Food Manufacturing

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The accuracy of any measured data is clearly important when considering its value. However, equally important when assessing the potential of any analytical system is the relevance of the data it provides. Focusing on our area of expertise, the in-process behavior and flow of powder, there are many different techniques used routinely to measure flow properties. Some are relatively accurate, but many fail to provide information relevant to the process environment and are, therefore, less suitable for process optimisation.

Shear testing produces information that can be used, for example, to assess the likely behavior of powder in a hopper, where the powder is stored under its own weight and in a relatively high stress state. However, when optimizing a pneumatic conveying line, for example, where the powder is under much lower stress and subjected to a much higher dynamic regime, shear data is far less relevant.

Dynamic powder characterization is considerably more informative for situations where the powder is flowing in a more dynamic or an unconsolidated state. This technique can be applied to aerated and even fluidized powders, to directly measure the powder’s flow properties when in a low stress state.

Further measurements of bulk properties, such as compressibility, permeability and density should also be considered to complement dynamic and shear measurements.

Used together, dynamic, shear and bulk powder testing can provide useful information that, amongst other possibilities, enables food processors to ensure reliable, consistent flow through the plant; understand blending performance and achieve optimized blend uniformity; assess alternative feed supplies in a meaningful way; investigate fill weight variability; and control the impact of humidity.

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If more accurate information is provided from the sensor, the whole control system is better able to consistently provide the desired results with tighter specification in terms of product quality and cost optimization.

In a food application, one of the primary challenges users address is getting the right blend ratio of raw materials. Raw material supply can change, or cost pressure may require different ingredients to take advantage of changes in commodity pricing. A defined ratio of raw materials helps the end product taste right, and meet both nutritional and regulation requirements. When they are not mixed to the correct finished product specification, the product must be reworked or disposed of as waste. Automated blending technologies leverage a special algorithm based on the quantity of material being mixed and correlating it with the quality characteristics of both the raw material and finished product. This allows blending operations to utilize capital equipment more efficiently and reduce, or even eliminate, the need for intermediary vessels.

Feedback from smart instrumentation is the key to effectively monitoring raw materials. Process control sensors and actuators (devices measuring and controlling level, flow, temperature and other variables) provide seamless interconnectivity into critical business systems like MRP and LIMS.

There’s a growing need to capture more data, deliver it faster, perform additional diagnostics, access all device information remotely and leverage the data across the manufacturing enterprise. Many instruments now communicate using EtherNet/IP™ to help collect this information. With EtherNet/IP, which is based on standard unmodified Ethernet, users have easier and better access to real-time data, which improves the ability to monitor overall performance, troubleshoot out-of-margin conditions and minimize downtime.