Introduction

ITG Technologies is pleased to have successfully partnered with customer for a 3-month Smart Process Optimization Control Modeling (SPOCM) production deployment. This transformative collaboration focused on using advanced AI/ML techniques to tackle energy inefficiencies in compressor and boiler utility assets at ABI.

Overview of the Production Deployment

The Partnership

Customer reached out to ITG, a leader in digital transformation solutions since 2003, to deploy the Automated AI/ML SORBA software platform. ITG, headquartered in Jacksonville, Florida, has over 50 years of combined experience in factory automation and is a certified solutions partner for the SORBA AI technology.

Objectives

The primary aim was to improve energy consumption inefficiencies by 10-20% through real-time AI industrial optimization techniques. Customer recognized the substantial ROI and immediate business impact this would have on their operations.

What We Achieved

Skillset Transfer

ITG empowered customer’s brewery utilities personnel with the tools and skills to rapidly identify root causes and optimize manufacturing processes. This enabled them to become citizen data scientists capable of predicting machine failures and streamlining reliability efforts, all without writing a single line of code.

Energy Consumption Minimization

We successfully met the project's energy consumption reduction goals. By optimizing control process parameters and reinforcing smart KPI-generated setpoints back to the PID layer in real-time, we helped customer achieve their energy consumption minimization target within the 3-month deployment period.

Cost and Downtime Reduction

The project averted potential unplanned downtime and costly process oscillation events, thereby reducing operational costs and enhancing productivity.

Sustainability Goals

The project contributed to customer’s broader sustainability objectives, aligning with ITG's mission to improve sustainability KPIs that drive value across supply chains and stakeholders.

Documentation and Training

An integral part of the project was to ensure the effective transfer of domain knowledge to customer’s utilities personnel. We provided comprehensive documentation and training, enabling them to proactively predict and counteract machine failures and inefficiencies in less than 90 days.

Conclusion

We are delighted that our partnership with customer successfully addressed complex, multivariate production control challenges. The deployment helped customer move closer to becoming an Industry 4.0-equipped enterprise, increasing production revenues, decreasing operational costs, and achieving their sustainability goals.

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