How human expertise at industrial scale and experiments can be combined to improve food process knowledge and control

Allais, Irène; Edoura-Gaena, Roch-Boris; Gros, Jean‐Bernard; Trystram, Gilles

doi:10.1016/j.foodres.2006.11.003

Cited by 9 publications

(4 citation statements)

References 31 publications

(33 reference statements)

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“…A framework for solidly designed interactive assistance systems was for instance proposed by Wandke in 2005 [2]. According to Allais et al the process-relevant sources of knowledge can be represented by using three different kinds of models: models for human expertise, models for data or physical models [3]. The integration of these models into specific assistance systems for food processing have already been pursued in several, mostly scientific approaches; e.g., for processing of dairy (as proposed by Perrot et al [4]) or baking products (as presented by Edoura-Gaena et al and Kansou et al [5,6]).…”

Section: Introductionmentioning

confidence: 99%

Disturbance Simulation in the Packaging Process of Confectionary Using Virtual Commissioning

et al. 2020

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Operator assistance systems can help to reduce disturbance-related machine downtime in food production and packaging processes, especially when combined with machine learning algorithms. These assistance systems analyze the available sensor signals of the process control over time to help operators identify the causes of disturbances. Training such systems requires sufficient test data, which often are hardly available. Thus, this paper presents a study to investigate how test data for teaching machine learning algorithms can be generated by numerical simulation. The potential of using virtual commissioning (VC) software for simulating disturbances of discrete processes is examined, considering the example of a friction and collision-afflicted sub-process from an intermitting wrapping machine for confectionary. In this study the software industrialPhysics (iP) is analyzed regarding accuracy of static and dynamic friction and restitution. The values are verified by setting up virtual substitute tests and comparing the results with analytically determined values. Subsequently, prerecorded disturbances are classified, and seven selected elements are simulated in VC software, recording visual effects and switching the characteristics of sensors. The verification shows that VC software is generally adequate for the assigned task. Restrictions occur regarding the computing power required of the built-in physics engine and the resulting reduction of the machine to be simulated.

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Section: Introductionmentioning

confidence: 99%

Disturbance Simulation in the Packaging Process of Confectionary Using Virtual Commissioning

et al. 2020

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“…Qualitative knowledge difficult to formalize: Human experts still play a key role because they are able to explain part of the complex phenomena through their sensory perceptions (for example flavor, texture). It is particularly true in food engineering where the quality of the food stuffs is evaluated through human senses (Allais et al, 2007;Perrot et al, 2004). Partial existing models: Information about transformation processes may stem from existing mathematical models (e.g.…”

Section: Introductionmentioning

confidence: 99%

“…Knowledge integration has been reported in several application fields, including food science. As for example, Allais et al (2007) illustrate how mechanical laws can be coupled with an expert knowledge database to better comprehend a sponge finger batter process. Hadiyanto et al (2007) applied similar ideas to quality prediction of bakery products.…”

Section: Introductionmentioning

confidence: 99%

Parameter elicitation in probabilistic graphical models for modelling multi-scale food complex systems

Baudrit

Wuillemin

Perrot

2013

Journal of Food Engineering

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“…Food processes involve complex physicochemical behaviors. The information available on food processes is data obtained from laboratory experiments and the expertise of operators involved in controlling production lines (Allais et al . 2007).…”

Section: Introductionmentioning

confidence: 99%

Effect of Manufacturing Level on the Biochemical Characteristics of Cantonese Sausage During Processing

Sun

Zhao

et al. 2011

Journal of Food Biochemistry

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The aim of this article was to investigate the differences in biochemical characteristics of Cantonese sausage between laboratorial and industrial levels during processing. Results showed that although water-soluble nitrogen (WSN) and nonprotein nitrogen showed similar patterns of proteolysis in both sausages, laboratorial sausage exhibited a more extensive protein degradation than those for industrial sample during processing. Peptides of >10 and 3-5 kDa were the main WSN fractions for both sausages. The textural characteristics, including hardness, fracturability, gumminess and chewiness, showed notable increases during processing for both sausages. The microbiological population in the laboratorial sausage was significantly higher (P < 0.05) than that in industrial sausage. Staphylococci and Micrococci were the major microflora in both sausages. Results from sensory analysis showed that different biochemical parameters and microbial groups led to different sensory profiles. PRACTICAL APPLICATIONSCantonese sausage is a traditional Chinese meat product. It is well accepted by consumers over the world. The aim of this article was to evaluate 3 Corresponding

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How human expertise at industrial scale and experiments can be combined to improve food process knowledge and control

Cited by 9 publications

References 31 publications

Disturbance Simulation in the Packaging Process of Confectionary Using Virtual Commissioning

Disturbance Simulation in the Packaging Process of Confectionary Using Virtual Commissioning

Parameter elicitation in probabilistic graphical models for modelling multi-scale food complex systems

Effect of Manufacturing Level on the Biochemical Characteristics of Cantonese Sausage During Processing

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