Industrial automation
Industrial Internet of Things (or Industry 4.0) in combination with Robotics, Artificial Intelligence, Augmented Reality and Edge Computing is fundamentally transforming production systems. Simple assembly lines up to large manufacturing plants take advantage of deployed sensors and data analytics to optimize their production & supply chains and improve their TCO. Composing and deploying workflow automations that combine data retrieved from traditional SCADA and ERP systems, real-time streams coming from IoT sensors along with modern Machine Learning algorithms while guaranteeing security and privacy are tedious procedures needing strong data engineering expertise. In addition, scalability, multi-site management, limited compute power infrastructure at the edge and possible off-line mode are some more issues that complexify workflow deployments for Industrial Automation. Ryax offers a data engineering platform that facilitates the creation and deployment of Industry 4.0 data analytics workflows by proposing features such as integrations to traditional industrial protocols and systems, offering low overhead orchestration for edge deployments, seamless edge-cloud execution, stringent security and privacy policies and multiple supported machine learning frameworks.
Ryax applied to predictive maintenance
Complete user walkthrough
Connect data sources
Without Ryax
Data Engineers need to assist Data Scientists in connecting data sources and anticipating incidental events.
- Data Engineers must map and connect data sources
- In case of any incidental event (e.g. when sensors stop sending data or servers stop responding) teams need to:
- Proactively detect that the server/sensor is faulty
- Need to define when and how to start the chain over
- Establish and implement a procedure to deal with missing/delayed/corrupted data
- To finally restore the workflow
- Data Engineers need to build (from scratch) a way to communicate their process externally.
With Ryax
Seamless data sources connection. Integrated & automated event-driven procedures.
- Data Scientist can connect data sources at their own level
- Functions to deal with incidental events are already pre-coded, Data Scientists can configure them in a few minutes with no specific IT knowledge
- Ryax provides high-level visualisation of these functions, enabling full transparency and easy reporting to clients and/or hierarchy
Manage complex stream processing tasks
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Without Ryax
Data Engineers need to build a complete set of complex functions to deal with stream processing requirements.
- Engineers must create processes for live concatenation of heterogeneous data sources (different natures, types, volumes, temporalities)
- They need to ensure data treatment consistency in the context of imprecise and evolutive tempo: non ideal clocks, time changes…
- They must anticipate incidental events:
- Missing/delayed/corrupted/bursting data sources
- Unbalanced computing power across workflows
- And implement live scaling accordingly
- Data Engineers need to build (from scratch) a way to communicate their process externally.
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With Ryax
Integrated & automated management of complex, asynchronous live data from multiple industrial sources.
- Stream Processing functions are already pre-coded, Data Scientists can configure them in a few minutes with no specific IT knowledge
- Ryax provides high-level visualisation of these functions, enabling full transparency and easy reporting to clients and/or hierarchy
Integrate the Predictive Maintenance workflows
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Without Ryax
Data Scientists and Predictive Maintenance experts will have to code from scratch.
- Even the simplest function (if then, less than…etc) has to be hand-coded from scratch
- Cross-function interfacing has to be implemented
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With Ryax
Data Scientists can drop their Predictive Maintenance algorithms in the treatment chain. They can focus on what they are good at.
- Data Scientists can use pre-established standard functions for all main actions (send to, filters, loops…etc) that are already interfaced
- Functions are evolutive and get richer over time
Manage multi-language frameworks
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Without Ryax
Data Scientists will be limited to the framework(s) they master.
Data Scientists and Predictive Maintenance experts will have to code from scratch:
- Handwrite compatibility scripts ac
- Cross-function interfacing has to be implemented
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With Ryax
Data Scientists can expand to multiple interconnectable frameworks.
Data Scientists can focus on what they do best, thanks to Ryax’ precoded functions:
- Data Scientists can use pre-established standard functions for all main actions (send to, filters, loops…etc)
- Functions and frameworks interfacing is already provided
- Function libraries are evolutive and get richer over time
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