AI in Process Optimization

Businesses are built on processes.

- Dr. Kaushik Ramakrishnan

A process is a structured, sequential list of activities that takes inputs and transforms them into the desired output. From a manufacturing perspective, the inputs are real world materials like minerals or agricultural commodities which undergo physical/mechanical or chemical transformations. A manufacturing process can be discrete (batch/countable output) or continuous (uncountable). A manufacturing process is evaluated on the basis of its efficiency, cost, and output quality. The defining characteristics that influence these evaluation criteria are input, output, transformation activities, resources, control parameters, constraints, and process owner. By using data analytics, automation, and continuous evaluation, businesses enhance productivity and cut costs without sacrificing quality. This is known as process optimization.

Process optimization in the food industry, therefore, is highly relevant from the perspective of minimizing waste, maximizing product consistency, optimizing energy and water consumption, and ensuring strict compliance with health and safety standards.

Focus Areas

There are four core focus areas in which process optimization can be achieved in the food industry.

• Ingredient and recipe optimization

• Processing and equipment control

• Quality, safety, and compliance

• Resource efficiency and sustainability

Specialized data-centric tools are deployed to achieve this optimization, including AI/ML, SCADA, and IoT sensors, and RSM (response surface methodology).

Ingredient and recipe optimization

A recipe formulation defines:

• Ingredient composition

• Proportions

• Functional balance