Ahead of the fair, we also published a new report in collaboration with MIT Technology Review Insights uncovering the current state and ambitions around AI in the manufacturing industry. The report clearly indicates that manufacturers are excited about the potential of AI and plan to make significant investments over the next two to three years to deploy AI at scale to unlock innovation and enhance efficiency.

Microsoft Cloud for Manufacturing

Design, build, and operate with AI

Explore capabilities

Transforming the manufacturing value chain with AI

The Microsoft experience focused on how AI transforms the manufacturing value chain: starting with accelerating product development cycles, improving efficiency in the factory, making operations more sustainable, and finally empowering every employee across business functions with the latest AI tools. These four opportunities manifested as the four distinct neighborhoods in the booth, with demos and customer stories populating each one.

1. Unlock innovation in design and engineering

AI has the potential to unlock a tremendous amount of innovation in design and engineering by allowing manufacturers to simulate and generate new options faster. It can help accelerate development cycles for new products and services as shown by our customers Kuka & Schneider Electric, how manufacturers can accelerate the programming of industrial robots and programmable logic controllers (PLCs) with Microsoft Azure OpenAI Service, significantly speeding up development times. Siemens, along with customer Harting, showcased how generative AI can be used to speed up the design process of new industrial connectors and revolutionize mass-customization. Additionally, our partners Threedy, PTC, Hexagon, Capgemini, and Ansys showcased how applying technologies from digital twins to mixed reality to the Internet of Things (IoT) and cloud computing accelerates product development cycles.

2. Enable intelligent factories

Making factories smarter is top of mind for manufacturers. In this area of the booth, we showed customers how they can improve quality, resource utilization and accelerate issue resolution in the factory with industrial IoT, data, and AI. Along with our partners Accenture, Avanade, Sight Machine, Rockwell, and AVEVA, we showcased the manufacturing data solutions in Fabric (preview) and the Copilot template for factory operations on Azure AI. These solutions help manufacturers unify their information technology (IT) and operational technology (OT) data estates in an industry standard data model on Fabric. The Copilot template then uses this unified data to answer questions asked in natural language to help resolve issues on the factory floor. In addition, we showcased solutions from partners such as Tulip, TCS, SymphonyAI, SAP with Syntax, Cognite, Weavix, and Unmanned Life and from customers including Andritz, Chevron, Electrolux, and Ecopetrol that utilize Microsoft Azure IoT Operations, Azure private multi-access edge compute (MEC), Azure AI, Fabric, and more to enable intelligent factories.

3. Create resilient and sustainable operations

Manufacturing companies are looking to make their supply chain and service operations more resilient and sustainable. In this neighborhood we showed how they can achieve their goals using the power of cloud, AI, and mixed reality. In collaboration with Volvo Penta, we showed how using Microsoft Copilot in Dynamics 365 Field Service and Guides improves technician training, service manager workflows, and eventually, delivers better customer outcomes for their marine engines. With Caterpillar, we showcased how their Service Information System built on Azure provides detailed service information for CAT products from 1977 up to today. We also showcased Microsoft Sustainability Manager, which helps organizations to record, report, and reduce their environmental impacts through the power of data and AI. Our partners Blue Yonder, O9, and Tools Group demonstrated the power of cloud and AI to make supply chains more resilient.

4. Enhance employee productivity with AI

AI has the potential to unlock productivity and innovation for employees in all areas of the business. In this area of the booth, we showcased how Microsoft Copilot in products such as Microsoft Teams, Microsoft Security, Microsoft Power Platform, Fabric, Microsoft Dynamics 365, Windows, and Bing on Surface devices can empower employees across business functions in the manufacturing enterprise to achieve more. We showcased how Microsoft Copilot for Security and Microsoft Defender for IoT empower security teams to protect their OT environments, bringing collaboration to the forefront by reducing knowledge barriers for securing such environments. In the Fabric demo, we showed how manufacturing customers can use the suite of analytics workloads in Fabric, Copilot in Fabric, and direct integration with generative AI models to transform their factory operations.

The BMW Group showcase was the connecting thread between each of the booth neighborhoods. Built in collaboration with Hexagon, NVIDIA, PTC, and Rockwell Automation, business leaders and dignitaries could experience how technology enables cutting-edge transformation through AI-assisted design, connected data, and agile production for organizations like BMW Group. Featured in the exclusive Hannover Messe press tour highlight, which hosted more than 40 international journalists, this demo garnered significant attention for depicting how the integration of technology is changing manufacturing as we know it.

Thought leadership and continued innovation

A space for thought leadership, the Microsoft theater was very busy this year, bringing together C-level leaders, innovators, and business leaders eager to learn about how technology is changing the sector, what their peers are doing, and the importance of diversity within manufacturing. This space connected customers to the experts: creating a unique forum of innovation where solutions to complex industrial problems were revealed, and where ideas were brought to life.

Covering topics from the return on investment (ROI) of 5G factories, to delivering practical insights for how exactly to build your own copilots, the theater sessions delivered valuable insights on the most pressing questions the industry faces today. Here are a few highlights of the theater sessions:

• Celebrating women in manufacturing brought together influential voices of women in manufacturing to explore their career journeys, achievements, challenges, and best leadership practices to inspire the next generation of female talent.
• Industrial transformation with AI: A discussion with Kraft and Schneider Electric shared how cloud, IoT, and mixed reality technologies together with AI are reshaping entire value chains.
• Microsoft partners, including IBM, PwC, Fractal, DXC, Honeywell, and Rescale spoke about how their solutions built with Microsoft technologies can help transform all aspects of manufacturing from design and engineering to the factory floor.
• Microsoft Intelligent Manufacturing Award showcase, in partnership with Roland Berger, celebrated the winners of the fifth annual Microsoft Intelligent Manufacturing Awards (MIMA), a prestigious award recognizing innovation in digitalizing the manufacturing industry in Europe, Middle East, and Africa (EMEA). The award honors the most promising and innovative digital best practices from the industrial and operations sectors: production, purchasing, supply chain, engineering, and after sales. This year’s MIMA winners were Mercedes Benz, Northvolt, Malvern Paralytical, Wilo, Andritz, and Danfoss.

Learn more about solutions from Microsoft

Finally, we would like to thank our customers and partners who joined us at the booth as exhibitors, along with the thousands of attendees who visited the booth to engage with us and looking forward to Hannover Messe 2025. To learn more about the latest solutions for manufacturing, please visit Microsoft Cloud for Manufacturing.

The post Microsoft experience at Hannover Messe 2024: Accelerating industrial transformation with AI appeared first on The Microsoft Cloud Blog.

Against this background, Microsoft commissioned a research report in collaboration with MIT Technology Review Insights to uncover the state of AI adoption, expectations, and challenges to scaling AI in the manufacturing industry. This report, titled “Taking AI to the Next Level in Manufacturing” is a culmination of a global survey of 300 senior manufacturing executives and expert interviews aimed at guiding the industry to develop robust strategies to scale AI across the manufacturing value chain. 

Below are some of the key findings from the report around AI ambitions, key challenges, and strategies to successfully implement AI. For complete insights, we invite you to download the full report. 

AI ambitions: Investment, top use cases, and expectations

Investment: Major players leading the way

The transformative power of AI in the manufacturing sector is not just a future prospect, it’s an unfolding reality. 77% of surveyed firms with more than USD10 billion in annual revenue are already deploying AI use cases. Engineering and design executives are particularly proactive with 58% anticipating an increase in AI spending by more than 10% within the next two years. This surge in investment is mirrored in factory operations, where 43% of leaders anticipate a similar increase, a testament to the industry’s interest in AI’s potential to drive innovation and efficiency. 

Top use cases: AI application from design to factory floor

Use cases are where “the rubber meets the road” for AI adoption. Pavandeep Kalra, Chief Technology Officer of AI for Microsoft Cloud for Industry, emphasizes that, “The barriers to AI use-case development are falling” as generative AI foundational models are reducing the requirement for industry-specific customizations. Among the survey sample, the AI use cases most likely to have progressed through production involve product design, conversational AI (chatbots), and content creation. On the factory floor, the focus is on process optimization, quality control, and asset maintenance use cases. 

Expectations: Unlocking speed, efficiency, and innovation 

The potential for AI to deliver impact in the realm of engineering and design is becoming increasingly apparent with more than 40% of executives aiming to use AI to enhance speed and efficiency and minimize product failures. The experience of Gunaranjan Chaudhry, Director of Data Science at Symphony Industrial AI, exemplifies the transformative effect AI can have on the design process. He notes,

“AI speeds up the process by homing in on the specific parameters that you need to focus on. We’ve had design cycles being cut from 12 months to less than six months.”

Gunaranjan Chaudhry, Director of Data Science at Symphony Industrial AI

In factory operations, AI is expected to unlock innovation in production and assembly process, improve safety, and help reduce carbon footprint. 

Taking AI to the Next Level in Manufacturing

Gain insights on AI adoption in the manufacturing industry

Download the report

Key challenges to scaling AI in the manufacturing sector

Talent, skills, and data: The triad of AI scaling challenges 

One of the main challenges in scaling AI use cases is the deficit of talent, skills, and data. Manufacturers cite this as their toughest challenge in both design and engineering and factory operations. Inadequate data quality and governance also hamper use-case development in both areas. Additionally, insufficient access to cloud-based compute power is another constraint in design and engineering. AI model governance is expected to be one of the big challenges on the factory floor, with 61% of manufacturers that have begun deploying AI use cases citing governance as a major data challenge. This underscores the difficulties in maintaining high standards of data quality, consistency, and compliance within the complex and variable manufacturing settings.

Critical need for data unification and contextualization 

Scaling AI use cases can be hindered without solid data foundations, as respondents have identified inadequate data quality (57%), weak data integration (54%), and insufficient governance (47%) as significant challenges. Regrettably, only approximately one in five manufacturers have production assets with data prepared for utilization in current AI models. This issue is further exacerbated as manufacturers transition use cases into production. Notably, larger manufacturers tend to encounter a more pronounced challenge with unsuitable data. 

Reducing fragmentation for AI to flourish 

To effectively scale AI, data fragmentation must be minimized. Most manufacturers will need to update their data architecture, infrastructure, and processes to gain full benefits from AI, as well as other technological and business objectives. Prioritizing a modernization strategy that enhances interoperability between engineering and design and factory data systems, as well as between operational technology (OT) and information technology (IT), is crucial. 

Strategies to successfully scale AI 

As manufacturers worldwide progress in their digital transformation journeys, data serves as the crucial enabler. To harness the full potential of AI, it is imperative to establish and maintain data quality, integration, and governance throughout the entire value chain, extending from design and production to distribution. Bridging the divide between OT and IT systems, which frequently function in isolation and adhere to disparate protocol and stands, is essential. By cultivating a more cohesive and consistent data landscape, manufacturers can expedite their AI integration and optimize their use case scalability. As manufacturers continue to tap into the transformative power of AI, here are some essential considerations.

Start with the business case

Companies should begin by identifying the business problem or challenge that technology, including AI, could address. Only then should technology solutions be considered. “Asking ‘what can we do with AI?’ can generate lots of great ideas,” says Philippe Rambach, Chief AI Officer of Schneider Electric, “but most will have limited impact if they don’t start with the actual business need.”  

Embrace structural flexibility

In this evolving landscape, use-case development extends beyond the realm of AI experts. It has become a multidisciplinary endeavor as internal expertise is harnessed alongside data science and engineering teams, in collaboration with business product owners and IT professionals. Such a unified approach increases the chances of successful AI use-case development and deployment. 

Prepare the data foundation

AI thrives in a mature data environment. To achieve this, manufacturers can strategically adopt modular updates and employ data virtualization techniques to incrementally enhance their systems and align their data architecture with AI capabilities without immediate, extensive change. It’s important to assess your organization’s data collection, storage, and processing capabilities, addressing any identified weaknesses before deploying AI use cases. This may involve consolidating data repositories where feasible. While AI models necessitate high-quality data, perfection is not a prerequisite for moving use cases into production. 

Leverage AI for skill development

It’s natural for manufacturers to be concerned about the lack of AI skills and talent, but they should recognize that AI can aid in cultivating these skills within their workforce. Generative AI, for instance, simplifies the process for engineers and non-IT staff to engage with models. AI can also enhance the problem-solving abilities of production personnel. 

Take AI to the next level 

AI holds the potential to fundamentally transform the manufacturing sector, bringing about unparalleled opportunities for innovation, productivity, and environmental sustainability. To gain a deeper understanding of these insights and explore practical strategies for scaling AI use cases, download the full “MIT Technology Review Insights: Taking AI to the Next Level in Manufacturing” report today. 

To explore Microsoft’s comprehensive suite of products and services that empower manufacturers to innovate, optimize, and scale AI use cases across the manufacturing value chain, visit the Microsoft Cloud for Manufacturing webpage. Join us in shaping the future of manufacturing.  

The post Industrial transformation: Scaling AI across the manufacturing value chain appeared first on The Microsoft Cloud Blog.

There’s much to explore on this topic—that is why we developed A New Era of Industrial Transformation. This series, featuring analysts from Forrester, digs into the changing face of manufacturing, examining the related trends, use cases, and technology leading the way.  

A New Era of Industrial Transformation

Discover how technology is helping overcome modern manufacturing challenges

Watch the series

Episode 1: Converging technology and its combinatorial effect

In the first conversation, Dominik Wee, Corporate Vice President of Manufacturing and Mobility at Microsoft, sits down with guest Paul Miller, Vice President Principal Analyst at Forrester, to discuss how manufacturing organizations are using technology to improve their operations. Acknowledging the challenges that manufacturers face today, Paul reviews some findings of our commissioned research conducted by Forrester Consulting, Accelerate Future Manufacturing Transformation. Focused on the industrial metaverse, the research examines why organizations are turning to this emerging category to integrate their physical and digital environments to find balance.  

While new, this confluence of technology is already providing value. Forrester sees organizations prioritizing technology investments in three key areas:

1. Technology that offers greater connectivity. Industrial environments have hundreds of moving parts, making connectivity essential. The internet of things (IoT) and wireless (5G) networks enable new organizational visibility that enable the data foundation necessary to industrial metaverse capabilities.  

2. Technology that offers greater simulation, modeling, and engagement. AI is influencing other technologies. This is especially true for extended reality solutions (for example, augmented, mixed, and virtual reality). From using digital twins to monitoring asset health to simulation optimizing industrial processes to mixed reality accelerating worker upskilling—manufacturing leaders are seeing real value.  

3. Technology that offers greater automation and computing power. With their industrial data gathered, manufacturers are turning to AI for a deeper analysis to do predictive maintenance and yield optimization or streamline production processes.  

Dominik uses Bridgestone, Bosch, and ALTANA stories to articulate the ways manufacturing organizations are using these technologies today and discuss how others can start. Catch up on episode one. 

Episode 2: Reengineering the product development lifecycle   

Episode two looks at product innovation. Here Simon Floyd, General Manager for Manufacturing and Mobility at Microsoft, chats with guest George Lawrie, Vice President and Principal Analyst at Forrester, on what is happening inside the product engineering and design departments. Generative AI is at the heart of their transformation, helping these departments rethink the product lifecycle in three major ways: 

1. AI can enhance collaboration and productivity. Transform engineering and product design by automating tasks such as code generation, enhancing decision-making through knowledge discovery at scale, and advanced simulations. These capabilities streamline the development process, fostering innovation and ensuring products meet market demands more efficiently. 

2. AI can help address growing product complexities. Empower enterprises to manage the increasing complexity and diversity in product development by personalizing designs based on consumer data, ensuring regulatory compliance, and integrating sustainability into the design process. These capabilities facilitate innovation that better meet customer and market needs.  

3. AI can enable new product concepts. Bring concepts to life faster through generative design, simulations using cloud-based high-performance computing and advanced technologies such as digital twins and mixed reality. AI will not only streamline product exploration but also ensure that final products are more aligned with user preferences and trends. 

Simon uses Eagle Industries and Siemens stories to articulate the ways manufacturers are using generative AI in product lifecycle to reimagine products, while discussing how organizations can get started with AI in their engineering processes. Watch episode two. 

Episode 3: Transforming factories from the inside 

Paul Miller returns as a guest speaker. In episode three, he joins John Reed, Solutions Leader for Manufacturing and Mobility at Microsoft, exploring technologies’ impact on factories and production, globally. Their conversation highlights the four big trends that Forrester sees shaping the industry, as outlined in their Future of Manufacturing report: 

1. Integrating digital technologies with physical products. Most traditional industrial players are rushing to acquire and embed digital capabilities. But the physical products, and the hard-won industrial skills that create them, aren’t going away. Rather, digital technologies help augment these products and enable manufacturers to design, build, sell, use, reuse, support, and value it in new ways.  

2. Adapting to a changing world with local, near, and far capacity. Rumors of globalization’s demise was premature, but economic pressures, aging workforces, and technological advances are altering the balance. It’s no longer wise to assume everything will be made in China—nor anywhere else. Smart leaders are embracing more flexible and resilient supply networks. 

3. Electrifying, decarbonizing, and manufacturing sustainably. Electrification of industrial processes has been underway for years, and decarbonization projects are showing promise. However, most organizations are just getting started on sustainably. This will require them to reconsider the energy and raw materials connected to their finished goods.  

4. Getting the best from hardware, software, and people. Few industrial workflows will suit entirely automated, lights-out operation any time soon. Far from replacing human workers, well-deployed hardware and software automation augment them, extend their reach, removing administrative burdens that keep them from their work. 

John examines Intertape Polymer Group’s (IPG) story to discuss the role generative AI could have inside a factory. Working with Sight Machine, IPG is developing a factory copilot using Microsoft Azure OpenAI Service. While is it early, IPG has noticed a 50% decrease in manufacturing data platform onboarding time, a 25% increase in average weekly platform usage, and improved customer experience scores due to automatic report generation. John and Paul conclude the conversation with areas of AI-enabled quick wins, and where to start with embedded AI copilots. Don’t miss episode three.  

Advancing your industrial transformation strategy 

We are at a unique moment of change and convergence with data and AI becoming more accessible and fundamentally changing our relationship with products, processes, and places. This integration of digital and physical technologies presents a big opportunity to reinvent the entire value chain: 

• The vast amount of data and digital feedback loops from both consumers and connected products allows us to use AI-driven product design to deliver on individualized customer needs, enhancing customer satisfaction and brand loyalty. 

• In the factory, continuous monitoring of assets through sensors and data analysis helps workers anticipate maintenance needs to reduce unplanned downtime, enhancing asset reliability. 

• AI-optimized supply chains monitor pricing changes from suppliers, dynamically dispatch materials to meet production needs, and prioritize customer shipments based on fulfillment penalties. 

Next steps

Watch the New Era of Industrial Transformation series to learn more about how AI is driving transformation across manufacturing organizations and visit Microsoft Cloud for Manufacturing for more resources and customer stories to inform your transformation.   

Forrester: The Future of Manufacturing: Disruptive Innovations In Manufacturing Will Reshape Entire Industries (2022). 

The post A new era of industrial transformation: 3 conversations to challenge your perspective appeared first on The Microsoft Cloud Blog.

Against this backdrop, Microsoft decided to spotlight the manufacturing industry for our August 2022 IoT Signals report. IoT Signals is a series of impactful thought leadership content curated by Microsoft to inform the community about the latest developments and technology trends in the IoT industry. The first report, published in 2019, provided a broad view of IoT across a variety of industries—from manufacturing and energy to healthcare and retail—based on comprehensive, survey-based research.

For this edition of the report IoT Signals: Manufacturing Spotlight Microsoft, Intel, and IoT Analytics surveyed 500 decision makers working on digital transformation initiatives in discrete, hybrid, or process manufacturing across North America, Europe, and Asia Pacific. We conducted more in-depth interviews with some participants to gain a deeper understanding of their transformation strategies, execution plans, and challenges.

Six key findings about digital transformation and IoT in manufacturing

This new IoT manufacturing report reveals insights from real-world manufacturers that have started their digital transformation journey. It also uncovers fresh learnings about the state of industrial IoT devices and technology in manufacturing, specifically in the areas of manufacturing operations and smart products.

During our research, we discovered six key digital transformation and IoT manufacturing trends:

1. Most manufacturers are advancing their efforts to build smart factories. Three out of four survey respondents (72 percent) said they’re implementing their smart factory strategy.
2. Operational improvement is still a top goal for manufacturers. Four out of five survey respondents said they consider overall equipment effectiveness (OEE) to be the most important key performance indicator to measure the success of their smart factory strategy.
3. Organizations are shifting investments to industrial automation-based process control. To date, most manufacturers have focused on quality control and condition-based maintenance for smart factory projects. However, the need for greater agility is leading these organizations to shift their investments over the next three years to industrial automation-based process control—the use of automated control systems, such as IoT and AI, to automate manufacturing processes.
4. Manufacturers face new challenges with scaling smart factory initiatives. Half of the respondents said they face challenges in developing new software applications, and the majority (eight out of 10) said they’re dealing with skills gaps, particularly in data science, AI, and cybersecurity.
5. IT-OT convergence is happening in the manufacturing industry. With 76 percent of manufacturing assets now connected, many manufacturers are moving workloads and applications from on-premises infrastructure to public and private cloud platforms.
6. Manufacturers plan to increase investments in smart connected IoT products. Manufacturing organizations are not only optimizing their own operations with smart connected IoT products—they’re also creating new revenue streams by selling these products to customers. Manufacturers that already sell connected IoT products expect to increase investments from 33 percent today to 47 percent by 2025, with a strong focus on value-added services, such as predictive maintenance and remote support.

Read the IoT Signals: Manufacturing Spotlight to learn more about what’s driving these six key trends and holistic understanding of six key components of digital transformation in manufacturing.

Accelerating digital transformation and embracing IoT with Microsoft Cloud for Manufacturing

All six of the key findings from this manufacturing IoT report share a common theme: Manufacturers across the globe are advancing their digital transformation efforts. These organizations are tapping into innovative solutions to reimagine manufacturing and build a more resilient and sustainable future.

By adopting transformative technologies like IoT industrial devices, AI, and digital twins, your manufacturing organization can:

• Transform your workforce. Eight out of 10 manufacturers report having at least one important skill gap, particularly when it comes to advanced data analysis and IT cybersecurity. In this environment, manufacturers are looking for tools that will help them close the gap and boost employee productivity. Today’s manufacturers can transform their workforce by empowering their frontline workers with digital tools and modern devices that enable real-time collaboration, enhance training, and improve worker health and safety.

• Build more agile factories. The ability to adapt quickly to rapid change is a defining factor between manufacturers that simply survive and those that thrive. That’s why manufacturers across the globe are tapping into advanced technologies to build more agile, smarter factories.

• Create more resilient supply chains. According to the report, 74 percent of manufacturers ranked supply chain resilience as a top priority. This is no surprise considering that, now more than ever, manufacturers are under pressure to prevent and minimize supply chain disruptions. Microsoft Cloud for Manufacturing is already helping manufacturers improve end-to-end supply chain visibility and boost supply chain resilience.

• Engage customers in new ways. If you want to gain an edge in the manufacturing industry, customer engagement is critical. As manufacturers search for innovative ways to engage customers, many are selling smart connected IoT products. Our research shows that 33 percent of manufacturers’ product revenue comes from smart products today.

• Drive innovation and deliver new services. Manufacturers are investing in advanced technologies to create a more resilient future. According to our research, 28 percent of manufacturers have rolled out digital twins, and four percent of them have fully deployed them in their factories. Another 45 percent of manufacturers are in development and proof of concept (POC) stage for digital twins, and 39 percent are in the same stage for augmented reality (AR).

• Decrease your environmental impact. Most manufacturing board members (59 percent) believe that decreasing their carbon footprint is an important area of focus. Manufacturers are uniquely positioned to drive sustainability while saving costs and improving safety using cloud-based automation, machine learning, and AI.

• Improve security. Security is a top priority for manufacturing organizations, and 62 percent of manufacturers have strict data privacy policies. Over the next three years, manufacturers plan to decrease the mean time to detect cybersecurity incidents by 30 percent.

Build a resilient future with IoT manufacturing

Manufacturing organizations are drawing from the lessons learned during COVID-19 to develop resilience and build a better future. Digital transformation continues to be top of mind for these manufacturers as they work to increase agility, improve customer engagement, and drive growth. To gain insights from the digital transformation journeys of real-world manufacturers, read the IoT Signals: Manufacturing Spotlight report. 

The post Top 6 findings from IoT Signals: Manufacturing Spotlight appeared first on The Microsoft Cloud Blog.