Seminar: On- and inline analysis in the dairy industry - methods and applications

Torsdag, 31 januar, 2019
9.30
Hotel Legoland, Billund

 

The dairy industry is constantly developing the methods and equipment, as well as the intelligence behind it, which makes it possible to install more and more inline-measures in the dairy’s production lines.

The seminar looks into how far the Process Analytical Technology (PAT) are today. Experts and industry-people will, in different presentations, shed light on, how new and enhanced inline-measurements technologies and analyses gives new opportunities to meet the product specifications, optimizing of the production-processes, optimizing the quality and generally a better work flow in the dairies.
During the presentations, examples of the results, made with the use of inline measures in the production optimisation and quality optimisation, will be given. Furthermore, the seminar focuses on what the blockchain systems are, what they have to offer and if blockchain can minimize the risk of food fraud.

Price:
For members of the Danish Society of Dairy Technology: 2.195,- VAT  
For non-members: 2.695,- VAT

Presentations

Program

Changes in the program may occur

Process Analytical Technology creates smart production - How far are we today?

Process Analytical Technology (PAT) essentially deals with measuring the relevant parameters at the relevant time and interpreting the data you get from the measurements correctly in order to control and optimize the production process optimally in relation to, for example, product quality, sustainability, production optimization.
PAT measurements are often fast and non-invasive. They are often done online or inline, which allows you to adjust production while it is in progress so that you get the best quality for every production produces in the dairies. The presentation looks into where PAT are today and as well as with cases.

Associate Professor Klavs Martin Sørensen University of Copenhagen, Food science

A tool for increased effectiveness in the dairy industry

The dairy plants become larger and more complex and at the same time the demand for rapid adaptation to new product recipes and improved accuracy increases. New and enhanced technologies for real time and inline measurement and analysis offer new opportunities for meeting product specifications, optimisation of production processes as well as enhancing the work flow in the dairies.  
The presentation will give highlights on the two subjects; measurement principal as well as the control

The measurement principal part is also covering accuracy, reliability and data analysis.   The control part is covering; the process application, interface as well as control and regulation software. 
The presentation will also highlight how high precision in-line instrument measuring of e.g. fat, protein, solids and lactose could be combined with several advanced control applications at the implementation.

Development Engineer Kim Salling, Au2Mate & International Business Manager Process Michael Sievers, Foss

Self-learning systems

Online NIR equipment in itself does not improve neither process nor product. A valid insight into the process has to be generated, before the results can be used for finetuning and adjusting of the process and thereby optimize as well as production and/or quality.
The requirement for security and accuracy has led to long calibration processes, but new on-line platforms with both hardware and a universe of new software possibilities makes it possible for process technicians without calibration insight to utilize the technology. This is made possible using the automatic (self-driving) car as a role model. This presentation will give a visionary outlook to a future technology based on local resources and supported by a “very wise” cloud.

CTO Anders Larsen, Q-Interline

Production optimisation by use of in-line sensors in Arla Foods

In Arla Foods more and more in-line sensors are installed. The presentation takes offset in Arla Foods way of working with inline sensors and their experience with inline sensors from feasibility test to implementation. Results and benefits of inline measurements in production will be presented with a specific case from one of Arla’s dairies.

 

Excellence Manager Christian Zachariasson & Project Manager Simon Mortensen, Arla Foods

Blockchain – Full transparency and honest food products. Scan me and know my history

The tendency among consumers and producers are, that they request easily accessible information and information about the products they use and consume. To accommodate this, producers – particularly food producers – have sought a platform, where the history of the products and general information can be accessed. Through a Blockchain based solution, the producers and consumers can now get insight into the product history from farm to fork.  
The presentation will cover how the Blockchain system works, which benefits Blockchain offers and whether Blockchain can minimize the risk of fraud with food products.

Marked Leader, Retail & Food Lone Hansen, Bureau Veritas

Calibration of inline sensors

Any single point of measurement needs a proper adjustment and calibration to be able to show correct values. The presentation will go through how inline sensors can be adjusted and what the consequences it might be if the sensors are not properly calibrated.

Business Development Manager, Dino Holmqvist & Senior QA Specialist Carsten Theisen, Eurofins

Artificial intelligence in manufacturing

In the talk you will hear about how to get started with artificial intelligence, in the production. Why is it that sometimes hits the "golden batch" where the product has a superb quality, unlike other times when the result is mediocre? Artificial intelligence might answer this, but perhaps you just use the wrong analysis tools or data sources? You will also get an understanding of the challenges to be solved before and after hiring your first "digital AI employee", and how artificial intelligence actually works under the bonnet.

Director Mads Voigt Hingelberg, Big Data by Innovation Lab