Barbara Case Studies Edge Computing: Automatic fine-tuning of predictive models in water plants

	Edge Computing: Automatic fine-tuning of predictive models in water plants Barbara

Edge Computing: Automatic fine-tuning of predictive models in water plants

Barbara

Technology Category	Platform as a Service (PaaS) - Edge Computing Platforms
Applicable Industries	Oil & Gas Utilities
Applicable Functions	Maintenance
Use Cases	Edge Computing & Edge Intelligence
Services	Software Design & Engineering Services
Challenge	ACCIONA spent significant time and resources manually testing water samples in a laboratory to determine chemical concentrations. Due to the time it took to obtain these results, they were often outdated and unreliable. This resulted in additional costs related to chemical supply and regulatory penalties. By implementing real-time optimized Machine Learning control algorithms at each of its desalination plants, ACCIONA was able to minimize the use of reactive chemicals, eliminate associated regulatory penalties, and provide an efficient edge infrastructure to implement new applications for predictive maintenance, energy efficiency, sensing, optimization or reinforcement learning. Read More
About Customer	ACCIONA is a global group that develops and manages sustainable solutions for infrastructure, including water, concessions, construction, services, and renewable energy. The company plays a leading role in the water treatment sector, participating in designing, constructing, and operating various water treatment plants. These include drinking water treatment plants, water purification plants, wastewater treatment plants, reverse osmosis desalination plants, and tertiary treatment plants for water reuse. ACCIONA places special emphasis on providing services to cities. Read More
Customer Name	ACCIONA Read More
Solution	ACCIONA aimed to achieve the following objectives: Precise control of the variables to be monitored: The algorithm had the ability to predict the values of chemical elements in the water, which could only be detected by laboratory analysis. By continuously monitoring correlated parameters, ACCIONA aimed to achieve more precise control of these variables. Cost reduction by optimizing reagent dosing control loops ACCIONA aimed to minimize the costs of heavy chemical usage, which would result in savings on penalty payments. Scale the solution globally to all its plants. In order to achieve these objectives, ACCIONA needed a tool that would: Efficiently ingest data from different sensors, machines, and devices. Securely store and manage all their data. Easily deploy their AI models. Automatically adjust their algorithms with environment variables. Remote and centralized monitoring and maintenance of the complete lifecycle of applications and devices. Barbara's Industrial Edge AI Platform was instrumental in deploying, monitoring, and orchestrating algorithms in real time, while complying with the highest cybersecurity standard (IEC62443-4-2 safety level 1 standard). Read More Log in to view content
Data Collected	Water Quality Read More Log in to view content
Contents

Technology Category

Platform as a Service (PaaS) - Edge Computing Platforms

Applicable Industries

Oil & Gas

Utilities

Applicable Functions

Maintenance

Use Cases

Edge Computing & Edge Intelligence

Services

Software Design & Engineering Services

Challenge

ACCIONA spent significant time and resources manually testing water samples in a laboratory to determine chemical concentrations. Due to the time it took to obtain these results, they were often outdated and unreliable. This resulted in

additional costs related to chemical supply and regulatory penalties.

By implementing real-time optimized Machine Learning control algorithms at each of its desalination plants, ACCIONA was able to minimize the use of reactive chemicals, eliminate associated regulatory penalties, and provide an efficient edge infrastructure to implement new applications for predictive maintenance, energy efficiency, sensing, optimization or reinforcement learning.

About Customer

ACCIONA is a global group that develops and manages sustainable solutions for infrastructure, including water, concessions, construction, services, and renewable energy. The company plays a leading role in the water treatment sector, participating in designing, constructing, and operating various water treatment plants. These include drinking water treatment plants, water purification plants, wastewater treatment plants, reverse osmosis desalination plants, and tertiary treatment plants for water reuse. ACCIONA places special emphasis on providing services to cities.

Customer Name

ACCIONA

Solution

ACCIONA aimed to achieve the following objectives:

Precise control of the variables to be monitored: The algorithm had the ability to predict the values of chemical elements in the water, which could only be detected by laboratory analysis. By continuously monitoring correlated parameters, ACCIONA aimed to achieve more precise control of these variables.
Cost reduction by optimizing reagent dosing control loops ACCIONA aimed to minimize the costs of heavy chemical usage, which would result in savings on penalty payments.
Scale the solution globally to all its plants.

In order to achieve these objectives, ACCIONA needed a tool that would:

Efficiently ingest data from different sensors, machines, and devices.
Securely store and manage all their data.
Easily deploy their AI models.
Automatically adjust their algorithms with environment variables.
Remote and centralized monitoring and maintenance of the complete lifecycle of applications and devices.

Barbara's Industrial Edge AI Platform was instrumental in deploying, monitoring, and orchestrating algorithms in real time, while complying with the highest cybersecurity standard (IEC62443-4-2 safety level 1 standard).

Data Collected

Water Quality

Impact #1	[Cost Reduction - Operation] Achieved 250.000 USD savings per plant only in the first year. Expected to save more than $70 million in the first 3 years across its 89 desalination plants.
Impact #2	[Process Optimization - Real Time Alerts] Remotely predict and monitor in real-time the water component values in all their facilities centrally. Overcome fragmentation of equipment and heterogeneity of plant environments.
Impact #3	[Financial Growth - Market Opportunities] Incorporate new applications and models for predictive maintenance, energy efficiency, sensing, and reinforcement learning to optimize other plant operations. Accelerate go-to-market of new models by 800%, thanks to Barbara's remote and automatic management of distributed application deployment.

Impact #1

[Cost Reduction - Operation]

Achieved 250.000 USD savings per plant only in the first year.
Expected to save more than $70 million in the first 3 years across its 89 desalination plants.

Impact #2

[Process Optimization - Real Time Alerts]

Remotely predict and monitor in real-time the water component values in all their facilities centrally.
Overcome fragmentation of equipment and heterogeneity of plant environments.

Impact #3

[Financial Growth - Market Opportunities]

Incorporate new applications and models for predictive maintenance, energy efficiency, sensing, and reinforcement learning to optimize other plant operations.
Accelerate go-to-market of new models by 800%, thanks to Barbara's remote and automatic management of distributed application deployment.

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Overview

Edge Computing: Automatic fine-tuning of predictive models in water plants

Operational Impact