IoT in Manufacturing Market by Component (Hardware, Services, Software), Manufacturing Type (Discrete Manufacturing, Process Manufacturing), Connectivity, Deployment Mode, Organization Size, Application, End-Use Industry - Global Forecast 2025-2030
Description
The IoT in Manufacturing Market was valued at USD 69.31 billion in 2024 and is projected to grow to USD 74.38 billion in 2025, with a CAGR of 8.00%, reaching USD 110.03 billion by 2030.
A concise orientation to the industrial IoT revolution outlining how connected devices, analytics, and services are redefining manufacturing operations and strategy
The industrial Internet of Things is accelerating a fundamental reimagining of manufacturing architectures, where connected devices, edge computing, and advanced analytics converge to deliver operational visibility and control previously unattainable. Leaders are integrating sensors, gateways, and machine intelligence to reduce downtime, optimize throughput, and enhance safety, while pursuing new value streams that extend beyond traditional production metrics. As manufacturers prioritize resiliency, digital threads are enabling near real-time orchestration across distributed assets and suppliers, creating opportunities to respond faster to demand variability and supply disruptions.
Across this environment, the interplay of hardware, software, and professional services is becoming central to transformation initiatives. Organizations are shifting from isolated pilot projects to scaled deployments that require interoperable device ecosystems, robust connectivity, and disciplined data governance. Consequently, cross-functional teams increasingly coordinate investments in sensorization, edge platforms, and analytics to align technology adoption with measurable operational objectives. In short, the modern factory is evolving into a connected, intelligent ecosystem where technology choices and organizational readiness jointly determine success.
How converging sensing, connectivity, edge compute, and service models are driving structural shifts in manufacturing operations and competitive advantage
Manufacturing is experiencing transformative shifts as digital and physical systems fuse to create more adaptive and efficient production environments. The first shift is toward pervasive sensing and visibility: an expanding array of sensors and vision systems is supplying richer operational data, which, when combined with robust edge processing, shortens decision cycles and enables local autonomy. This shift is accompanied by a rebalancing of compute architectures, where edge and cloud complement each other to deliver both latency-sensitive control and enterprise-scale analytics.
A second major change is the maturation of connectivity options. With the emergence of higher-performance cellular standards alongside reliable wired and wireless links, companies can design networks that match application requirements for latency, throughput, and coverage. Third, service models are evolving; manufacturers increasingly rely on managed and professional services to integrate complex solution stacks, maintain asset fleets, and extract ongoing value from analytics investments. Finally, industry practices are moving toward digital twins and simulation-driven engineering to test scenarios, optimize operations, and shorten development cycles. These shifts collectively enable manufacturers to scale pilots into sustainable, resilient, and competitive operations.
Assessing how evolving tariff dynamics are reshaping hardware procurement, supplier strategies, and resilient sourcing approaches within manufacturing ecosystems
Tariff policy changes and trade measures affecting hardware components and connectivity equipment are exerting a tangible influence on procurement strategies and supply chain design. As tariffs adjust the landed cost of sensors, cameras, gateways, and robotic systems, procurement teams are compelled to reassess supplier diversification, total cost of ownership, and the viability of local sourcing options. In response, many manufacturers are evaluating dual-sourcing arrangements, qualification of regional suppliers, and longer inventory planning horizons to mitigate cost volatility and delivery uncertainty.
Beyond direct cost impacts, tariffs are prompting changes in product architecture and sourcing decisions that prioritize modularity and interoperability. Companies are exploring whether to standardize on components that are more readily available within preferred trade zones or to invest in software-defined capabilities that reduce dependency on specific hardware configurations. Additionally, tariffs influence the cadence of refresh cycles and the economics of maintaining legacy equipment versus accelerated upgrades. Overall, trade policy dynamics are encouraging strategic supply chain resilience, closer collaboration with suppliers, and a heightened focus on procurement processes that can adapt to regulatory shifts without compromising operational continuity.
Comprehensive segmentation insights combining components, connectivity layers, manufacturing types, deployment modes, organization scale, and industry-specific application priorities
Segmentation analysis reveals that effective IoT strategies require coordinated decisions across components, connectivity, manufacturing types, deployment modes, organization sizes, applications, and end-use industries. Component choices span hardware, services, and solution categories, with hardware selections including actuators, cameras and vision systems, connectivity modules, controllers, gateways and edge devices, robotic systems, and an expanding set of sensors. Services demand both managed services for ongoing operations and professional services for integration, while solutions increasingly focus on analytics and visualization, application management, data management, device management, network management, and smart surveillance capabilities.
Connectivity decisions are equally pivotal, with manufacturers selecting from cellular options such as 4G LTE and 5G, satellite for remote operations, wired alternatives like Ethernet and fieldbus for deterministic control, and wireless standards including Bluetooth, near field communication, Wi‑Fi, and Zigbee to support local connectivity needs. The nature of manufacturing-whether discrete or process-shapes functional requirements: discrete environments may emphasize high-volume or low-volume production variability, while process settings consider batch and continuous workflows and the associated control and monitoring demands. Deployment mode choices between cloud-based and on-premises architectures influence latency, data sovereignty, and integration pathways, while organization size determines governance, funding cadence, and the scale of implementation efforts for both large enterprises and small and medium-sized enterprises.
Application-level priorities center on condition monitoring, digital twin and simulation, energy management, inventory and asset tracking, predictive maintenance, production monitoring, safety and compliance, and supply chain and logistics. Within condition monitoring, thermal monitoring and vibration analysis remain foundational for asset health, and digital twin initiatives differentiate into product twins that focus on design and lifecycle and system twins that model operational behavior. Finally, industry context-ranging from aerospace and defense to automotive, chemicals, consumer goods, electronics and semiconductors, food and beverage, metals and mining, oil and gas, pharmaceuticals and biotechnology, and textiles-conditions regulatory requirements, reliability targets, and domain-specific use cases that shape solution design and deployment strategies.
Regional perspectives on connectivity, regulatory priorities, and deployment strategies that influence IoT adoption across the Americas, EMEA, and Asia-Pacific manufacturing hubs
Regional dynamics shape the path to IoT adoption, with each geopolitical cluster presenting distinct opportunities and constraints that influence technology choices and deployment timelines. In the Americas, established industrial bases are combining automation modernization with strong investments in predictive maintenance and digital twin capabilities, and there is growing activity around modernizing legacy assets through retrofitting and edge analytics. Investment patterns emphasize integration with enterprise systems and compliance with regional regulatory frameworks, while partnerships between manufacturers and solution providers accelerate pilots into operations.
Across Europe, the Middle East and Africa, priorities include stringent regulatory compliance, a strong emphasis on sustainability and energy management, and a diverse supplier landscape that spans highly industrialized markets to emerging manufacturing centers. Organizations in this region often balance harmonization of standards with localized customization to meet jurisdictional requirements. In the Asia-Pacific region, rapid industrial expansion, high adoption of automation in automotive and electronics manufacturing, and investments in both wired and wireless connectivity create a fertile environment for scaling IoT solutions. Supply chain density, proximity to component manufacturers, and increasing emphasis on smart factory initiatives drive unique patterns of vendor collaboration and solution integration. Recognizing these regional differentiators enables leaders to tailor deployment strategies that align with local infrastructure, regulatory expectations, and operational priorities.
Competitive and partner ecosystem characteristics emphasizing interoperability, integration capabilities, and service excellence among leading industrial IoT providers
Competitive landscapes in industrial IoT are defined by a mix of incumbent automation vendors, specialized sensor manufacturers, software platform providers, and integrators offering managed services. Leading technology providers differentiate through end-to-end solution depth, modular architectures that support incremental adoption, and partnerships that bridge hardware, connectivity, and analytics. Strategic collaborations and alliance ecosystems are common, with cloud and edge platform vendors working alongside system integrators to deliver domain-specific solutions that meet stringent reliability and security requirements.
Market leaders prioritize interoperability and open standards to reduce vendor lock-in, while smaller innovators focus on niche capabilities such as advanced vision systems, machine-level control algorithms, or verticalized analytics for specific end-use industries. Service providers with strong professional services teams help accelerate deployments by delivering project management, systems integration, and change management expertise. In this environment, companies that combine robust product portfolios with demonstrated implementation experience and clear service-level commitments are best positioned to capture enterprise-scale engagements and long-term service relationships.
Actionable recommendations for manufacturing leaders to prioritize outcomes, build foundational capabilities, and scale IoT initiatives with resilience and governance
Leaders should pursue a pragmatic, phased approach that aligns technical pilots with clear business outcomes and organizational readiness. Start by defining prioritized use cases such as predictive maintenance, production monitoring, or digital twin initiatives, and establish measurable KPIs that tie directly to operational goals. Invest in foundational capabilities-reliable connectivity, secure edge compute, and disciplined data management-before scaling to enterprise-wide deployments, and use pilot projects to validate integration pathways and ROI assumptions while minimizing operational disruption.
Organizational change is as important as technology; allocate resources to upskilling operations and IT teams, and create cross-functional governance structures that retain accountability for data quality and cybersecurity. Consider diversified sourcing strategies to mitigate supply chain risk, and adopt modular hardware and software components that accommodate evolving standards and connectivity options. Finally, cultivate partnerships with experienced system integrators and service providers to accelerate deployment while preserving flexibility, and prioritize solutions that facilitate continuous improvement through analytics, digital twins, and closed-loop optimization.
Transparent research methodology combining expert interviews, technical analysis, and scenario evaluation to ensure robust and operationally relevant insights
This research synthesizes qualitative and quantitative inputs derived from expert interviews, vendor documentation, technology white papers, and primary discussions with industrial stakeholders. Analytical methods include comparative evaluation of solution architectures, connectivity trade-off analyses, and scenario-based assessments that examine implications for operations, procurement, and organizational readiness. Data integrity was maintained through cross-validation across multiple sources, while findings were reviewed iteratively with domain experts to ensure relevance and applicability across diverse manufacturing contexts.
The methodology emphasizes transparency in assumptions and a focus on operational impact rather than vendor marketing claims. Use case selection was informed by prevalence in production environments and potential to drive measurable outcomes. Connectivity and architecture evaluations considered latency, reliability, and security requirements aligned to application needs. Where applicable, sensitivity analyses explored variations in sourcing, deployment mode, and regional constraints to illuminate resilient strategies for decision-makers facing uncertain external conditions.
A succinct conclusion emphasizing the interplay of technology, organization, and governance as the foundation for successful IoT-driven manufacturing transformation
The convergence of sensing, connectivity, edge compute, and analytical platforms is redefining how manufacturers operate, compete, and innovate. Organizations that systematically align technology adoption with operational priorities, governance structures, and supply chain resilience will be best positioned to realize the productivity, quality, and sustainability benefits of industrial IoT. While technical choices such as connectivity options, deployment modes, and component selection remain critical, the human and organizational factors-skills, processes, and governance-determine whether those technologies deliver sustained value.
Looking ahead, manufacturers that adopt modular architectures, prioritize interoperability, and cultivate strategic partnerships will minimize risk and accelerate time to value. By focusing on measurable use cases and maintaining disciplined change management, leaders can move from pilot successes to scaled operations that enhance competitiveness and responsiveness in increasingly dynamic markets. The path to a digitally enabled factory is iterative, and disciplined execution grounded in practical metrics will distinguish successful transformations from fragmented experiments.
Market Segmentation & Coverage
This research report categorizes to forecast the revenues and analyze trends in each of the following sub-segmentations:
Component
Hardware
Actuator
Cameras & Vision Systems
Connectivity Modules
Controller
Gateways & Edge Devices
Robotic Systems
Sensor
Services
Managed Services
Professional Services
Software
Analytics & Visualization
Application Management
Data Management
Device Management
Network Management
Smart Surveillance
Manufacturing Type
Discrete Manufacturing
High-Volume
Low-Volume
Process Manufacturing
Batch
Continuous
Connectivity
Wired
Ethernet
Fieldbus
Wireless
Bluetooth
Cellular
4G LTE
5G
Near Field Communication
Satellite
Wi‑Fi
Zigbee
Deployment Mode
Cloud-Based
On-Premises
Organization Size
Large Enterprises
Small & Medium-Sized Enterprises
Application
Condition Monitoring
Thermal Monitoring
Vibration Analysis
Digital Twin & Simulation
Product Twins
System Twins
Energy Management
Inventory & Asset Tracking
Predictive Maintenance
Production Monitoring
Safety & Compliance
End-Use Industry
Aerospace & Defense
Automotive
Chemicals
Consumer Goods
Electronics & Semiconductors
Food & Beverage
Metals & Mining
Oil & Gas
Pharmaceuticals & Biotechnology
Textiles
This research report categorizes to forecast the revenues and analyze trends in each of the following sub-regions:
Americas
North America
United States
Canada
Mexico
Latin America
Brazil
Argentina
Chile
Colombia
Peru
Europe, Middle East & Africa
Europe
United Kingdom
Germany
France
Russia
Italy
Spain
Netherlands
Sweden
Poland
Switzerland
Middle East
United Arab Emirates
Saudi Arabia
Qatar
Turkey
Israel
Africa
South Africa
Nigeria
Egypt
Kenya
Asia-Pacific
China
India
Japan
Australia
South Korea
Indonesia
Thailand
Malaysia
Singapore
Taiwan
This research report categorizes to delves into recent significant developments and analyze trends in each of the following companies:
ABB Ltd.
Accenture PLC
Atos SE
Cisco Systems Inc.
Dell Technologies Inc.
Fujitsu Ltd.
GE Vernova by General Electric Company
HCL Technologies Ltd.
Hewlett Packard Enterprise Development LP
Hitachi Ltd.
Huawei Technologies Co., Ltd.
Intel Corporation
International Business Machines Corporation
Litmus Automation Inc.
Microsoft Corporation
NTT DATA Group Corporation
Oracle Corporation
PTC Inc.
Robert Bosch GmbH
Rockwell Automation
SAP SE
Schneider Electric SE
Siemens AG
TATA Consultancy Services Limited
Telefonaktiebolaget LM Ericsson
Wind River Systems, Inc. by Aptiv PLC
Amazon Web Services, Inc.
Honeywell International Inc.
Emerson Electric Co.
Please Note: PDF & Excel + Online Access - 1 Year
A concise orientation to the industrial IoT revolution outlining how connected devices, analytics, and services are redefining manufacturing operations and strategy
The industrial Internet of Things is accelerating a fundamental reimagining of manufacturing architectures, where connected devices, edge computing, and advanced analytics converge to deliver operational visibility and control previously unattainable. Leaders are integrating sensors, gateways, and machine intelligence to reduce downtime, optimize throughput, and enhance safety, while pursuing new value streams that extend beyond traditional production metrics. As manufacturers prioritize resiliency, digital threads are enabling near real-time orchestration across distributed assets and suppliers, creating opportunities to respond faster to demand variability and supply disruptions.
Across this environment, the interplay of hardware, software, and professional services is becoming central to transformation initiatives. Organizations are shifting from isolated pilot projects to scaled deployments that require interoperable device ecosystems, robust connectivity, and disciplined data governance. Consequently, cross-functional teams increasingly coordinate investments in sensorization, edge platforms, and analytics to align technology adoption with measurable operational objectives. In short, the modern factory is evolving into a connected, intelligent ecosystem where technology choices and organizational readiness jointly determine success.
How converging sensing, connectivity, edge compute, and service models are driving structural shifts in manufacturing operations and competitive advantage
Manufacturing is experiencing transformative shifts as digital and physical systems fuse to create more adaptive and efficient production environments. The first shift is toward pervasive sensing and visibility: an expanding array of sensors and vision systems is supplying richer operational data, which, when combined with robust edge processing, shortens decision cycles and enables local autonomy. This shift is accompanied by a rebalancing of compute architectures, where edge and cloud complement each other to deliver both latency-sensitive control and enterprise-scale analytics.
A second major change is the maturation of connectivity options. With the emergence of higher-performance cellular standards alongside reliable wired and wireless links, companies can design networks that match application requirements for latency, throughput, and coverage. Third, service models are evolving; manufacturers increasingly rely on managed and professional services to integrate complex solution stacks, maintain asset fleets, and extract ongoing value from analytics investments. Finally, industry practices are moving toward digital twins and simulation-driven engineering to test scenarios, optimize operations, and shorten development cycles. These shifts collectively enable manufacturers to scale pilots into sustainable, resilient, and competitive operations.
Assessing how evolving tariff dynamics are reshaping hardware procurement, supplier strategies, and resilient sourcing approaches within manufacturing ecosystems
Tariff policy changes and trade measures affecting hardware components and connectivity equipment are exerting a tangible influence on procurement strategies and supply chain design. As tariffs adjust the landed cost of sensors, cameras, gateways, and robotic systems, procurement teams are compelled to reassess supplier diversification, total cost of ownership, and the viability of local sourcing options. In response, many manufacturers are evaluating dual-sourcing arrangements, qualification of regional suppliers, and longer inventory planning horizons to mitigate cost volatility and delivery uncertainty.
Beyond direct cost impacts, tariffs are prompting changes in product architecture and sourcing decisions that prioritize modularity and interoperability. Companies are exploring whether to standardize on components that are more readily available within preferred trade zones or to invest in software-defined capabilities that reduce dependency on specific hardware configurations. Additionally, tariffs influence the cadence of refresh cycles and the economics of maintaining legacy equipment versus accelerated upgrades. Overall, trade policy dynamics are encouraging strategic supply chain resilience, closer collaboration with suppliers, and a heightened focus on procurement processes that can adapt to regulatory shifts without compromising operational continuity.
Comprehensive segmentation insights combining components, connectivity layers, manufacturing types, deployment modes, organization scale, and industry-specific application priorities
Segmentation analysis reveals that effective IoT strategies require coordinated decisions across components, connectivity, manufacturing types, deployment modes, organization sizes, applications, and end-use industries. Component choices span hardware, services, and solution categories, with hardware selections including actuators, cameras and vision systems, connectivity modules, controllers, gateways and edge devices, robotic systems, and an expanding set of sensors. Services demand both managed services for ongoing operations and professional services for integration, while solutions increasingly focus on analytics and visualization, application management, data management, device management, network management, and smart surveillance capabilities.
Connectivity decisions are equally pivotal, with manufacturers selecting from cellular options such as 4G LTE and 5G, satellite for remote operations, wired alternatives like Ethernet and fieldbus for deterministic control, and wireless standards including Bluetooth, near field communication, Wi‑Fi, and Zigbee to support local connectivity needs. The nature of manufacturing-whether discrete or process-shapes functional requirements: discrete environments may emphasize high-volume or low-volume production variability, while process settings consider batch and continuous workflows and the associated control and monitoring demands. Deployment mode choices between cloud-based and on-premises architectures influence latency, data sovereignty, and integration pathways, while organization size determines governance, funding cadence, and the scale of implementation efforts for both large enterprises and small and medium-sized enterprises.
Application-level priorities center on condition monitoring, digital twin and simulation, energy management, inventory and asset tracking, predictive maintenance, production monitoring, safety and compliance, and supply chain and logistics. Within condition monitoring, thermal monitoring and vibration analysis remain foundational for asset health, and digital twin initiatives differentiate into product twins that focus on design and lifecycle and system twins that model operational behavior. Finally, industry context-ranging from aerospace and defense to automotive, chemicals, consumer goods, electronics and semiconductors, food and beverage, metals and mining, oil and gas, pharmaceuticals and biotechnology, and textiles-conditions regulatory requirements, reliability targets, and domain-specific use cases that shape solution design and deployment strategies.
Regional perspectives on connectivity, regulatory priorities, and deployment strategies that influence IoT adoption across the Americas, EMEA, and Asia-Pacific manufacturing hubs
Regional dynamics shape the path to IoT adoption, with each geopolitical cluster presenting distinct opportunities and constraints that influence technology choices and deployment timelines. In the Americas, established industrial bases are combining automation modernization with strong investments in predictive maintenance and digital twin capabilities, and there is growing activity around modernizing legacy assets through retrofitting and edge analytics. Investment patterns emphasize integration with enterprise systems and compliance with regional regulatory frameworks, while partnerships between manufacturers and solution providers accelerate pilots into operations.
Across Europe, the Middle East and Africa, priorities include stringent regulatory compliance, a strong emphasis on sustainability and energy management, and a diverse supplier landscape that spans highly industrialized markets to emerging manufacturing centers. Organizations in this region often balance harmonization of standards with localized customization to meet jurisdictional requirements. In the Asia-Pacific region, rapid industrial expansion, high adoption of automation in automotive and electronics manufacturing, and investments in both wired and wireless connectivity create a fertile environment for scaling IoT solutions. Supply chain density, proximity to component manufacturers, and increasing emphasis on smart factory initiatives drive unique patterns of vendor collaboration and solution integration. Recognizing these regional differentiators enables leaders to tailor deployment strategies that align with local infrastructure, regulatory expectations, and operational priorities.
Competitive and partner ecosystem characteristics emphasizing interoperability, integration capabilities, and service excellence among leading industrial IoT providers
Competitive landscapes in industrial IoT are defined by a mix of incumbent automation vendors, specialized sensor manufacturers, software platform providers, and integrators offering managed services. Leading technology providers differentiate through end-to-end solution depth, modular architectures that support incremental adoption, and partnerships that bridge hardware, connectivity, and analytics. Strategic collaborations and alliance ecosystems are common, with cloud and edge platform vendors working alongside system integrators to deliver domain-specific solutions that meet stringent reliability and security requirements.
Market leaders prioritize interoperability and open standards to reduce vendor lock-in, while smaller innovators focus on niche capabilities such as advanced vision systems, machine-level control algorithms, or verticalized analytics for specific end-use industries. Service providers with strong professional services teams help accelerate deployments by delivering project management, systems integration, and change management expertise. In this environment, companies that combine robust product portfolios with demonstrated implementation experience and clear service-level commitments are best positioned to capture enterprise-scale engagements and long-term service relationships.
Actionable recommendations for manufacturing leaders to prioritize outcomes, build foundational capabilities, and scale IoT initiatives with resilience and governance
Leaders should pursue a pragmatic, phased approach that aligns technical pilots with clear business outcomes and organizational readiness. Start by defining prioritized use cases such as predictive maintenance, production monitoring, or digital twin initiatives, and establish measurable KPIs that tie directly to operational goals. Invest in foundational capabilities-reliable connectivity, secure edge compute, and disciplined data management-before scaling to enterprise-wide deployments, and use pilot projects to validate integration pathways and ROI assumptions while minimizing operational disruption.
Organizational change is as important as technology; allocate resources to upskilling operations and IT teams, and create cross-functional governance structures that retain accountability for data quality and cybersecurity. Consider diversified sourcing strategies to mitigate supply chain risk, and adopt modular hardware and software components that accommodate evolving standards and connectivity options. Finally, cultivate partnerships with experienced system integrators and service providers to accelerate deployment while preserving flexibility, and prioritize solutions that facilitate continuous improvement through analytics, digital twins, and closed-loop optimization.
Transparent research methodology combining expert interviews, technical analysis, and scenario evaluation to ensure robust and operationally relevant insights
This research synthesizes qualitative and quantitative inputs derived from expert interviews, vendor documentation, technology white papers, and primary discussions with industrial stakeholders. Analytical methods include comparative evaluation of solution architectures, connectivity trade-off analyses, and scenario-based assessments that examine implications for operations, procurement, and organizational readiness. Data integrity was maintained through cross-validation across multiple sources, while findings were reviewed iteratively with domain experts to ensure relevance and applicability across diverse manufacturing contexts.
The methodology emphasizes transparency in assumptions and a focus on operational impact rather than vendor marketing claims. Use case selection was informed by prevalence in production environments and potential to drive measurable outcomes. Connectivity and architecture evaluations considered latency, reliability, and security requirements aligned to application needs. Where applicable, sensitivity analyses explored variations in sourcing, deployment mode, and regional constraints to illuminate resilient strategies for decision-makers facing uncertain external conditions.
A succinct conclusion emphasizing the interplay of technology, organization, and governance as the foundation for successful IoT-driven manufacturing transformation
The convergence of sensing, connectivity, edge compute, and analytical platforms is redefining how manufacturers operate, compete, and innovate. Organizations that systematically align technology adoption with operational priorities, governance structures, and supply chain resilience will be best positioned to realize the productivity, quality, and sustainability benefits of industrial IoT. While technical choices such as connectivity options, deployment modes, and component selection remain critical, the human and organizational factors-skills, processes, and governance-determine whether those technologies deliver sustained value.
Looking ahead, manufacturers that adopt modular architectures, prioritize interoperability, and cultivate strategic partnerships will minimize risk and accelerate time to value. By focusing on measurable use cases and maintaining disciplined change management, leaders can move from pilot successes to scaled operations that enhance competitiveness and responsiveness in increasingly dynamic markets. The path to a digitally enabled factory is iterative, and disciplined execution grounded in practical metrics will distinguish successful transformations from fragmented experiments.
Market Segmentation & Coverage
This research report categorizes to forecast the revenues and analyze trends in each of the following sub-segmentations:
Component
Hardware
Actuator
Cameras & Vision Systems
Connectivity Modules
Controller
Gateways & Edge Devices
Robotic Systems
Sensor
Services
Managed Services
Professional Services
Software
Analytics & Visualization
Application Management
Data Management
Device Management
Network Management
Smart Surveillance
Manufacturing Type
Discrete Manufacturing
High-Volume
Low-Volume
Process Manufacturing
Batch
Continuous
Connectivity
Wired
Ethernet
Fieldbus
Wireless
Bluetooth
Cellular
4G LTE
5G
Near Field Communication
Satellite
Wi‑Fi
Zigbee
Deployment Mode
Cloud-Based
On-Premises
Organization Size
Large Enterprises
Small & Medium-Sized Enterprises
Application
Condition Monitoring
Thermal Monitoring
Vibration Analysis
Digital Twin & Simulation
Product Twins
System Twins
Energy Management
Inventory & Asset Tracking
Predictive Maintenance
Production Monitoring
Safety & Compliance
End-Use Industry
Aerospace & Defense
Automotive
Chemicals
Consumer Goods
Electronics & Semiconductors
Food & Beverage
Metals & Mining
Oil & Gas
Pharmaceuticals & Biotechnology
Textiles
This research report categorizes to forecast the revenues and analyze trends in each of the following sub-regions:
Americas
North America
United States
Canada
Mexico
Latin America
Brazil
Argentina
Chile
Colombia
Peru
Europe, Middle East & Africa
Europe
United Kingdom
Germany
France
Russia
Italy
Spain
Netherlands
Sweden
Poland
Switzerland
Middle East
United Arab Emirates
Saudi Arabia
Qatar
Turkey
Israel
Africa
South Africa
Nigeria
Egypt
Kenya
Asia-Pacific
China
India
Japan
Australia
South Korea
Indonesia
Thailand
Malaysia
Singapore
Taiwan
This research report categorizes to delves into recent significant developments and analyze trends in each of the following companies:
ABB Ltd.
Accenture PLC
Atos SE
Cisco Systems Inc.
Dell Technologies Inc.
Fujitsu Ltd.
GE Vernova by General Electric Company
HCL Technologies Ltd.
Hewlett Packard Enterprise Development LP
Hitachi Ltd.
Huawei Technologies Co., Ltd.
Intel Corporation
International Business Machines Corporation
Litmus Automation Inc.
Microsoft Corporation
NTT DATA Group Corporation
Oracle Corporation
PTC Inc.
Robert Bosch GmbH
Rockwell Automation
SAP SE
Schneider Electric SE
Siemens AG
TATA Consultancy Services Limited
Telefonaktiebolaget LM Ericsson
Wind River Systems, Inc. by Aptiv PLC
Amazon Web Services, Inc.
Honeywell International Inc.
Emerson Electric Co.
Please Note: PDF & Excel + Online Access - 1 Year
Table of Contents
182 Pages
- 1. Preface
- 1.1. Objectives of the Study
- 1.2. Market Segmentation & Coverage
- 1.3. Years Considered for the Study
- 1.4. Currency & Pricing
- 1.5. Language
- 1.6. Stakeholders
- 2. Research Methodology
- 3. Executive Summary
- 4. Market Overview
- 5. Market Insights
- 5.1. Growing focus on cybersecurity frameworks tailored for IoT in industrial environments
- 5.2. Integration of AI and machine learning for predictive maintenance in manufacturing IoT networks
- 5.3. Increase in energy management solutions leveraging IoT for sustainable manufacturing operations
- 5.4. Use of IoT data analytics to drive operational efficiency and reduce downtime in production lines
- 5.5. Deployment of automated quality control systems driven by IoT-enabled visual inspection
- 5.6. Utilization of digital twins for simulation and optimization of manufacturing processes
- 5.7. Implementation of 5G connectivity to enhnace speed and reliability of IoT devices in manufacturing
- 5.8. Adoption of advanced sensor technologies for improved asset tracking and monitoring
- 5.9. Convergence on unified namespace architectures to break data silos between PLCs, historians, MES, and ERP in brownfield plants
- 5.10. Cross-vendor interoperability testing programs that certify IoT-enabled machine tools and controllers for plug-and-play deployment at scale
- 6. Cumulative Impact of United States Tariffs 2025
- 7. Cumulative Impact of Artificial Intelligence 2025
- 8. IoT in Manufacturing Market, by Component
- 8.1. Hardware
- 8.1.1. Actuator
- 8.1.2. Cameras & Vision Systems
- 8.1.3. Connectivity Modules
- 8.1.4. Controller
- 8.1.5. Gateways & Edge Devices
- 8.1.6. Robotic Systems
- 8.1.7. Sensor
- 8.2. Services
- 8.2.1. Managed Services
- 8.2.2. Professional Services
- 8.3. Software
- 8.3.1. Analytics & Visualization
- 8.3.2. Application Management
- 8.3.3. Data Management
- 8.3.4. Device Management
- 8.3.5. Network Management
- 8.3.6. Smart Surveillance
- 9. IoT in Manufacturing Market, by Manufacturing Type
- 9.1. Discrete Manufacturing
- 9.1.1. High-Volume
- 9.1.2. Low-Volume
- 9.2. Process Manufacturing
- 9.2.1. Batch
- 9.2.2. Continuous
- 10. IoT in Manufacturing Market, by Connectivity
- 10.1. Wired
- 10.1.1. Ethernet
- 10.1.2. Fieldbus
- 10.2. Wireless
- 10.2.1. Bluetooth
- 10.2.2. Cellular
- 10.2.2.1. 4G LTE
- 10.2.2.2. 5G
- 10.2.3. Near Field Communication
- 10.2.4. Satellite
- 10.2.5. Wi‑Fi
- 10.2.6. Zigbee
- 11. IoT in Manufacturing Market, by Deployment Mode
- 11.1. Cloud-Based
- 11.2. On-Premises
- 12. IoT in Manufacturing Market, by Organization Size
- 12.1. Large Enterprises
- 12.2. Small & Medium-Sized Enterprises
- 13. IoT in Manufacturing Market, by Application
- 13.1. Condition Monitoring
- 13.1.1. Thermal Monitoring
- 13.1.2. Vibration Analysis
- 13.2. Digital Twin & Simulation
- 13.2.1. Product Twins
- 13.2.2. System Twins
- 13.3. Energy Management
- 13.4. Inventory & Asset Tracking
- 13.5. Predictive Maintenance
- 13.6. Production Monitoring
- 13.7. Safety & Compliance
- 14. IoT in Manufacturing Market, by End-Use Industry
- 14.1. Aerospace & Defense
- 14.2. Automotive
- 14.3. Chemicals
- 14.4. Consumer Goods
- 14.5. Electronics & Semiconductors
- 14.6. Food & Beverage
- 14.7. Metals & Mining
- 14.8. Oil & Gas
- 14.9. Pharmaceuticals & Biotechnology
- 14.10. Textiles
- 15. IoT in Manufacturing Market, by Region
- 15.1. Americas
- 15.1.1. North America
- 15.1.2. Latin America
- 15.2. Europe, Middle East & Africa
- 15.2.1. Europe
- 15.2.2. Middle East
- 15.2.3. Africa
- 15.3. Asia-Pacific
- 16. IoT in Manufacturing Market, by Group
- 16.1. ASEAN
- 16.2. GCC
- 16.3. European Union
- 16.4. BRICS
- 16.5. G7
- 16.6. NATO
- 17. IoT in Manufacturing Market, by Country
- 17.1. United States
- 17.2. Canada
- 17.3. Mexico
- 17.4. Brazil
- 17.5. United Kingdom
- 17.6. Germany
- 17.7. France
- 17.8. Russia
- 17.9. Italy
- 17.10. Spain
- 17.11. China
- 17.12. India
- 17.13. Japan
- 17.14. Australia
- 17.15. South Korea
- 18. Competitive Landscape
- 18.1. Market Share Analysis, 2024
- 18.2. FPNV Positioning Matrix, 2024
- 18.3. Competitive Analysis
- 18.3.1. ABB Ltd.
- 18.3.2. Atos SE
- 18.3.3. Cisco Systems Inc.
- 18.3.4. Fujitsu Ltd.
- 18.3.5. GE Vernova by General Electric Company
- 18.3.6. Hitachi Ltd.
- 18.3.7. Robert Bosch GmbH
- 18.3.8. Rockwell Automation
- 18.3.9. SAP SE
- 18.3.10. Schneider Electric SE
- 18.3.11. Siemens AG
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