Robotics in food manufacturing

2011 ◽  
pp. 213-224
Author(s):  
K. Khodabandehloo
Keyword(s):  
Food Manufacturing

Modeling Transport in Porous Media With Phase Change: Applications to Food Processing

2010 ◽  
Vol 133 (3) ◽  
Author(s):  
Amit Halder ◽  
Ashish Dhall ◽  
Ashim K. Datta
Keyword(s):  
Mass Transfer ◽  
Porous Media ◽  
Food Processing ◽  
Transport Processes ◽  
Phase Changes ◽  
Solid Matrix ◽  
Deep Fat Frying ◽  
Modeling Framework ◽  
Food Manufacturing ◽  
Food Processes

Fundamental, physics-based modeling of complex food processes is still in the developmental stages. This lack of development can be attributed to complexities in both the material and transport processes. Society has a critical need for automating food processes (both in industry and at home) while improving quality and making food safe. Product, process, and equipment designs in food manufacturing require a more detailed understanding of food processes that is possible only through physics-based modeling. The objectives of this paper are (1) to develop a general multicomponent and multiphase modeling framework that can be used for different thermal food processes and can be implemented in commercially available software (for wider use) and (2) to apply the model to the simulation of deep-fat frying and hamburger cooking processes and validate the results. Treating food material as a porous medium, heat and mass transfer inside such material during its thermal processing is described using equations for mass and energy conservation that include binary diffusion, capillary and convective modes of transport, and physicochemical changes in the solid matrix that include phase changes such as melting of fat and water and evaporation/condensation of water. Evaporation/condensation is considered to be distributed throughout the domain and is described by a novel nonequilibrium formulation whose parameters have been discussed in detail. Two complex food processes, deep-fat frying and contact heating of a hamburger patty, representing a large group of common food thermal processes with similar physics have been implemented using the modeling framework. The predictions are validated with experimental results from the literature. As the food (a porous hygroscopic material) is heated from the surface, a zone of evaporation moves from the surface to the interior. Mass transfer due to the pressure gradient (from evaporation) is significant. As temperature rises, the properties of the solid matrix change and the phases of frozen water and fat become transportable, thus affecting the transport processes significantly. Because the modeling framework is general and formulated in a manner that makes it implementable in commercial software, it can be very useful in computer-aided food manufacturing. Beyond its immediate applicability in food processing, such a comprehensive model can be useful in medicine (for thermal therapies such as laser surgery), soil remediation, nuclear waste treatment, and other fields where heat and mass transfer takes place in porous media with significant evaporation and other phase changes.

Optimisation of the resource efficiency of food manufacturing via the Internet of Things

2021 ◽  
Vol 127 ◽  
pp. 103397
Author(s):  
Sandeep Jagtap ◽  
Guillermo Garcia-Garcia ◽  
Shahin Rahimifard
Keyword(s):  
Internet Of Things ◽  
Resource Efficiency ◽  
The Internet ◽  
Food Manufacturing ◽  
The Internet Of Things

scholarly journals Enhanced Clean-In-Place Monitoring Using Ultraviolet Induced Fluorescence and Neural Networks

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3742 ◽  
Author(s):  
Alessandro Simeone ◽  
Bin Deng ◽  
Nicholas Watson ◽  
Elliot Woolley
Keyword(s):  
Image Processing ◽  
Digital Camera ◽  
Computation Time ◽  
Cleaning Process ◽  
Food Manufacturing ◽  
Intelligent Decision Making ◽  
Intelligent Decision ◽  
Potential Benefits ◽  
Image Acquisition System ◽  
Nonlinear Autoregressive

Clean-in-place (CIP) processes are extensively used to clean industrial equipment without the need for disassembly. In food manufacturing, cleaning can account for up to 70% of water use and is also a heavy user of energy and chemicals. Due to a current lack of real-time in-process monitoring, the non-optimal control of the cleaning process parameters and durations result in excessive resource consumption and periods of non-productivity. In this paper, an optical monitoring system is designed and realized to assess the amount of fouling material remaining in process tanks, and to predict the required cleaning time. An experimental campaign of CIP tests was carried out utilizing white chocolate as fouling medium. During the experiments, an image acquisition system endowed with a digital camera and ultraviolet light source was employed to collect digital images from the process tank. Diverse image segmentation techniques were considered to develop an image processing procedure with the aim of assessing the area of surface fouling and the fouling volume throughout the cleaning process. An intelligent decision-making support system utilizing nonlinear autoregressive models with exogenous inputs (NARX) Neural Network was configured, trained and tested to predict the cleaning time based on the image processing results. Results are discussed in terms of prediction accuracy and a comparative study on computation time against different image resolutions is reported. The potential benefits of the system for resource and time efficiency in food manufacturing are highlighted.

The Structural Stability of the Concentration-Performance Relationship in Food Manufacturing

1982 ◽  
Vol 14 (2) ◽  
pp. 43-49
Author(s):  
Stephen E. Miller
Keyword(s):  
Industrial Organization ◽  
Linear Relationship ◽  
Structural Stability ◽  
Market Performance ◽  
Continuous Linear ◽  
Food Manufacturing ◽  
The Relationship

The literature of industrial organization is replete with analyses of the relationship between seller concentration and market performance. Most researchers have hypothesized a continuous linear relationship between profitability and concentration and have estimated that relationship accordingly.

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