PerceptiveAPC - Case Study

Nutritional Powders, Nutraceuticals and Ingredients

Company
Abbott Nutritionals

Challenge
Increase production capacity

Solution
Inferential Sensor, Model Predictive Control, Process Optimiser

Results
Payback within 3 months

BUSINESS CHALLENGE

Abbott Nutritionals operates plants in Europe, Singapore, and North America. Each site has its own unique challenges, specific to the products they manufacture and the markets they serve.

One common factor is the desire to increase process capacity and capability - pushing existing plants closer to their constraints to maximise ROCE and OEE.

The project goal was to increase throughput and raise yield, without compromising the very high standards of product quality. This was to be achieved with no additional capital expenditure on in-line sensors or other devices.

The secondary goal was to accommodate new formulations that presented additional drying challenges; their increased 'stickiness' meant a higher risk of fouling and blocking.

SOLUTION

A robust virtual sensor provides realtime moisture results that are used to continually fine-tune the predictive controller. Operators can define optimisation goals - yield, powder rate, energy savings. Read more...

NutriMV SOLUTION

There are several competing requirements in the manufacture of high-value nutritional powders. Increasing run time to a safe maximum, reducing the energy and chemical costs of plant cleaning, making product to specification with the minimum amount of waste.

First, we examined the key process units to determine where opportunities existed to enhance the operation. Then we developed robust models from process and quality data, to determine how much entitlement could be won and what strategies would be required. Finally, we implemented a suite of Advanced Automation tools:

Automate start-up of evaporators, to reach targets more quickly and avoid process upset
Reduce variability in evaporator outlet solids and increase in mean solids
Optimize scheduling, to better balance output from the evaporators with demand from the dryer
Minimize the disturbance caused by feed tank changes
Deploy inferential 'soft' sensors for real-time powder moisture estimation and control
Calculate dryer humidity and its impact on powder properties
Predictive dryer control, to maximize throughput and avoid blockages
Increase powder rate, provide tighter control of powder moisture, increase yield

RETURN ON INVESTMENT

The energy savings and improvements in yield were enough to return the initial investment within 6 months. Once the plant was able to fully exploit a production capacity increase of more than 8%, the true rate of return was measured in weeks.

Since implementation, we have been asked to develop an operator training simulator, which brings new recruits up to speed more rapidly, while offering a valuable refresher to existing operators.

“The Perceptive system is helping run our plants more efficiently and the support we get is excellent.”

Kevin Brady, Engineering Manager, Abbott