Data Analytics in Manufacturing with Azure

Manufacturing

The powerful change that data analytics can unlock for companies in the manufacturing space allows for better competition and optimized performance in a highly competitive industry. IoT is playing an increasingly critical role in the manufacturing industry with the monitoring and optimization of manufacturing process data, providing increased insight.

See how OmniData can help you on your journey to the cloud and data modernization to optimize operations while providing insight into all aspects of the business.

Scenario

1

Use data analytics to grow your business and optimize manufacturing lines

With discreet manufacturing processes often requiring components from many factory lines, in different locations getting to grips with the differences in data and the sheer volume of data in order to apply some logic and understanding to the data can become a complex process.

Outcome

Using the power of Microsoft Azure, we consolidated data from a total of 25 manufacturing lines from 3 locations into a cohesive enterprise data environment that allowed us to analyze the exact production flow of each component individually and in the final assembly.

This allowed our customer to compare the performance of different sites and to pinpoint the reasons for the differences, allowing them to answer strategy questions around growth and expansion based on actual business data.

Architecture

How can Azure Data Analytics be used in Manufacturing
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Scenario

2

Use data analytics to track daily production rates for your manufacturing lines

With production numbers coming from various sources in the business (production line, financial, operational, etc.), it is often difficult to get a clear picture of activities. As a result, it is often difficult to optimize production quality and yield.

Outcome

Digital Transformation allows manufacturers to spend time where it matters most. Bringing together data from all the systems in the business to create an accurate daily production view involved getting data from various production, financial and operational systems to create a consolidated view of production.

This allowed for the creation of an environment where opportunities for optimization, cost-saving, and prevention could be identified by analyzing the data.

Architecture

How can Azure Data Analytics be used in Manufacturing
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Scenario

3

Tracking finished goods through the extended logistics cycle

With many manufacturing organizations, producing a tangible product is not all the business is responsible for. These products still need to be shipped and transported to the end customer. In many cases, this involves a lengthy logistics process that could span international borders, including multiple warehouses, and has several potential delays.

Outcome

We defined 24 logistics gates in the cycle ranging from the loading of finished products at the factory through to the first leg of the journey to shipping, storage and eventual delivery to the end customer. The data was then combined to create a single cohesive view of the entire logistics process from start to finish.

This allowed our customer to get to grips with several thousands of high value items that were in the current logistics process, identify specific slow points in the process and manage the entire logistics process with data from all over the world.

How can Azure Data Analytics be used in Manufacturing
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Best Practices: Data Analytics in Manufacturing

The manufacturing Industry sits on giant stockpiles of data. However, this data is rarely ever used efficiently. A Steel Manufacturing Plant in Europe was able to utilize this data and reap the rewards.

Data Analytics has and will continue to become an essential part of manufacturing. Utilizing this data allows manufacturers to optimize their own processes and create better interactions with their customers with greater insights.

With Azure's new platform, IoT Central, addressing IoT problems and building solutions becomes easier leading to "smarter industry management"