市场调查报告书
商品编码
1554255
製造分析市场规模、份额和成长分析:按类型、应用程式、部署模型、产业和地区划分 - 产业预测,2024-2031 年Manufacturing Analytics Market Size, Share, Growth Analysis, By Type, By Application, By Development Model, By Industry Vertical, By Region - Industry Forecast 2024-2031 |
2022年全球製造分析市场规模将达到128亿美元,预测期内(2024-2031年)复合年增长率为20.8%,从2023年的154.6亿美元增长到2031年的580亿美元。美国3000万美元。
对于希望透过资料主导的洞察来增强业务的现代製造商来说,製造分析市场发挥着至关重要的作用。该市场主要是由製造业中自动化和数数位化的日益一体化所推动的,物联网设备、感测器和互连机器会产生大量资料。然而,将分析工具整合到现有系统并确保资料准确性已成为需要解决的重大挑战。儘管存在这些障碍,製造分析市场仍具有相当大的成长和发展潜力。人工智慧和机器学习等技术进步提供了从海量资料集获取可行见解的创新方法。此外,製造业专注于工业4.0和数位转型,非常适合部署分析解决方案,反映出该产业注重利用资料分析实现营运绩效的环境已经到位。製造分析透过即时监控、预测性维护和供应链优化等应用提供实际好处。这些工具使製造商能够检测效率低下的情况、预测需求、最佳化库存并改善生产流程。透过利用分析的力量,製造商可以提高生产力、提高效率并保持竞争力。
Global Manufacturing Analytics Market size was valued at USD 12.80 Billion in 2022 and is poised to grow from USD 15.46 Billion in 2023 to USD 58.03 Billion by 2031, at a CAGR of 20.8% during the forecast period (2024-2031).
The manufacturing analytics market plays a pivotal role for contemporary manufacturers aiming to enhance their operations through data-driven insights. This market is largely propelled by the growing integration of automation and digitization in manufacturing, which generates extensive data from IoT devices, sensors, and interconnected machinery. However, integrating analytics tools with existing systems and ensuring the accuracy of data present significant challenges that need to be addressed. Despite these obstacles, the manufacturing analytics market holds considerable potential for growth and advancement. Advances in technologies such as artificial intelligence and machine learning are providing innovative ways to derive actionable insights from vast data sets. Additionally, the emphasis on Industry 4.0 and digital transformation in the manufacturing sector creates a conducive environment for adopting analytics solutions, reflecting the industry's focus on utilizing data analytics to achieve operational excellence. Manufacturing analytics offers practical benefits through applications like real-time monitoring, predictive maintenance, and supply chain optimization. These tools enable manufacturers to detect inefficiencies, predict demand, optimize inventory, and refine production processes. By harnessing the power of analytics, manufacturers can enhance productivity, boost efficiency, and maintain a competitive edge, all while promoting sustainability in a rapidly evolving industry.
Top-down and bottom-up approaches were used to estimate and validate the size of the Global Manufacturing Analytics market and to estimate the size of various other dependent submarkets. The research methodology used to estimate the market size includes the following details: The key players in the market were identified through secondary research, and their market shares in the respective regions were determined through primary and secondary research. This entire procedure includes the study of the annual and financial reports of the top market players and extensive interviews for key insights from industry leaders such as CEOs, VPs, directors, and marketing executives. All percentage shares split, and breakdowns were determined using secondary sources and verified through Primary sources. All possible parameters that affect the markets covered in this research study have been accounted for, viewed in extensive detail, verified through primary research, and analyzed to get the final quantitative and qualitative data.
Global Manufacturing Analytics Market Segmental Analysis
The global manufacturing analytics market is segmented based on Type, application, Deployment model, Industry Vertical and region. Based on type, the market is segmented into software and services. In terms of application, the market is segmented into predictive maintenance and asset management, inventory management, supply chain Planning and Procurement, energy management, emergency management, sales and customer management and others. Based on the development model, the market is segmented into on-premises, on-demand. In terms of industry vertical, the market is segmented into automotive and aerospace manufacturing, electronic equipment manufacturing, food and beverages manufacturing, chemicals and materials manufacturing, machinery and industrial equipment, pharma and life sciences, paper, pulp, plastic and rubber manufacturing, others. By region, the market is segmented into North America, Europe, Asia Pacific, Middle East and Africa, and Latin America.
Drivers of the Global Manufacturing Analytics Market
Predictive maintenance is increasingly becoming a key focus in the manufacturing sector due to its ability to proactively detect and address potential equipment failures. By utilizing manufacturing analytics, manufacturers can continuously monitor equipment health, anticipate maintenance needs, and plan maintenance activities in advance. This strategy helps reduce downtime, lower maintenance costs, and enhance overall equipment performance. In 2023, the growing emphasis on predictive maintenance to drive operational efficiency and cost savings is anticipated to significantly boost the demand for manufacturing analytics solutions.
Restraints in the Global Manufacturing Analytics Market
As manufacturing analytics involves handling large amounts of sensitive data, concerns about data security and privacy present a significant challenge in the market. Manufacturers must safeguard the confidentiality and integrity of their data to prevent unauthorized access and potential breaches. In 2023, ensuring robust data security measures and adhering to data protection regulations will remain crucial challenges that could impact the widespread adoption of manufacturing analytics solutions.
Market Trends of the Global Manufacturing Analytics Market
In 2023, the incorporation of artificial intelligence (AI) and machine learning (ML) technologies into manufacturing analytics is emerging as a major trend. These advanced algorithms have the capability to reveal hidden patterns and correlations within manufacturing data, facilitating predictive and prescriptive analytics. By harnessing the power of AI and ML, manufacturers can enhance their data-driven decision-making, streamline processes, and boost overall operational efficiency. The use of AI and ML in manufacturing analytics enables manufacturers to gain deeper insights from their data, driving improvements in various aspects of their operations. This integration supports more accurate predictions, better process optimization, and ultimately leads to greater operational effectiveness and efficiency.