Enterprise Manufacturing Intelligence Market Outlook 2032
The global enterprise manufacturing intelligence market size was USD 4.6 Billion in 2023 and is projected to reach USD 20.35 Billion by 2032, expanding at a CAGR of 16.5% during 2024–2032. The market growth is attributed to the increasing demand for real-time data analytics and process optimization in manufacturing operations.
Rising demand for operational excellence and data-driven insights is propelling the adoption of enterprise manufacturing intelligence (EMI) solutions globally. EMI integrates data from diverse manufacturing processes, enabling real-time analytics and actionable insights to optimize production efficiency and quality control. This trend reflects the industry's shift toward digital transformation and agile manufacturing practices to meet evolving customer demand and market dynamics.
Growing complexities in modern manufacturing environments have underscored the need for robust EMI systems that consolidate data from disparate sources. These systems empower manufacturers with comprehensive visibility into production operations, supply chain logistics, and equipment performance. EMI solutions drive continuous improvement initiatives, enhance predictive maintenance strategies, and enable proactive decision-making across the manufacturing value chain, by harnessing advanced analytics and machine learning capabilities.
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In January 2024, the European Commission introduced regulatory guidelines aimed at promoting digital transformation and data-driven decision-making in manufacturing sectors across the European Union. These guidelines emphasize the importance of leveraging technologies such as enterprise manufacturing intelligence (EMI) to enhance manufacturing efficiency, sustainability, and competitiveness in the global market. The regulatory framework encourages investments in EMI solutions and supports collaborative initiatives between industry stakeholders and regulatory bodies to drive innovation and growth in the manufacturing sector.
Impact of Artificial Intelligence (AI) in Enterprise Manufacturing Intelligence Market
Artificial Intelligence (AI) is revolutionizing enterprise manufacturing intelligence (EMI) by augmenting data analytics and decision-making capabilities. By leveraging AI algorithms, EMI systems analyze vast amounts of manufacturing data in real-time, identifying patterns, anomalies, and optimization opportunities. This enhanced data processing enables predictive maintenance, quality control enhancements, and proactive risk mitigation strategies, leading to improved operational efficiency and reduced downtime. For instance,
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In July 2023, ABB partnered with Microsoft to integrate generative AI into industrial applications, boosting safety, intelligence, and sustainability. This collaboration aims to enhance user interaction and optimize data value within ABB Ability Genix Industrial Analytics and AI Suite using Copilot capabilities. By leveraging Microsoft Azure OpenAI Service, ABB strengthens its comprehensive solution.
AI-powered EMI solutions facilitate advanced predictive modeling and simulation, empowering manufacturers to forecast demand, optimize production schedules, and streamline supply chain logistics. The integration of AI into EMI fosters a data-driven approach to manufacturing management, enabling agile responses to market fluctuations and customer demands.
Enterprise Manufacturing Intelligence Market Dynamics
Major Drivers
Growing focus on digital transformation initiatives in the manufacturing sector is driving the market. Enterprise manufacturing intelligence vendors, with manufacturers seeking to modernize their operations and harness data-driven insights to gain a competitive edge in the market, further fuel the market. For instance,
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In June 2022, Siemens introduced Siemens Xcelerator, an open digital business platform aimed at expediting digital transformation initiatives. The Siemens Xcelerator platform encompasses a carefully curated portfolio, an expanding partner ecosystem, and a dynamic marketplace, all intended to accelerate value creation across various sectors including industry, buildings, grids, and mobility.
Surging focus on regulatory compliance and quality assurance standards is propelling the market. Manufacturers invest in enterprise manufacturing intelligence solutions to ensure adherence to industry regulations, maintain product safety, and mitigate risks associated with non-compliance, boost the market.
Rising need for real-time visibility and insights into production operations is driving the adoption of enterprise manufacturing intelligence platforms. It enables manufacturers to monitor key performance indicators, track production metrics, and make data-driven decisions in real-time to optimize production efficiency and meet customer demand.
Existing Restraints
Regulatory complexities and compliance challenges are expected to hamper the market. Manufacturers face difficulties in aligning their systems with evolving regulatory requirements across different regions and industries, thus impeding the market.
High initial investment and implementation costs are anticipated to restrain the market, as manufacturers hesitate to invest in enterprise manufacturing intelligence solutions. This is due to the significant upfront expenses associated with software licenses, hardware infrastructure, and integration services, thereby impeding widespread adoption.
Data privacy and security concerns are projected to impede market expansion, with manufacturers expressing apprehensions about the confidentiality and integrity of sensitive production data stored and processed within enterprise manufacturing intelligence systems, leading to hesitancy in adopting these solutions.
Emerging Opportunities
Growing demand for predictive analytics solutions is expected to create lucrative opportunities in the market. Manufacturers seek to minimize downtime, reduce maintenance costs, and enhance product quality by leveraging advanced data analytics to anticipate equipment failures and identify optimization opportunities. Rising advancements in artificial intelligence and machine learning technologies, facilitate predictive analytics and prescriptive insights to optimize production processes and drive operational efficiencies.
Increasing adoption of Industry 4.0 technologies is expected to create new avenues in the enterprise manufacturing intelligence market. Companies are leveraging IoT sensors, AI algorithms, and cloud computing to optimize production processes and improve operational efficiency. For instance,
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In March 2021, General Electric Company (GE) Digital made a strategic acquisition, purchasing OpSense, a specialist in IoT-based environmental monitoring solutions. The acquisition aimed to fortify and enrich GE's Predix platform for industrial IoT applications.
Increasing adoption of cloud-based enterprise manufacturing intelligence solutions is anticipated to create opportunities in the market. This enables manufacturers to leverage scalable and flexible infrastructure for data storage, processing, and analysis, thereby enhancing accessibility and reducing infrastructure costs.
Scope of the Enterprise Manufacturing Intelligence Market Report
The market report includes an assessment of the market trends, segments, and regional markets. Overview and dynamics are included in the report.
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Attributes
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Details
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Report Title
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Enterprise Manufacturing Intelligence Market - Global Industry Analysis, Growth, Share, Size, Trends, and Forecast
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Base Year
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2023
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Historic Data
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2017 -2022
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Forecast Period
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2024–2032
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Segmentation
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Component (Software and Services), Deployment Mode (On-premises and Cloud-based), Application (Production Planning & Scheduling, Quality Management, Inventory Management, Supply Chain Management, Equipment Monitoring & Maintenance, and Others), End-user (Automotive, Aerospace & Defense, Electronics & Semiconductor, Food & Beverage, Pharmaceuticals, Chemicals, Energy & Utilities, and Others)
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Regional Scope
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Asia Pacific, North America, Latin America, Europe, and Middle East & Africa
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Report Coverage
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Company Share, Market Analysis and Size, Competitive Landscape, Growth Factors, Market Trends, and Revenue Forecast
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Key Players Covered in the Report
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ABB Ltd.; Dassault Systèmes SE; Emerson Electric Co.; General Electric Company (GE); Honeywell International Inc.; Oracle Corporation; Rockwell Automation, Inc.; SAP SE; Schneider Electric SE; and Siemens AG
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Regional Outlook
In terms of region, the global enterprise manufacturing intelligence market is classified as Asia Pacific, North America, Latin America, Europe, and Middle East & Africa. North America held a major market share in 2023, due to the strong presence of established manufacturing industries and technological advancements. Additionally, the high adoption rates of enterprise intelligence solutions, driven by the increasing focus on operational efficiency and regulatory compliance are boosting the market in the region.
The market in Asia Pacific is projected to grow at a significant pace during the forecast period, owing to the rapid industrialization, expanding manufacturing sector, and increasing investments in digital transformation initiatives. Furthermore, rising demand for cost-effective production processes, and government initiatives to promote Industry 4.0 technologies are expected to drive the market in the coming years.
Enterprise Manufacturing Intelligence Market Segment Insights
Component Segment Analysis
Based on component, the enterprise manufacturing intelligence market is divided into software and services. The software segment held a major share of the market in 2023, owing to the increasing demand for advanced analytics, real-time monitoring, and predictive insights provided by enterprise manufacturing intelligence software. Manufacturers are leveraging these solutions to optimize production processes, improve quality control, and enhance overall operational efficiency.
The services segment is expected to expand at a significant pace in the coming years, due to the rising need for consulting, integration, and support services to effectively implement and maintain enterprise manufacturing intelligence solutions. Businesses are increasingly seeking specialized expertise and assistance to ensure seamless integration with existing systems, customization to specific requirements, and ongoing support for optimization and upgrades, as they strive to maximize the value derived from these solutions.
Deployment Mode Segment Analysis
On the basis of deployment mode, the global market is segregated into on-premises and cloud-based. The on-premises segment held the largest share of the market in 2023 due to the established presence of traditional manufacturing facilities preferring localized data storage and control. Additionally, industries with stringent security and compliance requirements, such as aerospace & defense opt for on-premises solutions to maintain data sovereignty and confidentiality.
The cloud-based segment is anticipated to expand at a substantial CAGR during the projected period, due to the increasing adoption of cloud computing technologies and the benefits they offer, including scalability, flexibility, and cost-effectiveness. Cloud-based solutions enable real-time data access, seamless collaboration, and remote monitoring, catering to the evolving needs of modern manufacturing operations.
Rising trend of digital transformation and Industry 4.0 initiatives is driving the migration toward cloud-based deployment models to leverage advanced analytics and AI capabilities for enhanced decision-making and productivity gains.
Application Segment Analysis
Based on application, the enterprise manufacturing intelligence market is segmented into production planning & scheduling, quality management, inventory management, supply chain management, equipment monitoring & maintenance, and others. The production planning & scheduling segment led the market in terms of revenue in 2023, owing to its critical role in optimizing production processes, minimizing lead times, and ensuring efficient resource utilization. Manufacturers prioritize this application to enhance operational efficiency, meet customer demands, and reduce production costs.
The quality management segment is projected to register a robust growth rate during the assessment years, driven by the increasing focus on product quality, regulatory compliance, and customer satisfaction. Manufacturers are investing in enterprise manufacturing intelligence solutions to implement advanced quality management systems and conduct real-time monitoring and analysis. They are proactively identifying and addressing quality issues to enhance overall product quality and brand reputation, as they strive to maintain high standards of quality control and adhere to stringent regulatory requirements.
End-user Segment Analysis
On the basis of end-user, the market is divided into automotive, aerospace & defense, electronics & semiconductor, food & beverage, pharmaceuticals, chemicals, energy & utilities, and others. The automotive segment generated a major revenue share of the market in 2023, attributed to the increasing adoption of enterprise manufacturing intelligence solutions to optimize production processes, improve supply chain efficiency, and enhance product quality in the automotive manufacturing sector. Additionally, the growing demand for connected and autonomous vehicles is driving the need for advanced data analytics and real-time monitoring capabilities, further fueling the market. For instance,
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In July 2022, ABB announced its acquisition of ASTI Mobile Robotics Group, aiming to propel the next generation of flexible automation with autonomous mobile robots (AMRs). ASTI is a global leader in the rapidly growing AMR market, boasting a diverse portfolio of vehicles and software. This acquisition enhances ABB's robotics and machine automation solutions, augmenting its automation portfolio and enabling expansion into new industry segments.
The pharmaceuticals segment is projected to register a robust growth rate during the assessment years, driven by the rising demand for precision and compliance in pharmaceutical manufacturing processes. Manufacturers are increasingly turning to enterprise manufacturing intelligence solutions to ensure product quality, safety, and regulatory compliance, with stringent regulatory requirements and the need for quality assurance and traceability in pharmaceutical production. Additionally, growing emphasis on personalized medicine and biopharmaceuticals is expected to propel the segment in the coming years.
Segments
The enterprise manufacturing intelligence market has been segmented based on
Component
Deployment Mode
Application
- Production Planning & Scheduling
- Quality Management
- Inventory Management
- Supply Chain Management
- Equipment Monitoring & Maintenance
- Others
End-user
- Automotive
- Aerospace & Defense
- Electronics & Semiconductor
- Food & Beverage
- Pharmaceuticals
- Chemicals
- Energy & Utilities
- Others
Region
- Asia Pacific
- North America
- Latin America
- Europe
- Middle East & Africa
Key Players
Competitive Landscape
Key players competing in the global enterprise manufacturing intelligence market are ABB Ltd.; Dassault Systèmes SE; Emerson Electric Co.; General Electric Company (GE); Honeywell International Inc.; Oracle Corporation; Rockwell Automation, Inc.; SAP SE; Schneider Electric SE; and Siemens AG.
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On April 2, 2024, GE Aerospace became a standalone public entity, marking a significant development in aviation technology post the GE Vernova spin-off. GE Aerospace and GE Vernova commenced trading on the NYSE under the symbols GE and GEV, respectively. This strategic shift underscores GE's evolution into three distinct industry pioneers, with GE Aerospace at the forefront of aviation innovation, reflecting advancements in the enterprise manufacturing intelligence market.
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In September 2023, SAP acquired LeanIX, a leader in enterprise architecture management (EAM). LeanIX's software-as-a-service solutions enable organizations to visualize, assess, and manage IT landscape modernization. With this acquisition, SAP aims to enhance its transformation suite, providing customers with AI-enabled process optimization capabilities.
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