Digital twins of food process operations: the next step for food process models?

Verboven, Pieter; Defraeye, Thijs; Datta, Ashim K.; Nicolaï, Bart

doi:10.1016/j.cofs.2020.03.002

Cited by 114 publications

(90 citation statements)

References 88 publications

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“…Based on literature research and to our best knowledge, this work introduces the first DT based framework for autonomous cooking processes that fulfils real-time data provision. The recent review of Verboven [22] marks the dawn of DTs in the Food Science community. Their realisations of DTs are only post-processing steps included in a vision of cloud-based services.…”

Section: Discussionmentioning

confidence: 99%

Autonomous Cooking with Digital Twin Methodology

Kannapinn¹,

Schäfer²

2021

14th WCCM-ECCOMAS Congress

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This work introduces the concept of an autonomous cooking process based on Digital Twin methodology. It proposes a hybrid approach of physics-based full order simulations followed by a data-driven system identification process with low errors. It makes faster-thanreal-time simulations of Digital Twins feasible on a device level, without the need for cloud or high-performance computing. The concept is universally applicable to various physical processes.

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Section: Discussionmentioning

confidence: 99%

Autonomous Cooking with Digital Twin Methodology

Kannapinn¹,

Schäfer²

2021

14th WCCM-ECCOMAS Congress

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“…Application of virtual models of different food systems with known parameters is an immensely popular method to develop smart management systems of food supply chains [25,110,111,114,120,124]. Application of such systems in reality is a challenging task [1,101,109].…”

Section: Current Knowledge On Cps Application In Food Industrymentioning

confidence: 99%

“…Catering industry is more devoted to the application of smart and collaborative robots [1]. Recent literature also highlights on the potential of digital twins development for the process optimization in agri-food and especially processing factories [109]. However, first complete agri-food applications of digital twins and smart collaborative robotic networks are ought to be demonstrated [1,109].…”

Section: Current Knowledge On Cps Application In Food Industrymentioning

confidence: 99%

“…Recent literature also highlights on the potential of digital twins development for the process optimization in agri-food and especially processing factories [109]. However, first complete agri-food applications of digital twins and smart collaborative robotic networks are ought to be demonstrated [1,109]. Existing methods oriented on niche applications of machine learning and modelling approaches are indicated in literature (Table 1).…”

Section: Current Knowledge On Cps Application In Food Industrymentioning

confidence: 99%

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Food Supply Chains as Cyber-Physical Systems: a Path for More Sustainable Personalized Nutrition

2020

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Current food system evolved in a great degree because of the development of processing and food engineering technologies: people learned to bake bread long before the advent of agriculture; salting and smoking supported nomad lifestyles; canning allowed for longer military marches; etc. Food processing technologies went through evolution and significant optimization and currently rely on minor fraction of energy comparing with initial prototypes. Emerging processing technologies (high-pressure, pulsed electric fields, ohmic heating, ultrasound) and novel food systems (cultured biomass, 3-D bioprinting, cyber-physical chains) try to challenge the existing chains by developing potentially more nutritious and sustainable food solutions. However, new food systems rely on low technology readiness levels and estimation of their potential future benefits or drawbacks is a complex task mostly due to the lack of integrated data. The research is aimed for the development of conceptual guidelines of food production system structuring as cyber-physical systems. The study indicates that cyber-physical nature of modern food is a key for the engineering of more nutritious and sustainable paths for novel food systems. Implementation of machine learning methods for the collection, integration, and analysis of data associated with biomass production and processing on different levels from molecular to global, leads to the precise analysis of food systems and estimation of upscaling benefits, as well as possible negative rebound effects associated with societal attitude. Moreover, such data-integrated assessment systems allow transparency of chains, integration of nutritional and environmental properties, and construction of personalized nutrition technologies.

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“…So far, it is evident the underlying complexity of modelling and simulating volume change and deformation of foods during processing, but at the same time, the importance and thus the need to address this intricate problem. Actually, the development of the next generation of food process models, i.e., digital twins (virtual replica of the real process), certainly requires the inclusion of the previously described aspects, towards a holistic and comprehensive approach for food product/process design, considering the current and future challenges of agri-food industry [ 22 ]. Therefore, the objective of this article is to provide a general review of the more recent (2005–2021) and relevant works that have addressed the modelling and simulation of volume change and large deformation in different food products/processes, from a food engineering perspective.…”

Section: Introductionmentioning

confidence: 99%

Modelling Volume Change and Deformation in Food Products/Processes: An Overview

Purlis

Cevoli

Fabbri

2021

Foods

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Volume change and large deformation occur in different solid and semi-solid foods during processing, e.g., shrinkage of fruits and vegetables during drying and of meat during cooking, swelling of grains during hydration, and expansion of dough during baking and of snacks during extrusion and puffing. In addition, food is broken down during oral processing. Such phenomena are the result of complex and dynamic relationships between composition and structure of foods, and driving forces established by processes and operating conditions. In particular, water plays a key role as plasticizer, strongly influencing the state of amorphous materials via the glass transition and, thus, their mechanical properties. Therefore, it is important to improve the understanding about these complex phenomena and to develop useful prediction tools. For this aim, different modelling approaches have been applied in the food engineering field. The objective of this article is to provide a general (non-systematic) review of recent (2005–2021) and relevant works regarding the modelling and simulation of volume change and large deformation in various food products/processes. Empirical- and physics-based models are considered, as well as different driving forces for deformation, in order to identify common bottlenecks and challenges in food engineering applications.

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Digital twins of food process operations: the next step for food process models?

Cited by 114 publications

References 88 publications

Autonomous Cooking with Digital Twin Methodology

Autonomous Cooking with Digital Twin Methodology

Food Supply Chains as Cyber-Physical Systems: a Path for More Sustainable Personalized Nutrition

Modelling Volume Change and Deformation in Food Products/Processes: An Overview

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