vibration analyzers and meters, Thermography, Oil analysis, Corrosion monitoring, Ultrasound emission, Motor current analysis], Offering [Hardware – Vibration sensors, Accelerometers, Tachometers, Infrared sensors, Spectrometers, Ultrasound detectors, Spectrum analyzers, Corrosion probes], Software [Data integration, Diagnostic reporting, Order tracking analysis, Parameter calculation], Deployment Type [On-premises deployment, Cloud deployment], Monitoring Process [Online condition monitoring, Portable condition monitoring]})IndustryManufacturing, Automotive, Energy, Medical, Semiconductor & Electronics, Food & Beverage, Oil & Gas, Aerospace, Metals & Mining, Chemicals, and OthersRequest Free Customization of this report:
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Internet of Things (IoT) Technology to Remain Indispensable for Industry 4.0
Internet of Things (IoT) remains the most crucial technology in global Industry 4.0 market growth owing to its role in interconnectivity and automation across different verticals. Advancements in connectivity technologies and rising use of automation in different industry verticals are also estimated to help this sub-segment gain an impressive market share. Surging demand for predictive maintenance will also boost the adoption of IoT technology in the long run.
Advanced robotic technologies are also slated to gain traction in the Industry 4.0 market. Growing acceptance of robots and high investments in advancements of robotic technologies are also slated to create new opportunities for providers of advanced robotics in the Industry 4.0 market. The low margin of error and the immense scope of automation are key benefits of robotics that help this sub-segment flourish.
Artificial intelligence (AI) will be another popular technology in the Industry 4.0 world going forward. Increasing demand for continuous monitoring, real-time analytics, and predictive maintenance are slated to help the demand for artificial intelligence in the future. The rising use of IoT devices will also boost the demand for cloud computing technology in the long run.
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Manufacturing Vertical to Spearhead Industry 4.0 Market Development
The manufacturing vertical is estimated to be at the forefront when it comes to Industry 4.0 adoption. The surge in use of robotics, advanced technologies, and smart manufacturing practices sets the tone for Industry 4.0 in this industry vertical. High emphasis on improving manufacturing efficiency, reducing downtime, and maximizing profits are all contributing to the high market share of this sub-segment.
The automotive industry is another vertical where Industry 4.0 market players could invest to get good returns. The high adoption of advanced robotics and other smart manufacturing technologies to maximize production allows this sub-segment to become a crucial one for Industry 4.0 providers. The aerospace and defense industry vertical also shows a lot of promise for Industry 4.0 companies going forward. Growing demand for advanced manufacturing techniques and technologies to create complex aerospace components is helping Industry 4.0 market growth via this segment.
The oil & gas industry is also estimated to embrace Industry 4.0 trend with open hands as they try to improve their operations and promote better resource utilization. High demand for predictive maintenance to reduce downtime and the growing adoption of digital oilfield solutions are estimated to bolster Industry 4.0 market development in the long run.
To sum it up, the application scope for Industry 4.0 is endless as automation and digitization pick up pace around the world. High investments in development of IoT and AI technologies will create better opportunities for Industry 4.0 companies in the future. The manufacturing industry will remain the top revenue generating sub-segment and more opportunities for aerospace, automotive, and oil & gas verticals will be seen over the coming years.
Related Report:
Digital Twin Market
Cyber Security Market
Artificial Intelligence (AI) Market
Internet Of Things (IoT) Market
Machine Learning Market
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Artificial Intelligence
Generative AI Cybersecurity Market worth $40.1 billion by 2030 – Exclusive Report by MarketsandMarkets™
CHICAGO, July 26, 2024 /PRNewswire/ — The Generative AI cybersecurity Market is anticipated to experience substantial expansion, ascending from a value of USD 7.1 billion in 2024 to a substantial worth of USD 40.1 billion by the year 2030, according to a new report by MarketsandMarkets™. This growth trajectory reflects a robust compound annual growth rate (CAGR) of 33.4% over the forecast period.
Browse in-depth TOC on “Generative AI cybersecurity Market”
350 – Tables 60 – Figures450 – Pages
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Scope of the Report
Report Metrics
Details
Market size available for years
2019–2030
Base year considered
2023
Forecast period
2024–2030
Forecast units
USD (Million)
Segments Covered
Offering, Generative AI-based Cybersecurity, Cybersecurity for Generative AI, Security Type, End-user, and Region
Geographies covered
North America, Europe, Asia Pacific, Middle East & Africa, and Latin America
Companies covered
Microsoft (US), IBM (US), Google (US), SentinelOne (US), AWS (US), NVIDIA (US), Cisco (US), CrowdStrike (US), Fortinet (US), Zscaler (US), Trend Micro (Japan), Palo Alto Networks (US), BlackBerry (Canada), Darktrace (UK), F5 (US), Okta (US), Sangfor (China), SecurityScorecard (US), Sophos (UK), Broadcom (US), Trellix (US), Veracode (US), LexisNexis (US), Abnormal Security (US), Adversa AI (Israel), Aquasec (US), BigID (US), Checkmarx (US), Cohesity (US), Credo AI (US), Cybereason (US), DeepKeep (Israel), Elastic NV (US), Flashpoint (US), Lakera (US), MOSTLY AI (Austria), Recorded Future (US), Secureframe (US), Skyflow (US), SlashNext (US), Snyk (US), Tenable (US), TrojAI (Canada), VirusTotal (Spain), XenonStack (UAE), and Zerofox (US).
This dramatic surge is being fueled by a number of causes. The primary growth driver is the enhancement of existing cybersecurity tools through generative AI algorithms by improving anomaly detection, automating threat hunting and penetration testing, and providing complex simulations for security testing purposes. These techniques enable various cyber-attack scenarios that can be simulated using the Generative Adversarial Networks (GANs), thus enabling the development of better preparedness and response strategies. On the other hand, it requires special cyber security tools to protect generative AI workloads against unique vulnerabilities such as adversarial attacks, model inversions and LLM poisoning. These tools include differential privacy and secure multi-party computation that are integrated into AI systems for training and deployment data protection purposes.
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Generative AI apps security segment will account for largest market share during the forecast period.
The cybersecurity landscape is rapidly changing for generative AI apps, which are already making their way into chatbots, content creation tools like word processors, and personalized recommendation systems. According to McAfee, 55% of these programs have had security breaches. This highlights the dire need for stronger protective measures from unauthorized access. Several generative AI applications that use adversarial techniques to force the desired reaction out of intelligent machines.
Therefore, there is a pressing demand in the number of developers who ensure that such machines are made more robust through techniques like adversarially trained models and resistant architectures. Finally, the usage of secure enclaves plus hardware-based security measures is growing off late, mainly aimed at safeguarding vulnerable AI computations from being tampered with. For instance, OpenAI has very strict security rules meant to protect GPT models thereby ensuring data integrity and user privacy.
By end-user, government & defense sector is poised to account for larger market share in 2024.
Government as well as defense industries are increasingly resorting to generative AI for cyber security purposes due to the urgency of protecting sensitive information and national security. According to a recent CSIS report, AI is being integrated into the cybersecurity framework of 43% of government agencies which resultantly improves their ability to identify and counter threats. As an example, the United States Department of Defense has started using artificial intelligence (AI) based security solutions backed by generative AI that can create fictitious cyber-attacks, thereby providing them with enhanced preparedness against advanced types of threats.
This technology also helps these sectors handle and analyze large volumes of data more effectively, giving valuable insights that will enable them prevent or mitigate cyber threats. This trend demonstrates an increasing reliance on generative AI in fortifying cyber security measures so as to ensure that critical infrastructure and sensitive data remain secure in today’s intricate digital landscape.
By region, North America to hold the largest share by market value in 2024.
In 2024, North America will be the leading region based on market share due to its excellent technology infrastructure, substantial investments in AI-enabled cybersecurity and the presence of key players. Major cyber security research universities and tech companies such as Google, AWS, CrowdStrike, SentinelOne and IBM are present in this area, pushing them on the forefront of potent risk management technologies and generative AI tools for threat detection. For example, IBM’s security platform powered by AI has improved detection rates for threats up by 40%, thus proving the relevance of AI technology to enhancing cybersecurity.
Moreover, legislative instruments such as Cybersecurity Information Sharing Act (CISA) are being put in place to promote advanced cybersecurity technologies. As internet attacks continue getting more complicated, North American enterprises prefer generative artificial intelligence (AI), so as to enhance their safety measures pertaining to personal data and digital infrastructure.
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Top Key Companies in Generative AI cybersecurity Market:
The major players in the generative AI cybersecurity market include Palo Alto Networks (US), AWS (US), CrowdStrike (US), SentinelOne (US), and Google (US), along with SMEs and startups such as MOSTLY AI (Austria), XenonStack (UAE), BigID (US), Abnormal Security (US), and Adversa AI (Israel).
Browse Adjacent Market: Artificial Intelligence (AI) Market Research Reports & Consulting
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