Solutions for the manufacturing industry
Manufacturing sector, a hallmark of the modern industrialized world, encompasses all steps from procuring raw materials to transforming into final product. Starting from household manufacturing in the pre-industrial era, this sector has evolved through stages such as mechanized assembly lines and automation, every new development adding to faster and more efficient manufacturing processes. Cloud computing can bring forth the next revolution for manufacturing companies by transforming their IT infrastructures and processes from error-prone on-premises to highly available, secure, and efficient cloud, as well as providing cutting edge Internet of Things (IoT), AI/ML, and analytics solutions.
Microsoft Azure holds the promise of the fourth industrial revolution by providing manufacturing solutions that can do the following:
- Help build more agile smart factories with industrial IoT.
- Create more resilient and profitable supply chains.
- Transform your work force productivity.
- Unlock innovation and new business models.
- Engage with customers in new ways.
To learn how you can modernize your manufacturing business using Azure, visit Azure for manufacturing. For more resources, see Microsoft Trusted Cloud for Manufacturing.
Architecture guides for manufacturing
The following articles provide architectural guidelines for Azure solutions in the manufacturing industry.
| Architecture | Summary | Technology focus |
|---|---|---|
| Internet of things (IoT) architecture design | Learn about basic internet of things (IoT) concepts and how to get started with Azure IoT | IoT |
| On-demand, scalable, high-power compute | In this article, we walk through some well-known areas in engineering and manufacturing that need large computing power and explore how the Microsoft Azure platform can help. | Compute |
| Predictive maintenance in manufacturing | After introducing some background to predictive maintenance, we discuss how to implement the various pieces of a PdM solution using a combination of on-premises data, Azure machine learning, and usage of the machine learning models. | AI/ML |
| Predictive maintenance solution | This article presents options for building a predictive maintenance solution. It presents different perspectives and reference existing materials to get you started. | AI/ML |
| Extract actionable insights from IoT data | This guide provides a technical overview of the components needed to extract actionable insights from IoT data analytics. | IoT |
Architectures for manufacturing
The following articles provide detailed analysis of architectures developed and recommended for the manufacturing industry.
| Architecture | Summary | Technology focus |
|---|---|---|
| Automated guided vehicles fleet control | This example architecture shows an end-to-end approach for an automotive original equipment manufacturer (OEM) and includes a reference architecture and several published supporting open-source libraries that can be reused. | IoT |
| Citizen AI with the Power Platform | The architecture extends on the Analytics end-to-end with Azure Synapse scenario. It allows for a custom ML model to be trained in Azure Machine Learning, and implemented with a custom application built using Microsoft Power Platform. | AI/ML |
| End-to-end manufacturing using computer vision on the edge | This example architecture shows an end-to-end approach to computer vision from the edge to the cloud and back. | AI/ML |
| Predictive maintenance with the intelligent IoT Edge | The Internet-of-things (IoT) Edge brings data processing and storage close to the data source, enabling fast, consistent responses with reduced dependency on cloud connectivity and resources. | IoT |
| Quality assurance | This solution shows how to predict failures using the example of manufacturing pipelines (assembly lines). | AI/ML |
Solution ideas for manufacturing
The following are other ideas that you can use as a starting point for your manufacturing solution.