Kunstig intelligens og interaktiv læring vil forme arbeidslivet

Vil roboter i nær fremtid klare å utføre kompleks bearbeiding av råstoff som i dag kun utføres av mennesker? Hvordan kan dette bidra til en mer bærekraftig matproduksjon i Norge? Den 4. februar ble den

Program og påmelding til TechFood og sluttmøte i iProcess

TechFood Vil roboter i nær fremtid klare å utføre kompleks bearbeiding av råstoff som i dag kun utføres av mennesker? Hvordan kan dette bidra til en mer bærekraftig matproduksjon i Norge? Hva kan robotene gjøre for

Raman spectroscopy for quality differentiation of pork

Raman spectroscopy can be used for analysis of important quality indicators in meat, feasibly leading to on-line applications of the technique in the future.   Overall meat eating quality is very important for consumer confidence, willingness to pay

5 points to consider before setting sails in data science projects in the food industry

In the slipstream of the digitalization of modern food industry, part of Industry 4.0, a paramount need to handle larger and larger amounts of data has called for new developments in both the analytical toolbox

Tracking non-rigid objects using depth camera

Surface of non-rigid objects, such as leafy vegetables, meats and fishes can be completely and accurately tracked using a depth camera with the approach proposed in this article. This is exceptionally useful while interacting with

Raman spectroscopy for estimation of residual bone minerals in mechanically deboned chicken meat

Residual bone, measured as %calcium or %ash, is a strictly controlled quality parameter of mechanically deboned chicken meat (MDCM). Raman spectroscopy was developed as a rapid tool for estimation of this important parameter.  Mechanical deboning

Porosity maps give an ‘airy’ image of fruit and vegetables

See the internal structure of your product through 3D X-ray based porosity mapping.   The porosity of a fruit or vegetable quantifies the amount of air spaces inside the product. The porosity strongly determines to what

Managing supply uncertainty in operational production planning – A whitefish case study

Managing supply uncertainty by a formal stochastic programming approach demonstrates how expected profit may be increased due to more robust production plans.   Production planning Operational production planning deals with establishing optimal production plans. A production

411, 2019

Integrated planning in white fish supply chains

Through integrated supply chain planning by sharing information, uncertainty is mitigated

2504, 2016

WP 7 Management

Project Leader: Ekrem Misimi, SINTEF Ocean (SO) Participating partners SO, Management team,

2504, 2016

WP 6 Dissemination and Communication

Work Package leader / Responsible partner: SFA and Røe Kommunikasjon

2504, 2016

WP 5 Value chain strategies and business models

Work Package Leader/Responsible partner Dr. Ragnar Tveterås, Centre for Innovation

2504, 2016

WP 4 Information Management

Work Package Leader/Responsible partner: Dr. Maitri Thakur, SINTEF Fisheries and

2104, 2016

WP 3 Flexible Processing Automation

Work Package Leader Dr. Ekrem Misimi, SINTEF Fisheries and Aquaculture

2104, 2016

WP 2 Optimal process control and raw material differentiation

Work Package Leader: Dr. Jens Petter Wold, Nofima Participating partners: Nofima, SFA,

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About us 

iProcess’s main objective is to develop novel concepts and methods for flexible and sustainable food processing in Norway – that are to cope with small volume series and high biologicalvariation of the existing raw materials – to enable increased raw material utilization for food
products and to increase profitability.

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