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Case Study

Explore the Benefits and Use Cases for Industrial Edge Computing in Manufacturing

We recently heard about Edge computing from Chris Liu, Industrial Edge Product Marketing Manager at Siemens. He provided some basic information as well as four ways manufacturers can prove ROI using Edge computing.

For a non-technical person, can you explain what Edge computing is?

Edge computing is a distributed way of processing and analyzing data closer to where the data is generated. Edge computing brings the IT computing power to the shop floor and gives the flexibility to keep sensitive data locally or send pre-processed data to a centralized data center or cloud server, so you get full control over the data.

Think of a smartphone – you can still use pre-installed apps such as camera, calculator or GPS on airplane mode without connecting to the internet, but you can then choose to make phone calls, writing emails or post on social media whenever you connect to wifi or use cellular data.

When is it best to use edge computing?

When below functionalities are required:

  1. Low latency – Faster data processing (ms) and response times
  2. High bandwidth – Save both bandwidth and cost associated with data transfer
  3. Security – Keep sensitive data local without suffering from cyberattack or server outage.

Does Edge Computing need to be used in certain locations (I.e. no Wi-Fi or internet connections)?

It does not – Edge computing devices can be deployed in any location where computing resources are required. You can use Edge devices without Wi-Fi, and only need to connect to internet in instances where you send data to the cloud, download apps to your Edge device, or execute firmware updates. In most industrial settings, Edge devices are placed on the shop floor next to the machine to provide faster response times and reduced latency.

What is the difference between edge computing and cloud computing?

Cloud computing is a centralized computing platform or model that provides on-demand access to computing resources over the internet without using a dedicated hardware infrastructure, while Edge computing is a distributed computing paradigm that brings computing resources closer to the data source that allows real-time data processing, local data storage and analysis, and low latency.

How can Edge computing benefit OT and IT? Who owns and/or do you have any tips for how OT and IT can work together to implement and maximize Edge computing? 

Edge computing facilitates OT/IT convergence by enabling data transparency from the shop floor to the IT level. It enables data aggregation, contextualization, and transparency, ensures data security, and allows users to understand correlations.

OT and IT need to: 

  1. Collaborate to identify the value and align responsibilities of each side on targets and strategy.
  2. Prioritize and start with selected use cases and defined solutions. 
  3. Define the data and communication technologies for efficient engineering, flexibility, and scalability.

What is the greatest benefit that you have seen from manufacturing customers implementing Edge computing? Do you have any lessons learned you can share? 

Customers use Siemens Industrial Edge to collect and combine data from different sources, which closes the gap between the shop floor and the cloud, and it enables end-to-end vertical data integration. 

For example, many data management systems based on MQTT simply provide a single data point in a flat list which makes it difficult for different users to understand the meaning of the data. It is challenging to use a flat list with thousands of variables and impossible to retrieve data automatically. Siemens Industrial Edge resolves this by mapping all tags onto an OPC UA data structure or asset model within an application called Industrial Information Hub, which makes data retrieval and data synchronization much easier and safer.

How many apps can you install on a single Edge device? 

That depends on the size of the app(s) and the RAM of the device. 

How much data can be stored on the Edge device? 

This depends on the capacity of the Edge device.  The industrial Edge device box IPC 127E can store 96G but Rack IPC 847E can store up to 858G.

How can manufacturers prove ROI from Edge computing? 

There are 4 ways that manufacturers can prove ROI from implementing an Edge computing solution:

  1. Cost reduction – Edge computing allows local data storage and analysis, which saves bandwidth and storage and their associated costs. Manufacturers can choose to send desired and pre-processed data to a central server or cloud system with Edge computing, which makes data management more flexible. 
  2. Reduce downtime – Manufacturers can use Edge computing to measure anomalies and identify or address issues before it gets severe, which reduces downtime and increases availability. Edge computing enables predictive maintenance that reduces maintenance costs as well as ensures and optimizes operation.
  3. Cybersecurity – Edge computing allows manufacturers to process and store data locally and keep sensitive data secure that minimizes the risk from cyberattacks or data breaches and enhances cybersecurity.
  4. Gain transparency to improve efficiency – Manufacturers can use Edge computing to analyze real-time data collected from machines and equipment to gain and calculate OEE and energy consumption. This helps them reduce scrap and waste, and further optimize production processes and improve efficiency.

Want to learn more? View Unlock Full Machine Potential with Industrial Edge webinar recording featuring Siemens’ experts.

Chris Liu

Chris Liu

Industrial Edge Product Marketing Manager, Siemens

Chris Liu is the Product Marketing Manager for Siemens Edge computing technology Industrial Edge for the U.S. He has a bachelor’s degree in Electrical Engineering from Purdue University with years of industry experience in engineering, manufacturing and product management. Chris started with Siemens in 2021 and focuses on leveraging Industrial Edge to help customers make practical use of their machine and plant data to optimize workflows, save resources, and improve quality.