6 findings from IoT Indicators report: Producers put together their store flooring for AI


Producers are embracing AI to ship a brand new degree of automation, optimization, and innovation. To unlock the total potential of AI on the store flooring, organizations are testing and investigating applied sciences and paradigms that empower them to leverage their knowledge extra successfully.

Microsoft, in partnership with IoT Analytics market analysis agency, performed a world survey of producers to realize perception into how they’re seizing the AI alternative whereas navigating key business challenges. We requested producers about their present priorities and future visions, their adoption of recent applied sciences and paradigms, and the advantages they anticipate from these applied sciences 

On this report, we share the important thing findings from the survey, to indicate how manufacturing enterprises are making ready their shopfloors for AI to make them safe, scalable, and automatic and the way they’re adopting superior applied sciences reminiscent of centralized gadget administration, software program containerization on the edge, and unified industrial knowledge operations to speed up that course of.

Speed up industrial transformation

How producers put together shopfloors for a future with AI

A businesswoman reviews a colleague's presentation on a digital tablet at her desk in an open office space.

Learn on to find the six key classes discovered from producers rethinking their operations for AI and the way Microsoft is supporting the manufacturing unit of the longer term with Microsoft Azure’s adaptive cloud method.

Six findings from producers making ready their store flooring for AI

1. Scale issues probably the most within the period of AI

Scalability was the principle concern for 72% of survey respondents, who highlighted this paradigm as essential for his or her manufacturing unit’s future. Scalability got here first, adopted by automation and serviceability. These paradigms make sure that factories can effectively develop with demand, optimize with minimal handbook determination making, and preserve excessive uptime via straightforward troubleshooting and upkeep. 

What does scale appear like for industrial environments? 

Producers face the challenges of maintaining with the altering calls for of the market, the laws, and the competitors. Additionally they acknowledge the potential of AI to remodel their operations, optimize their processes, and improve their merchandise. However they don’t have the luxurious of spending months or years on deploying and scaling options throughout their crops. Producers want a quicker solution to transfer, a wiser solution to handle, and a extra versatile solution to adapt. That’s why we have now launched a brand new method—the adaptive cloud method. 

To be taught extra, see how the adaptive cloud method is designed to assist producers unify their groups, websites, and techniques with cloud-native and AI applied sciences that work seamlessly throughout hybrid, multicloud, edge, distributed computing, and the Web of Issues (IoT). The adaptive cloud method empowers producers to ship worth quicker, handle gadgets extra effectively, and run functions extra securely to prepares them for the AI-powered manufacturing unit of the longer term.  

2. Cybersecurity and knowledge administration are high of thoughts proper now 

Safety dangers and knowledge dealing with difficulties pose severe issues, with 58% of respondents seeing cybersecurity as a extreme situation and 49% seeing knowledge administration as a extreme situation. These issues are motivating clients to enhance community safety and guarantee knowledge is dependable and accessible for decision-making. 

What does safety appear like for industrial environments? 

Safety and knowledge safety are important for the manufacturing sector, because the sector faces growing regulatory requirements and cyber threats. Producers must safe current gadgets, and plan throughout gadget refresh to decide on gadgets that meet business safety requirements, will allow them to extra simply adjust to regulatory requirements, and supply safety to defend from the most recent safety threats.  

To be taught extra, see Microsoft’s complete method to safety, from gadget to cloud, that helps clients meet their compliance wants and defend in opposition to assaults. For current gadgets, Microsoft supplies firmware and community scanning with Microsoft Defender for IoT, which permits clients to stock their gadgets and monitor for vulnerabilities and threats. For brand spanking new gadgets, clients can select from main business authentic tools producers (OEMs) gadgets labeled Secured-core, which meet the most recent safety necessities. Each current and new gadgets may be monitored and remediated utilizing Microsoft Defender and Microsoft Sentinel.

3. Machine administration is important for safety and knowledge dealing with 

Machine administration’s worth is evolving past updates and gadget well being monitoring to additionally handle safety dangers and knowledge circulate administration. The survey knowledge supported this development, with 68% of respondents noting that the safety monitoring side of gadget administration was very or extraordinarily vital to their group and 59% of respondents highlighting knowledge administration because the second most vital side of gadget administration. 

Why is centralized gadget administration vital? 

Centralized gadget administration is important for making certain the efficiency and safety of operations in a manufacturing unit setting. It helps to maintain gadgets safe and functioning optimally, which contributes to the general effectivity and productiveness of a producing setting. Efficient administration additionally permits higher oversight and management over the manufacturing unit processes, bettering operational reliability and supporting scalability and flexibility in a dynamic industrial panorama.

To be taught extra, see how Azure Arc delivered centralized administration for IT and OT environments. Producers can outline assets, reminiscent of hybrid, multi-cloud, edge, and IoT, to Azure Useful resource Supervisor so providers reminiscent of system well being monitoring, safety, and plenty of others may be simply utilized throughout a globally distributed digital property.

4. Containerized workloads are coming to the store flooring 

The adoption of containerized software program on the store flooring is rising, with 85% of survey respondents already using this know-how. This shift in the direction of containerization on the edge signifies a transfer to enhance operational effectivity, system stability, and safety. 55% of respondents indicated that containerized software program may considerably or extraordinarily mitigate reliability and uptime challenges, whereas 53% indicated it may do the identical for cybersecurity challenges.

What’s containerized software program? 

Software program containerization permits constant and repeatable growth and deployment of options throughout totally different environments, within the cloud and in manufacturing unit. Containerization of OT software program is crucial for the AI-powered manufacturing unit of the longer term, because it permits seamless know-how deployment in scalable, serviceable, and automatic factories. Kubernetes automates the scaling and administration of containerized functions, saving time and assets for producers.

To be taught extra, see how Azure Kubernetes Service helps to securely modernize and optimize Kubernetes environments with unified administration, governance, and monitoring. Azure Kubernetes Service (AKS), helps groups speed up app growth and deployment with best-in-class instruments and generative AI. With AKS, enabled by Arc, these advantages will also be prolonged to on-premises and edge-based functions 

5. Industrial knowledge operations optimize OT knowledge administration

Corporations need to mix info know-how (IT) and operational know-how (OT) techniques for context pushed determination making. 52% of respondents indicated that having a mixed IT and OT knowledge platform was very or extraordinarily vital for his or her firm. Industrial knowledge operations improve the mixing of IT and OT knowledge by bettering knowledge circulate, high quality and worth; due to this fact, 87% of firms have already adopted industrial knowledge operations know-how in some type or are planning to take action.

What are industrial knowledge operations? 

Industrial knowledge operations delivers knowledge in a dependable, real-time method for optimizing factories and crops. Industrial knowledge operations manages and unifies knowledge from varied sources, facilitates seamless integration of knowledge, and ensures knowledge is accessible and usable for decision-making functions. Industrial knowledge operations helps break down knowledge silos and enhance predictive insights via an change and integration between store flooring and cloud environments.

To be taught extra, see how Azure IoT Operations handles knowledge from tools and techniques in OT environments, making certain that knowledge is collected, pre-processed, and built-in into functions operating onsite. This service, introduced in public preview at Ignite 2023, embraces business requirements—reminiscent of, Open Platform Communications Unified Structure (OPC UA), Message Queuing Telemetry Transport (MQTT), OpenTelemetry (OTel)—and natively integrates into Microsoft Cloth. Microsoft Cloth, handles knowledge for cloud environments, centralizing knowledge on one open, organization-wide knowledge lake to remove sprawl and scale back duplication. It permits creating and managing AI fashions on a single basis, decreasing knowledge motion and time to worth.

6. Respondents are investing in underlying knowledge structure for AI 

In line with the examine, producers plan to put money into AI-powered factories of the longer term throughout the subsequent two years. On common, respondents anticipated their organizations to extend their investments in software program for orchestrating edge AI by 11%. This funding exhibits that they acknowledge the necessity to overcome technical and talent gaps to totally exploit AI’s capabilities in future manufacturing processes. 

Easy methods to put money into underlying structure for AI? 

Microsoft recommends adopting superior know-how frameworks reminiscent of centralized gadget administration, software program containerization on the edge, and unified industrial knowledge operations to speed up industrial transformation and put together for AI. Azure’s adaptive cloud method embraces all three superior know-how frameworks. 

Speed up industrial transformation in manufacturing

To be taught extra learn the total 2024 IoT Indicators report, a complete survey of producers’ priorities, challenges, and plans for adopting new applied sciences, reminiscent of these, of their factories to arrange for AI. The report exhibits that producers are in search of options that may assist them safe, scale, and automate. Microsoft Azure is responding to those wants with its adaptive cloud method, which affords a versatile and scalable platform for managing gadgets, functions, and built-in knowledge throughout the sting and the cloud.

To view a presentation of this survey by IoT Analytics’ CEO and Microsoft’s GM of Azure IoT and Edge, recorded at HMI 2024, click on right here.

To find extra insights and finest practices for accelerating industrial transformation, obtain the 2024 IoT Indicators report beneath.



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