Manufacturers are embracing AI to deliver a new level of automation, optimization, and innovation. To unlock the full potential of AI on the shop floor, organizations are testing and investigating technologies and paradigms that empower them to leverage their data more effectively.
Microsoft, in partnership with IoT Analytics market research firm, conducted a global survey of manufacturers to gain insight into how they are seizing the AI opportunity while navigating key industry challenges. We asked manufacturers about their current priorities and future visions, their adoption of modern technologies and paradigms, and the benefits they expect from those technologies
In this report, we share the key findings from the survey, to show how manufacturing enterprises are preparing their shopfloors for AI to make them secure, scalable, and automated and how they are adopting advanced technologies such as centralized device management, software containerization at the edge, and unified industrial data operations to accelerate that process.
Six findings from manufacturers preparing their shop floor for AI
1. Scale matters the most in the era of AI
Scalability was the main concern for 72% of survey respondents, who highlighted this paradigm as crucial for their factory’s future. Scalability came first, followed by automation and serviceability. These paradigms ensure that factories can efficiently expand with demand, optimize with minimal manual decision making, and maintain high uptime through easy troubleshooting and maintenance.
What does scale look like for industrial environments?
Manufacturers face the challenges of keeping up with the changing demands of the market, the regulations, and the competition. They also recognize the potential of AI to transform their operations, optimize their processes, and enhance their products. But they don’t have the luxury of spending months or years on deploying and scaling solutions across their plants. Manufacturers need a faster way to move, a smarter way to manage, and a more flexible way to adapt. That’s why we have introduced a new approach—the adaptive cloud approach.
2. Cybersecurity and data management are top of mind right now
Security risks and data handling difficulties pose serious problems, with 58% of respondents seeing cybersecurity as a severe issue and 49% seeing data management as a severe issue. These concerns are motivating customers to improve network security and ensure data is reliable and accessible for decision-making.
What does security look like for industrial environments?
Security and data protection are critical for the manufacturing sector, as the sector faces increasing regulatory standards and cyber threats. Manufacturers need to secure existing devices, and plan during device refresh to choose devices that meet industry security standards, will enable them to more easily comply with regulatory standards, and provide security to defend from the latest security threats.
3. Device management is critical for security and data handling
Device management’s value is evolving beyond updates and device health monitoring to also address security risks and data flow management. The survey data supported this trend, with 68% of respondents noting that the security monitoring aspect of device management was very or extremely important to their organization and 59% of respondents highlighting data management as the second most important aspect of device management.
Why is centralized device management important?
Centralized device management is vital for ensuring the performance and security of operations in a factory setting. It helps to keep devices secure and functioning optimally, which contributes to the overall efficiency and productivity of a manufacturing environment. Effective management also enables better oversight and control over the factory processes, improving operational reliability and supporting scalability and adaptability in a dynamic industrial landscape.
4. Containerized workloads are coming to the shop floor
The adoption of containerized software on the shop floor is rising, with 85% of survey respondents already utilizing this technology. This shift towards containerization at the edge signifies a move to improve operational efficiency, system stability, and security. 55% of respondents indicated that containerized software could significantly or extremely mitigate reliability and uptime challenges, while 53% indicated it could do the same for cybersecurity challenges.
What is containerized software?
Software containerization enables consistent and repeatable development and deployment of solutions across different environments, in the cloud and in factory. Containerization of OT software is essential for the AI-powered factory of the future, as it enables seamless technology deployment in scalable, serviceable, and automated factories. Kubernetes automates the scaling and management of containerized applications, saving time and resources for manufacturers.
5. Industrial data operations optimize OT data management
Companies want to combine information technology (IT) and operational technology (OT) systems for context driven decision making. 52% of respondents indicated that having a combined IT and OT data platform was very or extremely important for their company. Industrial data operations enhance the integration of IT and OT data by improving data flow, quality and value; therefore, 87% of companies have already adopted industrial data operations technology in some form or are planning to do so.
What are industrial data operations?
Industrial data operations delivers data in a reliable, real-time manner for optimizing factories and plants. Industrial data operations manages and unifies data from various sources, facilitates seamless integration of information, and ensures data is accessible and usable for decision-making purposes. Industrial data operations helps break down data silos and improve predictive insights through an exchange and integration between shop floor and cloud environments.
6. Respondents are investing in underlying data architecture for AI
According to the study, manufacturers plan to invest in AI-powered factories of the future within the next two years. On average, respondents expected their organizations to increase their investments in software for orchestrating edge AI by 11%. This investment shows that they recognize the need to overcome technical and skill gaps to fully exploit AI’s capabilities in future manufacturing processes.
How to invest in underlying architecture for AI?
Microsoft recommends adopting advanced technology frameworks such as centralized device management, software containerization at the edge, and unified industrial data operations to accelerate industrial transformation and prepare for AI. Azure’s adaptive cloud approach embraces all three advanced technology frameworks.
Accelerate industrial transformation in manufacturing
A comprehensive survey of manufacturers’ priorities, challenges, and plans for adopting new technologies, such as these, in their factories to prepare for AI. The report shows that manufacturers are looking for solutions that can help them secure, scale, and automate. Microsoft Azure is responding to these needs with its adaptive cloud approach, which offers a flexible and scalable platform for managing devices, applications, and integrated data across the edge and the cloud.
Source: microsoft.com
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