LOGO - CORDIS
018176
MILQ-QC-TOOL
Project full title:
The development of predictive models on the Internet for optimisation of heat treatment of raw milk in small and medium-sized dairy companies
sixth framework programme
horizontal research activities involving smes
co-operative research
FINAL Activity Report
Period covered: from 16/9/2005 to 15/12/2007 Date of preparation: 15/01/2008
Start date of project: 16/9/2005 Duration: 2 years, 3 months
Joost van Dijk Revision: 1
Van Dijk Kaasmakerij BV
NIZO food research BV
M.A.I Schutyser
Wirelessinfo
P. Gnip, P. Horak
January 2008
1 Executive Summary 3
1.1 Aim 3
1.2 Tasks and objectives 3
1.3 Results 4
1.4 Milestones and deliverables 5
1.5 Corrective actions 7
2 Project objectives and major achievements 8
2.1 General Project Objectives 8
2.1.1 Objectives and targets of this project 8
2.1.2 International state-of-the-art 10
2.2 Summarise the objectives 11
2.3 Problems and corrective action 12
3 Work packages 13
3.1 Progress towards objectives WORK PACKAGE 1: Identification of products, processes, soft- and hardware requirements. 13
3.1.1 Task 1.1 – Collection of processing data and product data. 13
3.1.2 Task 1.2 – Collection of experimental data 15
3.1.3 Task 1.2 – Collection of data to validate the customised/calibrated predictive models 16
3.1.4 Deviations from the project work program and corrective actions 20
3.1.5 Deliverables 20
3.1.6 Milestones 21
3.2 Progress towards objectives WORK PACKAGE 2: Development of the first prototype 21
3.2.1 Task 2.1 – Customisation and validation of the predictive models 22
3.2.2 Task 2.2 – Evaluation of the first prototype 23
3.2.3 Deviations from the project work program and corrective actions 24
3.2.4 Deliverables 24
3.2.5 Milestones 25
3.3 Progress towards objectives WORK PACKAGE 3: Development and hosting of Internet application 25
3.3.1 Task 3.1 – Development of a secure Web page 26
3.3.2 Task 3.2 – Development of a Web database structure 26
3.3.3 Task 3.3 – Development of the basic simulation environment 28
3.3.4 Task 3.4 – Hosting of the Web application 29
3.3.5 Deviations from the project work program and corrective actions 30
3.3.6 Deliverables 30
3.3.7 Milestones 30
3.4 Progress towards objectives WORK PACKAGE 4: Training and implementation of simulation software 31
3.4.1 Task 4.1 Preparation of a user manual 31
3.4.2 Task 4.2 Arrangement of help-desk facilities 32
3.4.3 Task 4.3 Training of SMEs with the modelling tool 32
3.4.4 Deviations from the project work program and corrective actions 34
3.4.5 Deliverables 34
3.4.6 Milestones 34
3.5 Progress towards objectives WORKPACKAGE 5: Project management activities 35
3.5.1 Task 5.1 Overall project management 35
3.5.2 Task 5.2 – Exploitation and dissemination 37
3.5.3 Deviations from the project work program and corrective actions 37
3.5.4 Deliverables 37
3.5.5 Milestones 38
4 Consortium Management 38
5 Other issues 41
Annex I – Project deliverables 42
Executive Summary
1 Aim
The aim of the project has been to develop a web application, accessible on the internet, for optimization of heat treatment e.g. pasteurization processes in the dairy industry. This project has been carried out by a consortium of SME’s and two research providers. One of the fundamental ideas underlying the project was that SME’s should benefit from the applicable technology that has been developed. The application has potential to improve product quality, maximize food safety and minimize production costs. No integrated user friendly and web based model is available yet to achieve this task.
2 Tasks and objectives
The project has been completed in December 2007. The following tasks have been carried out during the course of the project:
1. Inventory of field conditions for heating processes at sixteen European small and medium dairy enterprises; pasteurizing equipment and processes have been described for each of the participating companies;
2. Selection of process-product combinations and collection of technical processing data and product data. The data collection phase has been of prime importance for the development of the prototype;
3. Development of a first prototype of the predictive model, definition of parameters used to optimize processes in the dimensions: production efficiency; pasteurizer fouling; food safety;
4. Design and implementation of a web-database structure and interface with the predictive model;
5. Develop and host a uniform simulation environment as Web application on the Internet;
6. Use the model to predict optimal circumstances for the consortium members selected production processes and report on the recommendations;
7. Collection of experimental data required for customisation and calibration of the available predictive models; i.e. new process settings have been recommended to consortium partners, they have implemented these settings and taken additional samples to validate the model;
8. Use field-data for model validation; additional reports to the participants with supporting evidence;
9. Carry out additional kinetic parameter estimation experiments to validate the model;
10. Write a manual for the resulting application called WebSim-MILQ;
11. Develop learning tools for end users; The tool is user friendly but still requires specialist training, a case has been defined and an e-learning platform has been created;
12. Define a structure for exploitation after project has ended.
13. To provide a forum for knowledge exchange during workshops for all participants
14. To train the dairy firms how to use the knowledge and show the potential of the tool to speed up product development cycles.
3 Results
Optimisation of heat treatments in dairy industry: Development of a
new web-based tool with predictive models (WebSim-MILQ).
Abstract
The main reason for heat treatment of milk is inactivation of harmful bacteria (e.g. Listeria monocytogenes) and enzymes such as milk lipase and plasmin. Besides inactivation of microorganisms and enzymes, heat treatment also adversely affects taste and quality of products. Heat treatment procedures such as high temperature/short time (HTST) pasteurization and ultra-high temperature (UHT) treatment have therefore evolved. Throughout 15 years NIZO experts work with predictive models describing chemical, physical and biochemical reactions that occur during heating of milk. This work has lead to the development of NIZO Premia, software with various computer models for optimization of dairy processes (heat treatment, membrane filtration, spray drying, cheese production, and evaporation). Main application of NIZO Premia is improving food safety and quality, reducing of energy consumption, and accelerating new product development. Many of the available predictive models are however not suitable for SME’s, because they are designed for use by R&D experts and thus not always user-friendly. Therefore, 16 small and medium dairy enterprises (SME’s) joined forces to set-up an EU project to develop a web based version of the modeling tools for heat treatment (Websim-MILQ available at websim.). NIZO food research and Wirelessinfo developed the web application in such a way that it is user-friendly and designed to the specifications of the SME’s. In the project the models were applied for optimization of a selected heat treatment in each SME. A stepwise approach was followed that consisted of process data collection, product analysis, predictive model implementation, and finally optimization of the heating process. This approach led to concrete improvements with respect to process efficiency (e.g. increased cheese yield), food safety, and reduction of fouling. The web application itself was introduced to the SME’s through training sessions and via the development of ultilingual tutorials. Shortly, the web application will be available to any interested dairy company.
Keywords: predictive modeling, heat treatment, web application
Illustration of WebSim-MILQ’s interface
[pic]
4 Milestones and deliverables
Table: Milestones
|Milestone no. |Milestone name |WP no. |Date due |Actual delivery date |Lead Contractor |
|Month 9 |Month 9: After task 1.1 and 1.2. all data required |1 |01/09/06 |01/10/06 |NIZO |
| |for customising and calibrating the models will be | | | | |
| |available, which will be done in work package 2. | | | | |
|Month 14 |Month 14: At the end of this work package all |1 |01/02/07 |01/10/07 |NIZO |
| |required data, including validation data, are | | | | |
| |collected. The validation data will be used in work | | | | |
| |package 2 to validate the customised/calibrated | | | | |
| |models. The data will be stored in the Web database | | | | |
| |structure which will be developed in work package 3 | | | | |
| |(task 3.2 | | | | |
|Month 12 |Month 12: The first off-line prototype of the model |2 |01/09/06 |01/12/06 |NIZO |
| |based on the customised/calibrated models will be | | | | |
| |available and ready to be evaluated by the SMEs. This| | | | |
| |prototype will also be used as a basis for building | | | | |
| |the Web enables version of the model (work package 3,| | | | |
| |task 3.3). | | | | |
|Month 18 |Month 18: At the end of this workpackage the |2 |01/06/07 |1/9/07 |NIZO |
| |predictive models will also be validated for the SMEs| | | | |
| |and each SME will know how to use the models. For | | | | |
| |each SME the selected heating process has been | | | | |
| |optimised with respect to product quality and | | | | |
| |fouling. This means that from this stage all SMEs can| | | | |
| |run their production with lower costs, whereas | | | | |
| |product quality and safety are the same. Furthermore,| | | | |
| |the Web enables version of the model can now be | | | | |
| |completed (workpackage 3). | | | | |
|Month 7 |Month 7: Hosting of the Web page will be available |3 |15/04/06 |01/05/06 |Wirelessinfo |
| |and facilitated during the rest of the project. | | | | |
|Month 24 |Month 24: At the end of this work package the |3 |01/10/07 |01/10/07 |Wirelessinfo |
| |predictive models will be available on a secure and | | | | |
| |safe Internet site. | | | | |
|Month 24 |Month 24: After this workpackage the implementation |4 |01/10/07 |15/12/07 |NIZO |
| |of the modelling tool is at each SME is established. | | | | |
| |All SMEs are capable of working with the Internet | | | | |
| |application and a manual will be available on how to | | | | |
| |use this application on the Web. | | | | |
|Month 23 |Month 23: Licence contract and consortium agreement |5 |01/09/07 |15/12/07 |Van Dijk |
|Month 27 |Month 27: Final review report. |5 |31/12/07 |15/12/07 |Van Dijk |
|Month 27 |Month 27: Final Plan for using and disseminating |5 |31/12/07 |15/12/07 |Van Dijk |
| |knowledge | | | | |
Table: Deliverables
|Del. |Deliverable name |WP no. |Lead participant |Estimated |Nature[1] |Dissem. |Actual Delivery|
|no. | | | |person-mon| |level[2] |date (last |
| | | | |ths | | |version) |
|D1 |Work sheet with process and product data |1 |NIZO |15 |R |CO |15/12/07 |
|D2 |Work sheet with experimental data |1 |NIZO |39 |R |CO |15/12/07 |
|D3 |Work sheet with validation data |1 |NIZO |23 |R |CO |15/12/07 |
|D4 |Customised models – first prototype |2 |NIZO |29 |P |RE |15/12/07 |
|D5 |Evaluation of comments SMEs on first |2 |NIZO |6 |R |RE |15/12/07 |
| |prototype | | | | | | |
|D6 |Report with results of optimised heat |2 |NIZO |24 |R |PU |15/12/07 |
| |treatment | | | | | | |
|D7 |Secure Internet page with public and |3 |Wirelessinfo |4 |P |PU |15/12/07 |
| |private part | | | | | | |
|D8 |Hosting, support and maintenance during |3 |Wirelessinfo |4 |O |RE |15/12/07 |
| |the project | | | | | | |
|D9 |Web database structure |3 |Wirelessinfo |3 |O |RE |15/12/07 |
|D10 |Brief report of test results simulation |3 |Wirelessinfo |4 |R |RE |15/12/07 |
| |environment | | | | | | |
|D11 |Brief report future maintenance protocol |3 |Wirelessinfo |1 |R |CO |15/12/07 |
|D12 |User Manual |4 |NIZO |5 |R |RE |15/12/07 |
|D13 |Report help-desk protocol |4 |NIZO |6 |R |CO |15/12/07 |
|D14 |Models available on the Internet |4 |NIZO |10 |P |CO |15/12/07 |
|D15 |Draft plan for using and dissemination |5 |Van Dijk |1 |R |RE |15/12/07 |
| |knowledge | | | | | | |
|D16 |Licence contract |5 |Van Dijk |0.5 |O |CO |15/12/07 |
|D17 |Consortium agreement |5 |Van Dijk |0.5 |O |CO |15/12/07 |
|D18 |Final plan for using and dissemination |5 |Van Dijk |1 |R |RE |15/12/07 |
| |knowledge | | | | | | |
|D19 |Annual reports |5 |Van Dijk |3 |R |RE |15/3/07; |
| | | | | | | |30/1/08 |
| | | |TOTAL |179 | | | |
5 Corrective actions
To validate the model additional micro-heater experiments have been conducted to estimate kinetic parameters and additional visit have been carried out to examine equipment in cases where the model yielded inexplicable results.
The investigation offered two type of explanations. Care should be given to the way sampling was conducted in the field to minimize variances and error margins. The other type of explanation related to the quality of data that were provided from the field. It turned out that actual flows, temperature readings that were assumed to be true in fact were not. After remedying both types of error sources the model predictions yielded acceptable results with a margin of about +/-1.5%.
The second type of corrective actions relates to consortium management. It was deemed necessary to maintain a consortium of sixteen members as originally was foreseen in the project description. This has lead to some replacements during the course of the project and a number of task running concurrently. The effect has been a three month delay in relation to the originally approved starting date of the project.
Due to changes in the consortium some tasks have been carried out later than originally was planned. Overall the work planning was workable. An extension was requested until the 15th of December to complete training of the participating companies and the training material.
Project objectives and major achievements
1 General Project Objectives
1 Objectives and targets of this project
Introduction
The aim of this project was to develop an easily accessible user-friendly application for heat treatment in dairy processes that is available on the internet and can safely accessed from terminals in the own environment. The project is set up around the bracket of small and medium sized companies (SMEs) to optimise heat treatment in the production of dairy products. The application is easy to use and the results should be interpretable for the quality/product design personnel of the participating dairy companies. Now the project phase has finished the application will also be made available for other users. Measures have been taken to manage maintenance, security and marketing of the application past the project horizon.
The uniqueness of the models used in this application is the integration of a number of product parameters together with processing parameters. In comparison, most research projects are about finding and estimating single parameters. These predictive models have been applied by larger dairy companies with success for research and development purposes. It is expected that if SME’s have access to similar software, innovations and process optimization speed is enlarged. At this time, at the end of the project, the models are bundled in an easy to use the application called WebSim-MILQ.
The tool is expected to yield accelerated improvement in product development, reduced energy use, and increased efficiency of production. The SMEs have selected process(es) and direction of optimisation at the beginning of the project since some of these objectives are conflicting. Process(es) have been upgraded using the knowledge of the predictive models during the course of the project. Meanwhile the models have been validated and packaged as a user friendly web-application.
The social objectives are:
- Improved quality of dairy consumer products.
- Improved market position for SMEs.
- The large variety of regional dairy consumer products will stay intact.
- Substantial energy reduction that will help Europe to work on the Kyoto protocol for sustainable development and energy reduction.
- Improved knowledge level in the dairy industry regarding their processing conditions.
A continuously returning issue within the bracket of SME companies is that they are specialized producers of dairy products. Usually they tend to have few knowledge workers and knowledge is concentrated in few but very committed people, quite often including the owner of a company. The setting of the project in which companies from several European countries are participating and interacting may have resulted in a steeper learning curve. All companies can learn from their peers. The dairy sector is facing increased interest from food safety regulators and increased pressure from the market to produce more efficiently. More knowledge is required and the use of easily accessible web-based technology, packaged as a user friendly software package opens up possibilities for SMEs to accelerate their level of knowledge in a rapidly changing world.
Usage of the web-application is expected to yield savings for the dairies and environment, estimates are:
- Reduction of processing costs by 30% compared to current processing costs. This will be achieved by decreased fouling, decreased energy consumption, less water usage and less product waste.
- Reduction of product waste by 30% compared to current product waste. An optimized heating process and the application of models will give the SMEs the guarantee of optimal product quality and safety with respect to the inactivation of bacteria.
- The application of these models will guarantee the SMEs more constant product quality with respect to taste, structure and health. If desired, these models will also give the SMEs the possibility to change the product quality (different taste, different texture, different nutrition).
- Fast and accurate response towards new European or national food safety regulations and towards outbreaks of epidemics. The aim is that SMEs will be able to adjust the heat treatment processes accurately while maintaining similar product quality within. With the modelling tool the SMEs will be able to do this within a few days.
- The application of these models will give the SMEs the possibility to enhance new product development. Heat treatment is an important parameter for the development of new products. With these models first the results of the heat treatment can be predicted and then validation experiments are required. Thus fewer trial and error experiments are needed and the time to market for new products is significantly decreased from several months to approximately one month.
Table 1. Participating companies
|Participant name |Country |
|Aurora |Netherlands |
|Bettinehoeve |Netherlands |
|DewLay |UK |
|Hekking |Netherlands |
|De Jong |Netherlands |
|Katshaar |Netherlands |
|Gordon Prod |Romania |
|Farmer House Products |Netherlands |
|Capra |Belgium |
|Vermeersch |Belgium |
|Vitalac |Belgium |
|Ste Marie |Belgium |
|Roussas |Greece |
|Trevigiane |Italy |
|Klaver Kaas |Netherlands |
|Van Dijk Kaasmakerij |Netherlands |
|NIZO food research, RTD |Netherlands |
|Wirelessinfo, RTD |Czech Republic |
2 International state-of-the-art
The production of high-quality guaranteed safe foods has become more and more important. The challenge is how to predict and to guarantee the product properties based on specifications of the raw material for different types of processes. Therefore, mathematical models that predict product properties could greatly benefit the food industry.
However, in general, three types of obstacles for full industrial use of models are recognised:
1. The extensive effort needed for model development. Development of white box models is very time-consuming and black box models have very limited predictive capabilities.
2. Many models are focused on specific unit-operations; the impact on the complete production chain is ignored.
3. Many models are focused on either particular food quality aspects or on production costs, while the industry wants to compare both quality and costs.
For the food industry, various mathematical models were developed that describe aspects of product quality or process efficiency (for example microbial growth and inactivation, formation of taste components and fouling of heating equipment). Typically these predictive models only describe one single aspect.
References can be found in Food Science and Technology Abstracts (FSTA), at the Cordis website and internet searches. A recent (December 2007) search on the internet resulted in a large number of hits for the keywords “development of kinetic dairy models”. Most hits were related to specialized single issue research projects. No other integrated models embedded in a user friendly internet application could be found.
One of the main bottlenecks for the implementation of predictive models is the lack of sufficient kinetic data. For most models many expensive experiments are required for obtaining kinetic data. In order to enhance the experimental part of the product development trajectory, a new technology will be used: miniature processing on micro scale. This technology is beyond state-of-the-art in the industry. A number of experiments to validate the model (specifically in relation to kinetic data parameters for whey and milk stemming from different species: cow and goat) have been carried out using micro technology.
The use of micro technology has a high potential for application in process and product development. The miniaturization of processing units enables the determination of the kinetics of food components in a very effective way.
It is expected that the use of new technologies as mentioned above will decrease the costs of development in such a way that more new food product can be introduced on the market.
The advantages of using the micro heater are:
▪ Small quantities of milk required for experiments (< 1 kg);
▪ Quick scan of processing conditions (> 10 scans per hour);
▪ Easy to handle, no special room;
▪ In the future it can be operated by SMEs.
The SMEs are able to use and update the models via the Internet, which is beyond the state-of-the-art. Manuals have been written in a number of languages so the SMEs have access to the web-tool in a number of languages thus ensuring ease of use. The resulting web-application can be applied in all dairy companies that process raw milk all over Europe and even world-wide. These models give SMEs the access to similar technology that previously was only available to the dairy giants with specialised research departments.
2 Summarise the objectives
Work package 1:
In work package 1 the relevant processes, raw materials and end products at the dairy companies have been identified. Each dairy company has identified one important raw material, one important end product, and one important heating step. Relevant data of the raw materials, end products and heating process have been collected. An inventory has been made of all relevant technical processing and product data. Experiments have been carried out both in the consortium members’ production environment and in the laboratories of NIZO food research to collect experimental data which has been used for customization and calibration of the existing models. Finally, NIZO food research and the participants have established procedures on how to collect relevant data which have been used for validation purposes in the follow up step.
Summarising, the specific objectives of work package 1 are:
1. Selection of process-product combinations and collection of technical processing data and product data.
2. Collection of experimental data required for customisation and calibration of the available predictive models
3. Collection of data to validate of the customised/calibrated predictive models.
Milestones of work package 1:
• Month 9: All data required for customising and calibrating the models will be available, which will be done in work package 2.
• Month 14: At the end of this work package all required data, including validation data, are collected. The validation data will be used in work package 2 to validate the customised/calibrated models. The data will be stored in the Web database structure which will be developed in work package 3.
Work package 2:
The specific objective of this work package was to produce and evaluate a first prototype of the predictive models. First, data produced in work package 1 have been used to customise and calibrate the available models. Based on the customised/calibrated models a first off-line prototype of the model has been developed. The prototype has been evaluated by the dairy companies and has served as the base for the final WebSim-MILQ application developed in work package 3. The comments of the dairy companies on the first prototype have been gathered and reported. Required adjustments based on these comments have been taken into account when building the Web enabled version in work package 3. Using the experimental validation data from work package 1 NIZO food research has also validated the use of the models. The validated models were used to optimise the heat treatment processes of the SMEs.
Milestones work package 2:
• Month 12: The first off-line prototype of the model based on the customised/calibrated models available and ready to be evaluated by the SMEs.
• Month 18: Predictive models validated for the SMEs and each SME knows how to use the models. For each SME the selected heating process has been optimised with respect to product quality and fouling. All SMEs can run their production with lower costs, whereas product quality and safety are the same. Web version of the model has been completed. (work package 3).
Work package 3:
In work package 3 Wirelessinfo has developed a website and hosting facilities for this project. An unsecured site will contain general information about the project. In addition, Wirelessinfo has developed a secure Web portal on which the Web application is available for the participants (http:// websim.). Each participant has its own secured environment on the Internet site thus ensuring confidentiality of the data. A secure Web database structure has been developed for data storage purposes. A proposal for future maintenance has been prepared.
Milestones work package 3:
• Month 7: Hosting of the Web page available and facilitated during the rest of the project.
• Month 24: End version predictive models available on a secure and safe internet site.
Work package 4:
In work package 4 knowledge has been transferred to the users and the SMEs have been trained to use the Web based application. A user manual has been prepared, translated into a number of languages for user convenience. A protocol for help-desk facilities has been set up and a proposal for maintaining help-desk facilities after the project has been prepared. For the training sessions Web based educational tools will be used for the trainings. The latter in the form of a video introduction which can be found on the websim. site.
Milestones work package 4:
Month 27: At the end of this work package the consortium partners have access to their specifically custom built process on the internet. All SMEs are capable of working with the Internet application and a manual is available on how to use this application on the Web.
Work package 5:
A separate work package (work package 5) is dedicated to consortium management activities, also covering activities related to exploitation and dissemination. This work package is described in detail in chapter 5.
3 Problems and corrective action
With respect to the planning some delays occurred within the first year of the project because visits could not be arranged with some consortium partners. In addition, we have had to deal with some organizational aspects relating to the consortium. Some organizations that were included in the original proposal failed to accede to the contract when it was awarded in 2005. Some replacements have taken place during the first year of the project. Visits with the companies Capra (B), Dew Lay (UK), and Gordon Prod (RO) have resulted in some timing issues.
Accurate analysis of whey protein denaturation in both goat and cow milk was found very important for yield estimation of cheese. Therefore, it was decided to perform additional heating experiments and subsequent analyses of the fraction of native whey proteins in raw and pasteurized goat and cow milk. With these experimental data the kinetic models of WebSim-MILQ were validated.
Training activities, adjustments to the software and setting up the e-learning tool for the project and reporting resulted in activities up until December 2007.
Work packages
This section details the progress per work package during the period of reporting
1 Progress towards objectives WORK PACKAGE 1: Identification of products, processes, soft- and hardware requirements.
Work package manager: A. Braber (NIZO food research)
|Work package number |1 |Start date or starting event: |Month 0 |
|Participant Short Name |Each SME* |NIZO | |Total |
|Person-months per participant: |4 (total: 16*4 = 64) |13 | |77 |
* Person-months are indicated as an average for each SME. In all work packages the participating SMEs perform approximately the same tasks.
|Objectives – starting point |
|The main objective of this work package is collection of all data required for customisation of the predictive models. This work package |
|is subdivided into three tasks. The objectives of these three tasks are: |
|Selection of process-product combinations and collection of technical processing data and product data. These data are of prime importance|
|for the development of the experimental plans in task 1.2 and the development of the prototype (as described in work package 2). |
|Collection of experimental data required for customisation and calibration of the available predictive models. |
|Collection of data to validate of the customised/calibrated predictive models. |
1 Task 1.1 – Collection of processing data and product data.
Each SME has selected one process and one product and relevant data have been collected. This resulted in the selection of processes and products to be optimized.
Collection of processing data.
All relevant data of the heating equipment, such as dimensions of design, conditions applied, and in- and off-line measurements including the following processing parameters have been determined for each SME:
– Configuration of equipment;
– Absence of leaks;
– Safety equipment;
– Position of valves and pumps;
– Design of equipment;
– Position of the temperature sensor and safety equipment sensors;
– Accuracy of the temperature sensor and registration equipment;
– Sensitivity of the temperature sensor and registration equipment;
– Average duration time and variation with minimum and maximum capacity.
During visits to the SMEs, data were collected about process equipment and product samples were taken for microbial and chemical analysis. The process and product data of the SMEs are summarized in a work sheet (deliverable 1), in addition specific processing schemes have been construed by the SME to allow for proper process modelling. The data have been used to customize and calibrate the underlying mathematical models to be used for the final project result i.e. the web-application.
Collection of product data.
SME’s have provided all available product information and results of various analyses throughout the process. SME’s have provided the end product specification and information about local legislation. A summary of product data has been presented in Table 2 below.
Table 2 Selected processes at participating SME’s
|Company |Milktype |Product |Flow |Past |Past |Pasteurizer type |
| | | | |Temp |Time | |
| | | |L/h |C |S | |
|Bettinehoeve |goat milk |Soft goat |12600 |73 |18,9 |Schmidt-Bretten SIGMA 27 TBN |
| | |Cheese | | | | |
|Hekking |goat milk |Goat cheese |4000 |73 |28,1 |Alfa Laval Phe CLIP 6-RM |
| | |Hard | | | | |
|Van Dijk |goat milk |Goat cheese |6900 |73 |34,3 |APV Phe N35 RKS 10/9 |
| | |Hard | | | | |
|Klaverkaas |goat milk |Goat cheese hard |6000 |73,8 |20,3 |Alfa Laval Phe M6-MGBase |
|St Marie |cow milk |Italian type hard cheese |11000 |72 |42,5 |Alfa Laval Phe P14-RB |
|Trevigiane |cow milk |half hard cheese |25000 |72 |17,6 |Alfa Laval H10-RC |
|Roussas |sheep milk |Feta |7000 |71 |22,5 |Schmidt-Bretten Sigma 27 TBN |
|Aurora |cow milk |Hard cheese |5000 |77 |18,4 |Schmidt BRD/NL Sigma 27 |
|Vermeersch |cow milk |Fresh Cream |5000 |115 |8,2 |APV Phe N35 RKS |
|Dew Lay |cow milk |Creamy Lancashire cheese |15000 |72 |28,6 |Alfa Laval C6-SR |
|Katshaar |cow milk |Yoghurt |20000 |93 |300 |APV Phe N35 RKS 10/9 |
|Vitalac |cow milk |Chocolat milk |15000 |85 |28,3 |Alfa Laval H10-RC |
|Gordon Prod |cow milk |Cascaval rucor |6500 |72-77 |46 |Alfa Laval M6-Mbase |
|Capra |goat milk |Soft goat cheese |10000 |76 |16,4 |Schmidt-Bretten SIGMA 26 SAN |
|De Jong |goat milk |Soft goat cheese |12000 |74 |20 |Alfa-Laval H7RC |
|Farmer House |buffalo milk |Mozarella type |1320 |72 |22 |Alfa-Laval P5-RB 2230-275 |
|Products | | | | | | |
Descriptive
The products are ranging from hard cheese associated with relatively short fermentation processes to soft cheese with a longer fermentation. Also milk sterilization, yoghurt production and cream processes have been used to gather data from. Generally, three producers of pasteurizing equipment have been implemented in the participating sixteen dairies: the well-known brands are: APV, Alfa-Laval and Schmidt-Bretten. The capacities vary from 1320 – 25000 L per hour. Cow milk is the most used milk type (8 processes), goat milk (6 processes), one sheep milk and one buffalo milk process make up for the rest. Holder residence time ranged from 8 seconds to 300 seconds. Excluding extreme values, the average was 25 seconds. This time denotes the number of seconds that milk is kept at pasteurization temperature. Pasteurization temperatures ranged from 71 to 115 degrees Celsius depending on the process. It can be concluded that within the participating SME’s a variety of product processes and types of milk are available to develop the tool.
2 Task 1.2 – Collection of experimental data
The second objective is the collection of experimental data. NIZO food research has performed scanning experiments to identify critical points if required. In experiments the configuration of the heating process of each SME has been simulated. During experimental runs processing and product data have been collected.
• Processing data: the exact processing conditions (flow and temperature) have been determined as a function of the run time.
• The following parameters of raw materials and/or end products are relevant to tune the model and have been collected in the field:
– Phosphatase level in the milk under different capacities, before and after pasteurisation;
– Native whey protein content under different capacities, before and after pasteurisation;
– Fat content, protein content, density and pH of the raw milk;
– Pasteurised milk: fat and protein content, density, pH and microbial quality control;
– Composition of the end product (pH, dry matter, fat, protein).
With the available experimental data and the experience of NIZO food research, good insight could be obtained into the critical points of the processes of the SMEs.
Accurate analysis of whey protein in especially goat milk appeared important for cheese yield estimation. Therefore, it was decided to perform additional analytical experiments and analyses to determine and validate the fraction of native whey proteins in raw and pasteurized goat and cow milk. The experiments were focussed on the more in depth analysis of the whey protein fractions in milk. The data were used for calibration of the kinetic predictive models.
It is important to know the exact amount of whey protein in both raw and pasteurized milk in order to calculate the degree of denaturation of the whey proteins during the pasteurization process. This information is critical for calibration and optimization of the pasteurization process and determines the cheese yield (Task 2.1).
The analytical tests were carried out with product samples obtained from SMEs. Additional sampling was carried out at three SMEs (Bettinehoeve, St. Marie and Hekking). This was done to validate and confirm the information as obtained in task 1.1. Results were integrated in the work sheet that was set-up for task 1.1.
3 Task 1.2 – Collection of data to validate the customised/calibrated predictive models
In the Craft MILQ-QC-TOOL project numerous cheese milk pasteurisation processes were sampled and modelled with NIZO Premia Qsim. It was observed that predicted degree of whey protein denaturation and measured degree of whey protein denaturation did not always agree.
During the process of data collection with the consortium members a number of issues arose. Several reasons were identified that could explain the difference between the predicted and measured degree of protein denaturation:
1. The actual pasteurization temperature deviates because of technical problems, for example a failing temperature sensor.
2. Modelling errors for example the equipment configuration provided did not coincide with the actual configuration of the pasteurizer.
3. Data errors, for example actual flow data deviated from the provided flow data.
4. Lower effective pasteurization temperature due to lack of isolation of holder tube.
5. Addition of ingredients to the raw milk (e.g. leftovers of pasteurized milk, starter).
6. Leaking heat exchanger plates (check microbial inactivation).
7. If sampling is done directly after start up of pasteurizer, effective pasteurization temperature may be lower in practice. This can be due to incorrect starting procedure.
8. Sometimes the pasteurized milk is lead through a flash vessel. During this step the milk is concentrated, which affects the concentration of whey proteins.
However, even after checking the previous points and/or described with NIZO Premia Qsim, differences between predicted and measured protein denaturation remained. There are two important reasons for this:
1. The sample preparation method applied for the measurement of the native whey proteins. This method should be the same for the measurements and the original data on which the denaturation kinetics is based.
2. The standard deviation that is valid for the analysis method. The standard deviation for the calculated degree of denaturation can be obtained from the standard deviation of the native whey protein concentration analysis.
Sample preparation method
There are several ways to prepare the raw or pasteurised milk prior to HPLC analysis. The methods that can be applied:
• COKZ, (the appointed agent by the Dutch government for controlling dairy quality) applies rennet to the milk and subsequent HPLC analysis of the native whey protein in the whey. Reference material used is Nilac powder.
• NIZO applies an acid preparation method (PH=4.6). The native whey protein in the supernatant is determined with HPLC. Reference material used is purified whey protein.
The detected native whey protein concentrations differ between the two methods. Depending on the type of whey protein and the exact composition of the sample treated the difference between the two methods will increase.
When predicting whey protein denaturation you should be aware 1) which analysis method is applied to obtain the measured whey protein concentrations and 2) which analysis method is used for obtaining the kinetic model available in NIZO Premia.
Standard deviation of degree of denaturation
The degree of whey protein denaturation is calculated as follows:
[pic]
A reasonable standard deviation would be about 3% for the measured concentrations. Note that this standard deviation is exemplary and is dependent on the analysis method used. The analysis error has the following impact on the final calculated degree of denaturation (see Table 3). It can be concluded from this table that the error for the protein denaturation of the individual proteins is higher compared to that for the total degree of protein denaturation.
Table 3. Concentrations of specific proteins in milk
|Protein |Concentration |Concentration |Degree of denaturation |
| |Raw milk (g/l) |Past milk (g/l) | |
|(-lactalbumin |1.46(0.04 |1.38(0.04 |5.3%(4.0% |
|(-lactoglobulin |2.88(0.09 |2.68(0.08 |7.2%(3.9% |
|BSA |0.28(0.01 |0.22(0.01 |21.3%(3.3% |
|Immuneglobulin |0.61(0.02 |0.41(0.01 |32.6%(2.9% |
|Total |5.24(0.06 |4.69(0.06 |10%(1.5% |
From these calculations it can be concluded that a deviation of 1.5% in the degree of denaturation is inevitable due to the standard analysis error. Therefore, if WebSim-MILQ predicts for example 11.4% whey protein denaturation, there is no significant difference between predicted and measured degree of protein denaturation.
Protein denaturation Kinetics
Please find below the kinetic data that have been determined for cow and goat milk during cheese milk pasteurisation combined with protein analysis by COKZ. The data are valid for pasteurization between temperatures of 65 and 80 oC. The experiments have been carried out on the FLIP equipment of NIZO food research. The complete time-temperature profile was taken into account with NIZO Premia Qsim, which is the engine for WebSim-MILQ to determine the kinetics below (Table 4).
Table 4. Protein denaturation kinetics
|GOAT | |(-lactoglobulin |(-lactalbumin |Immuneglobulin |BSA |
| |Lnko (-) |82.3 |18.5 |67.5 |22.1 |
| |Ea (J/mol) |258023 |77971 |207606 |78346 |
| |n |1.5 |1.0 |1.0 |1.0 |
|COW | | | | | |
| |lnko |57.5 |17.0 |78.5 |23.4 |
| |Ea |186904 |70326 |241084 |81187 |
| |n |1.5 |1.0 |1.0 |1.0 |
In the two figures below find a comparison between predicted and measured degree of total whey protein denaturation for three holding times as a function of pasteurization temperature. It is emphasized that the prediction of whey protein denaturation is more accurate for cow milk (Figure 2) than for goat milk (Figure 1).
Figure 1:
[pic]
Figure 2:
[pic]
Protein denaturation Kinetics Extended FOR UHT Range
Please find below the kinetic data that have been determined for cow milk during heating of milk combined with protein analysis by COKZ. The data are valid for heating between temperatures of 65 and 150 oC. The experiments have been carried out on the FLIP and microheater (90-150 oC) equipment of NIZO food research. The complete time-temperature profile was taken into account with NIZO Premia Qsim to determine the kinetics below (Table 5).
Table 5: Protein denaturation kinetics UHT range
|COW | |(-lactoglobulin | |(-lactalbumin |Immuneglobulin |BSA |
| |Upper T (oC) |93.7 | | |Idem before | |
| |lnko |45.1 |12.3 |16.9 |78.5 |18.6 |
| |Ea |150052 |49954 |69368 |241084 |67328 |
| |N |1.5 | |1.0 |1.0 |1.0 |
In the figure below (figure 3) find a comparison between predicted and measured degree of total whey protein denaturation for three holding times as a function of pasteurization temperature.
Figure 3.
[pic]
Conclusion
This investigation gives some support when comparing predicted and measured degree of whey protein denaturation. Causes of deviations are summarized and two are highlighted.
Attention has been paid to the importance of applied analysis method for setting-up kinetic data available in the NIZO Premia engine for WebSim-MILQ and applied analysis method used in the project.
Attention has been paid to the impact of analysis error on the total degree of whey protein denaturation. Small differences between predicted and measured degree of denaturation can be explained by the standard analysis error. In an example it was calculated that the degree of whey protein denaturation contributed 10.4(1.5%.
Finally, new kinetic data are provided to predict the effect of pasteurization (65-85 oC) on whey protein denaturation in goat milk and for heating of cow milk (65-150 oC). Analyses were carried out by COKZ Netherlands.
4 Deviations from the project work program and corrective actions
The SMEs Capra NV and Dew Lay have been visited in the autumn of 2006. Gordon Prod has been visited in February 2007 and all appropriate data collection has been completed. Additional visits to several SME’s were necessary to obtain explainable results for use in the model application. This resulted in some delay for the development of the web application (further info under work packages Wirelessinfo). Sample collection for validation ran through from January until August 2007.
Extensive additional work on the whey protein denaturation has been conducted in the period between January and August 2007, the results have been described above in the appropriate section.
5 Deliverables
|Deliverables |
|D1. Work sheet with process and product data of all SMEs (task 1.1), month 3 |
|D2. Work sheet with results of experiments (task 1.2), month 9 |
|D3. Work sheet with validation data (task 1.3), month 14 |
Deliverable D1 is a worksheet that contains the selected product and processes for each SME. It also contains some key data regarding the pasteurizing equipment. Based on this data and further company specific technical documentation NIZO food research is able to model the heat treatment processes. D1 is annexed to this report and separately loaded onto CIRCA in the deliverables section.
Deliverable D2 is a worksheet that contains for each SME the company specific microbiological and product composition analyses results required to model the heat treatment process chosen by the specific SME.
Deliverable D3 are a number of confidential letters to the participating SME’s with observations on the validation of the model. Separate from product and process optimization samples, additional samples have been sent in by the SMEs to NIZO food research after changing the process parameter settings on the pasteurizers for the chosen product/process combination. The process parameters have been changed based upon the calculations with the models and optimized in the direction that each SME has specified (i.e maximize yield, maximize runtime, etc.). D3 is annexed to the report per SME and separately loaded on to CIRCA in the deliverables section. In addition the report on the work done with the micro-heater to validate whey protein denaturation has also been uploaded as a separate document in the D3 section of the deliverables.
These data are highly confidential. Within the consortium the participants are using the same model and general knowledge to optimise their company specific processes. The exact settings and outcomes for selected processes are not shared information. The internet tool has a password protected area that is only accessible for the owner of the process data.
|Del. |Deliverable name |WP no. |Date due |Actual delivery |person-months |Lead Contractor |
|no. | | |(project |date | | |
| | | |month) | | | |
|D1 |Work sheet with process and product |1 |3 |15/12/07 |15 |NIZO |
| |data | | | | | |
|D2 |Work sheet with experimental data |1 |9 |15/12/07 |39 |NIZO |
|D3 |Work sheet with validation data |1 |14 |15/12/07 |23 |NIZO |
3.1.6 Milestones
The milestones have been achieved as summarized in the table below.
|Milestone no. |Milestone name |WP no. |Date due |Actual delivery date |Lead Contractor |
|Month 9 |Month 9: After task 1.1 and 1.2. all data required |1 |01/09/06 |01/10/06 |NIZO |
| |for customising and calibrating the models will be | | | | |
| |available, which will be done in work package 2. | | | | |
|Month 14 |Month 14: At the end of this work package all |1 |01/02/07 |01/10/07 |NIZO |
| |required data, including validation data, are | | | | |
| |collected. The validation data will be used in work | | | | |
| |package 2 to validate the customised/calibrated | | | | |
| |models. The data will be stored in the Web database | | | | |
| |structure which will be developed in work package 3 | | | | |
| |(task 3.2 | | | | |
2 Progress towards objectives WORK PACKAGE 2: Development of the first prototype
Work package manager: M. Schutyser/M. Vissers (NIZO food research)
|Work package number |2 |Start date or starting event: |Month 8 |
|Participant Short Name |Each SME |NIZO | |Total |
|Person-months per participant: |3 (total: 16*3 = 48) |11 | |59 |
|Objective |
|The objective of this work package is to produce and evaluate a first prototype of the predictive models. Therefore, first the predictive |
|models have to be customised for use by SMEs. Next, SMEs will test the first prototype and will use it to optimise the selected heat |
|treatment. This first prototype will not be available on the Internet, but is an off-line version. The Web application to be developed in |
|work package 3 will be based on this prototype. |
1 Task 2.1 – Customisation and validation of the predictive models
In this work package NIZO food research has customized, calibrated and validated the models for use by SMEs. Customizing/calibrating predictive models means changing the model parameters and applying small changes to the mathematical model relations based on the data and equipment settings of the SMEs. In order to customise these existing models for use by SMEs the experimental data had to be translated into a format that can be understood by the model.
For each SME a first prototype model has been customised and calibrated (D4). This means that the data as obtained in tasks 1.1 and 1.2 have been used to set-up a model description of the pasteurization process for each SME.
General optimization steps
The main reasons for pasteurization of cheese milk are inactivation of micro-organisms (e.g. Pseudomonas spp.) and enzymes such as milk lipase and phosphatase. Besides microbial and enzyme inactivation, cheese yield and cheese quality are also affected.
In this framework, the focus is especially on the denaturation of whey proteins. It is the irreversible change of the native structure of a protein. Protein denaturation is mainly caused by heating. The denatured whey proteins are partly bound to the casein micelles in the milk. Therefore, with respect to the cheese process, the cheese yield increases, because the denaturated whey protein is included in the casein matrix (curd).
However, a high level of denaturated protein can affect the taste of the cheese and result in problems by severe fouling of the equipment. Therefore, it is important to aim for an optimum with high cheese yield, without the loss of taste of the cheese and no problems with fouling. With the modeling software NIZO Premia Qsim the processes are simulated and optimized. The same software (set of equations) is implemented at the heart of the web application.
An increase in the degree of denaturation of whey proteins can also affect the coagulation process. This effect can be compensated by small adaptations in the subsequent cheese processing. Possible measures are the addition of more calcium chloride and/or increase of scalding temperature.
Important aspects for optimization
The aspects that play a role in the optimization of milk pasteurization are described below:
Denaturation of whey proteins (β-lactoglobulin, α-lactalbumin, immunoglobulin and bovine serum albumin (BSA)). A higher level of denaturation results in increased cheese yield. However, if it is too high, taste can be affected and severe fouling of the pasteurizer may occur in the case of long run-times (>6 hours), especially when pasteurization temperatures above 78C are applied.
The calculated level of denaturation of the whey proteins is based on literature data on bovine milk.
Inactivation of the enzymes phosphatase and xanthine oxidase. Pasteurized cheese milk should be phosphatase negative and xanthine oxidase positive. Negative means that >90% of the enzyme is inactivated in the pasteurized milk. Positive means that more than 10% of the original enzyme activity remains after pasteurization.
Psychrotrophic micro-organisms (such as Pseudomonas spp.) can produce heat-resistant enzymes at low temperatures (105 cells per ml milk) can cause deviations in taste and structure of the cheese.
To estimate the risk of biofouling, four categories are defined. The number of incoming and outgoing Streptococci after 6 hours runtime are compared to quantify the risk. Four categories are distinguished: Negligible (Nout < 10-3*Nin); Possible (Nout > 10-3*Nin but Nout < Nin); Critical (Nout > 10-3*Nin but Nout < 1000*Nin); Severe (Nout > 1000*Nin).
Optimization of the pasteurization temperature and the holder tube volume
The cheese yield increases with the increasing level of whey protein denaturation. Note that a very high level of denaturation (>20%) is undesired as it adversely affects the coagulation process. An increased level of whey protein denaturation can be achieved by increasing the pasteurization temperature and/or the residence time of the milk in the holder tube. The residence time increases with increasing volume of the holder tube, if the flow is constant.
An advantage of a higher pasteurization temperature is the higher inactivation rate of micro-organisms, especially TRS. As taste of the final product is also related to the level of denaturation there is a maximum to the combination of temperature and residence time in the holder. Therefore, it could be interesting to increase the pasteurization temperature and reduce the volume of the holder tube. At higher temperature micro-organisms are more effectively inactivated, while the level of denaturation can be kept constant by reduction of the residence time. In this study optima have been calculated and validated for the various processes. The results have been presented for each of the participants (D6).
2 Task 2.2 – Evaluation of the first prototype
Below you find an illustration of the prototype model.
Figure 4. Prototype model
[pic]
Basically, a process line is built from a number of components that are available from a library. Flows and heating steps are described as input and the model starts calculating using the kinetic data for a number of models. Output is in the form of tables and graphs.
Developmental works were running in several periods. New versions of developed application have been published on the server after each test and were then made available for further evaluations and suggestions to the consortium partners. After each testing, NIZO sent a list of revisions and requirements for making change and completion of the application to WIRELESSINFO developers. These requirements were included into next development and were attended in the further developmental application.
3 Deviations from the project work program and corrective actions
Wirelessinfo started working on the work packages in January 2006 after the kick-off meeting of the consortium and estimated that the workload would be until the end of 2007 taking into account resource and activity planning. Some planning issues resulted in parallel running of tasks for different consortium members and had some time effect on the timing of final outcomes for optimization and validation results. However, the development of the on-line web application was not greatly delayed. This has resulted in a delay of three months until end of 2007 to finalize all tasks. The web application proto-type became available in August 2006, the first on-line version in December 2006 and beta-testing by selected participants took place in January 2007. Further testing took place in June 2007 during a participants’ workshop conducted at NIZO food research and on site at the diverse SME’s.
|Deliverables |
|D4. First prototype of the model based on the customised/calibrated models, month 12 |
|D5. Evaluation report of the first prototype, month 18 |
|D6. Report with results of optimised heat treatment, month 18 |
4 Deliverables
Based on the result from experiments that have been carried out with thirteen out of sixteen participants the prototype of the model has been customised an calibrated. During the technical meeting of 1-2 August a case study modelled with the prototype was presented. In December 2006 the first prototype was available and this has been tested by a three SME’s in January 2007. Below you may find a screen shot from the prototype model.
|Del. |Deliverable name |WP no. |Date due |Actual delivery |Person-months |Lead Contractor |
|no. | | |(project |date | | |
| | | |month) | | | |
|D4 |Customised models – first prototype |2 |12 |15-12-07 |29 |NIZO |
|D5 |Evaluation of comments SMEs on first |2 |18 |15-12-07 |6 |NIZO |
| |prototype | | | | | |
|D6 |Report with results of optimised heat |2 |18 |15-12-07 |24 |NIZO |
| |treatment | | | | | |
In CIRCA we have uploaded a more detailed presentation about the set up of the prototype model (D4). This is Deliverable D4. More detailed information can be obtained from NIZO food research on request.
5 Milestones
The application is available on internet and validated. At month 12 it was not yet ready for evaluation by the SME’s since not all selected processes had been calibrated yet.
|Milestone no. |Milestone name |WP no. |Date due |Actual/Forecast |Lead Contractor |
| | | | |delivery date | |
|Month 12 |Month 12: The first off-line prototype of the model |2 |01/09/06 |01/12/06 |NIZO |
| |based on the customised/calibrated models will be | | | | |
| |available and ready to be evaluated by the SMEs. This| | | | |
| |prototype will also be used as a basis for building | | | | |
| |the Web enables version of the model (work package 3,| | | | |
| |task 3.3). | | | | |
|Month 18 |Month 18: At the end of this workpackage the |2 |01/06/07 |1/9/07 |NIZO |
| |predictive models will also be validated for the SMEs| | | | |
| |and each SME will know how to use the models. For | | | | |
| |each SME the selected heating process has been | | | | |
| |optimised with respect to product quality and | | | | |
| |fouling. This means that from this stage all SMEs can| | | | |
| |run their production with lower costs, whereas | | | | |
| |product quality and safety are the same. Furthermore,| | | | |
| |the Web enables version of the model can now be | | | | |
| |completed (workpackage 3). | | | | |
3 Progress towards objectives WORK PACKAGE 3: Development and hosting of Internet application
Work package manager: P. Gnip (Wirelessinfo)
|Work package number |3 |Start date or starting event: |Month 3 |
|Participant Short Name |Each SME |NIZO |Wirelessinfo |Total |
|Person-months per participant: | |1 |15 |16 |
|Objective |
|Design and implementation of project portal for data storage. |
|Developing a uniform simulation environment as Web application on the Internet. |
|Prepare for future maintenance of system. |
|Hosting website and application |
The main goal of work package 3 was the development of a web application on the basis of current NIZO food research prototype software. This work package has been managed by Wirelessinfo and all tasks have been carried out in close cooperation with NIZO food research.
1 Task 3.1 – Development of a secure Web page
Wirelessinfo has designed the Web pages for the project (). Wirelessinfo is also responsible for hosting the website on a server and maintenance. The webpage consists of an open part (public part) and a secure part (private part).
The open part is available to everyone and contains information about the project and participants. The secure part of the Internet page will be available only to the participants of the project and will contain the predictive models, simulated processing line and process parameters.
The webpage has been up and running on the Wireless Server since May 2006. A secure website and server services have been established during this period based on a Microsoft platform with the use of XML language.
Each SME participant has access only to its own secure area. A part of the members-only secure area is open to all participants and will also be used to transfer general information between the partners in the consortium.
2 Task 3.2 – Development of a Web database structure
In this task Wirelessinfo has created the possibility to store the simulation data in a database on the Web. The structure will be based on Open source solutions to minimise costs of implementation and future maintenance. Equipment design, processing conditions and product specialities can be saved securely in this database.
Data Model
A conception of the data model starts from the assumption that the main functionality of system will be supported by a data library which has been developed by NIZO as a part of the desktop predictive model system Premia. This data library supports all basic computer and analytical functions of the web application. The operation system Window 2003 Server and MS SQL2005 has been chosen in view of a necessity to include this library into a system on the server site.
Characteristics
• Storing of the models and simulation data in a database on the Web
• Closely linked to Task 3.3 – it depends on structure of simulation environment
• MS-SQL database
Developing services are concentrated into two main areas:
- a development of web interface Application
- a development of wrapper which will be able to provide communication with the library Qsim03.dll
In the figure below you will find a graphical interpretation of the interface that allows access and manages communication to the data core provided by the software models Nizo Premia.
Figure5:[pic]
Figure: WebSim development scheme
Four basic components are involved in data model:
- organisation
- user
- model
- variable quantities
Each of components and their mutual relations are demonstrated in the following model:
[pic]
Figure 6: Data Model
3 Task 3.3 – Development of the basic simulation environment
A first concept proposal for the structure of web application was defined in August 2006. The first prototype for the model (based on the customised/calibrated models) developed in work package 2 has been overhauled and transformed by Wirelessinfo into the form of a Web simulation application.
Wirelessinfo and NIZO food research have tested the models on the Web. In a later stage the validated model has been incorporated and required adjustments based on the comments of the SMEs in work package 2 have been implemented.
Over time a number of testing and checking operations have been carried out according to the summary below:
- design of the WebSim application including internal testing between NIZO food research and Wirelessinfo – August 2006
- the first version on the web – October 2006
- the second version on the web – December 2006
- the third version - application of suggestions user test 3 SME – March 2007
- the fourth version for testing by all SMEs – June 2007
- Final version – August 2007 with additional upgrades until December
The main evaluation facts from a user point of view were the following:
- The menu structure is very clear and easily accessible. Some technical problems were identified relating to the save function. These have since been solved. Simultaneous use of multiple accounts also caused some problems at the time.
- Modeling processes on the application: The user interface is very clear and allows for accurate modeling of the real-life processes. Specific parts have been improved based on comments from the users: in the edit section warnings have been added that in case you close the session or hit without saving your work is not lost immediately.
- More explanation and time is needed to explore all the different components that are available in the modelling library. Most SME users only had affinity with their own exact production situation when testing the model.
- Graphical representation: Issues on scaling were revealed and remedial measures have been taken
- Tabling results: Data export function was not yet functional at the time of prototype testing. Also there were some comments on readability and possibilities for adding own descriptive text to the headings. These issues have also been addressed.
The conclusion was that the application is very useful for the SMEs because one can adapt process settings (e.g. pasteurization temperature) and determine influence of these changes on the degree of whey protein denaturation (i.e. yield) without field process intervention. This sensitivity analysis may help taking decisions about optimization in the field. Participants also feel that their insight in the process has increased because of the graphical representation of the chosen production process
4 Task 3.4 – Hosting of the Web application
Wirelessinfo has set-up the ICT infrastructure for hosting of the internet site, both for a private and public part. For the duration of the project, Wirelessinfo will ensure a professional hosting environment. Professional hosting includes technical support, administration, user management, and security management.
NIZO and Wirelessinfo will provide maintenance to users also in the future to ensure trouble-free running and easy usage of the application. This maintenance includes regular service of the system and helpdesk.
Future maintenance will cover:
i. operation maintenance (server, Internet connectivity, security)
ii. control and service of the Internet application
iii. technical support for NIZO in limited rangecontinuous publication of changes and formats
Maintenance of server operation
Wirelessinfo will ensure that professional hosting will take place. The application is placed on server with access to a central network with high connectivity. The access to the application is secured for users by allotted name and password. Wirelessinfo will carry on regular controls and service of basic hardware and software for the server.
Control and maintenance of Internet application
Maintenance of the WebSim application will be a primary service within maintenance. Maintenance includes solution of possible problems connected with ordinary running of application and correction of recognized mistakes
Technical user support
Wirelessinfo will provide assistance to NIZO food research (and thereby indirectly to the SMEs) in the use of the Internet Application Software. Technical support services are defined as:
i. solving any questions with regard to user management administrative issues;
ii. technical support
iii. security management.
The communication should be provided by telephone or e-mail. Contact persons will be provided by NIZO food research shall. Also Wirelessinfo will appoint a person responsible for solving technical issues and bugs. NIZO food research remains responsible for the NIZO premia software and should provide Wirelessinfo with necessary updates of NIZO Premia QSIM.
Continuous publication of changes and revision
A list of all basic changes and possible corrections will be published on the project web sites and will be available also directly from the WebSim application.
5 Deviations from the project work program and corrective actions
No deviations from the project work program detailed in work package 3 were observed. Thus no corrective actions are required. In period 1 there has been a slight delay on finalizing the web data structure that is not material. By mid-December 2007 the application was running satisfactorily on the internet.
|Deliverables |
|D7. A secure Web site with a public and private part. () |
|D8 Hosting, support and maintenance during the project. |
|D9 Web database structure |
|D10 Brief report on test results of the basic simulation environment and specific simulation environment for each SME. |
|D11. Brief report with a proposal for future maintenance protocol of the system after the project |
6 Deliverables
Based on the description of the activities and the Deliverables Table (detailed in Annex), the deliverables of work package three take a slightly different form. The link to the website is integrated in this report and we consider this as Deliverable 7 (D7).
We may upload in CIRCA a small document containing the link. D8 are auxiliary services provided by Wirelessinfo to facilitate the accessibility of the website, no specific proof of this will be uploaded into CIRCA.
|Del. no. |Deliverable name |WP no. |Date Due (project month) |Actual |Person-months |Lead participant |
| | | | |Date | | |
|D7 |Secure Internet page with public and private |3 |6 |15/12/07 |4 |Wirelessinfo |
| |part | | | | | |
|D8 |Hosting, support and maintenance during the |3 |7 |15/12/07 |4 |Wirelessinfo |
| |project | | | | | |
|D9 |Web database structure |3 |8 |15/12/07 |3 |Wirelessinfo |
|D10 |Brief report of test results simulation |3 |16 |15/12/07 |4 |Wirelessinfo |
| |environment | | | | | |
|D11 |Brief report future maintenance protocol |3 |21 |15/12/07 |1 |Wirelessinfo |
7 Milestones
Milestones have been achieved within the period under review.
|Milestone no. |Milestone name |WP no. |Date due |Actual delivery date |Lead Contractor |
|Month 7 |Month 7: Hosting of the Web page will be available |3 |15/04/06 |01/05/06 |Wirelessinfo |
| |and facilitated during the rest of the project. | | | | |
|Month 24 |Month 24: At the end of this work package the |3 |01/10/07 |01/10/07 |Wirelessinfo |
| |predictive models will be available on a secure and | | | | |
| |safe Internet site. | | | | |
4 Progress towards objectives WORK PACKAGE 4: Training and implementation of simulation software
Work package manager: M. Schutyser / M. Vissers (NIZO food research)
|Work package number |4 |Start date or starting event: |Month 14 |
|Participant Short Name |Each SME |NIZO |Wirelessinfo |Total |
|Person-months per participant: |1 (total 16*1 = 16) |3 |2 |21 |
|Objective |
|Training of the SMEs on how to use the simulation software; implementation of the software. |
1 Task 4.1 Preparation of a user manual
A user manual has been prepared that describes the working of the model. Below an illustration has been captured from the user manual. The manual is one of the deliverables of the project and can be found in D12. The user manual describes how to build a model and which types of heating processes may be simulated. Screen shots are used to clarify and exemplify the model workings. For enhanced user friendliness colour codes have been used to identify fixed parameters and user specified parameters. Also, it provides answers and clues for troubleshooting.
[pic]
2 Task 4.2 Arrangement of help-desk facilities
General
A proposal has been defined on how to organize the help desk facilities for software support.
To start there is an on line help function build in the application. The application is hosted on websim.. In the right hand corner there is an on-line help button available for users. The help function serves as a first recourse for users and is naturally free of charge.
There will also be a help-desk facility. If the on-line help-desk facilities of the application do not provide the solution to the question of the user, it is possible to contact NIZO food research for assistance. NIZO food research will provide primary assistance to the SME in the use of the Internet application Software. Help-desk services shall mean: the answering by NIZO food research by telephone of day to day questions with regard to the use of the Software.
Organizational aspects
The consortium will appoint NIZO food research to do what is necessary to maintain the WebSim-MILQ in good and usable condition on behalf of the consortium for its users. There will be an agreement underlying this appointment (produced in Deliverable 17).
NIZO food research will subcontract Wirelessinfo to carry out maintenance of server operation and the control and maintenance of the WebSim application. For this part of the services an agreement (produced in Deliverable 16) will be drafted between Wirelessinfo and NIZO food research based on a two step approach. If the on-line help-desk facilities of the application do not provide the solution to the question of the user then this person may contact NIZO food research for assistance. If required NIZO food research will contact Wirelessinfo to answer the question or solve the problem of the user.
The consortium will appoint NIZO food research to carry out the help desk function. There will be an agreement underlying this appointment (produced in Deliverable 17).
Each consortium member appoints one contact person who shall be entitled to make use of the help-desk services. This person may contact NIZO food by e-mail or by phone with questions on the application. Actual contact data are provided on websim.. A fixed application management fee is proposed that entitles each participating SME to 2 hours help desk assistance per year without additional charges.
The consortium appoints a contact person representing the consortium in relation to the management of the application after the project has finished. An agreement will be drawn up (Deliverable 17.
For new users (non-consortium members) separate agreements will be drawn up according to the same principles as outlined before (fees and terms will be different).
3 Task 4.3 Training of SMEs with the modelling tool
All consortium members have had the opportunity to go to a workshop held at NIZO food research in Ede on 14 June 2007. During this workshop participants have worked through the case presented in Deliverable 14.
Websim MILQ has been developed in the framework of the MILQ-QC-TOOL CRAFT project by NIZO food research (modelling software) and Wirelessinfo (web technology). In this tutorial an exercise has been worked out to stimulate a quick acquaintance with most possibilities of the web application. It is assumed that the user is familiar with working with Microsoft Internet Explorer.
The training case
The milk of a dairy enterprise is pasteurized before cheese making. A scheme of the pasteurizer is shown in the figure below. The cold milk is first preheated by exchanging heat with the hot product coming from the holder (Reg. up). So the heat is regenerated in this section, which is why it is often named a regenerative section. Next, the product is heated to the desired pasteurization temperature (heater 1) and held for some time at this temperature (holder). After the holder, the product is cooled with the cold product in the regenerative section (Reg. down). Finally the product is brought to the renneting temperature for cheese making (heater 2).
To model the pasteurizer in Websim MILQ, it has to be divided into sections for which a sub-model is available. In the figure, the seven selected sections are displayed in different colours. Note that the connection tubes between Reg. up and Heater 1 section (Conn. 1) and between Reg. down and Heater 2 section (Conn. 2) are modelled too. It is not necessary to model sections in which the product temperature is low (black coloured sections in Figure 3), because at low temperatures the changes in the milk are negligible. Sections with a small volume (short residence time of the product) can also be omitted.
[pic]
Figure 7: Scheme of the pasteurization process.
The regenerative and heating sections are plate heat exchangers. The holder section is a thermally isolated cylindrical tube. The connections (sections 2 and 6) are cylindrical tubes too. The regenerative sections 1 and 5 are physically the same. The heat of the product leaving the holder is exchanged in counter-current flow with the cold product. In the heater sections the heat-exchanging medium is hot water with the same flow rate as the milk flow. Each heating section acts in counter-current.
Based on the above process description and additional information on heating equipment dimensions, flows and kinetic data, the user-trainee builds his/her own model for evaluation of a certain set of problems. The trainees are expected to solve these problems using calculations from the WebSim-MILQ application. Then the tutorial provides answers for the case in a logical way. First, it is being discussed how to build a model. Then, analyses and kinetic data issues are tackled and after that results and graphical representations are evaluated.
Another training tool that has been implemented in the last months of 2007 is the e-learning tool. It offers a virtual exploratory tour through WebSim-MILQ application by means of a video showing on the website.
4 Deviations from the project work program and corrective actions
Except for timing issues no deviations in the sense of additional tasks have occurred from the project work program.
5 Deliverables
|Deliverables |
|D12. User manual. |
|D13. Short report describing the realisation of help-desk facilities |
|D14. Course material for training. |
The deliverables have been discussed as part of the work packages. The user manual is attached as D12. A short report describing the realisation of help-desk facilities is attached as D13. Course material for training can be found in complete form in D14. All deliverables are also available as pdf’s from CIRCA.
|Del. no. |Deliverable name |WP no. |Date Due |Actual |Person-months |Lead participant |
| | | |(project |Date | | |
| | | |Month) | | | |
|D12 |User Manual |4 |16 |15/12/07 |5 |NIZO |
|D13 |Report help-desk protocol |4 |27 |15/12/07 |6 |NIZO |
|D14 |Models available on the Internet |4 |27 |15/12/07 |10 |NIZO |
6 Milestones
Below you will find the milestone that has been achieved.
|Milestone no. |Milestone name |WP no. |Date due |Actual/Forecast |Lead Contractor |
| | | | |delivery date | |
|Month 24 |Month 24: After this workpackage the implementation |4 |01/10/07 |15/12/07 |NIZO |
| |of the modelling tool is at each SME is established. | | | | |
| |All SMEs are capable of working with the Internet | | | | |
| |application and a manual will be available on how to | | | | |
| |use this application on the Web. | | | | |
5 Progress towards objectives WORKPACKAGE 5: Project management activities
Workpackage manager: J. van Dijk (Van Dijk Kaasmakerij BV)
|Workpackage number |5 |Start date or starting event: |Month 1 |
|Participant Short Name |Van Dijk | |Total |
|Person-months per participant: |6 | |6 |
|Objective |
|Consortium management activities by the Project Co-ordinator are required to finish this project successfully. |
Consortium and project management activities will be performed continuously throughout the project.
1 Task 5.1 Overall project management
Van Dijk, has been in charge of the management and co-ordination over the entire project duration. Project management comprised the following elements:
• Consortium consensus – pooling of data;
• Monitoring of project progress, including milestones, deliverables and technical risks;
• Contact with EC and Report on project progress;
• Organisation of reviews and meetings (management/technical)
Consortium consensus – pooling of data
Pooling of data and consortium consensus relates to the degree of data sharing between the consortium participants. Some data are company specific and will not be shared except for general and anonymous reporting purposes.
Monitoring of project progress
Monitoring of project progress and associated tasks is done by frequent meetings with NIZO food research and the SME’s. Bi-monthly meetings with NIZO food research have taken place over time during the project. SME’s have been visited as the need arose. All consortium members were contacted by telephone and e-mail.
Contact with EC and Report on project progress
Contact with EC has been established mainly through e-mail contact with the project’s legal liaison, Mr. Alás-Minguez until August 2006, and from September on Mr. Stella and the technical liaison, Mr. Niehoff. There has been also telephone contact with Mr. Nieland regarding amendments to the contract (August 2005). On some occasions we had e-mail contact about technical issues concerning CIRCA with Mrs. Pouret. Mr. G. Coluccio got involved in the project medio 2007.
Subjects of contact with the commission included:
- Accession to the contract
- Amendment to the contract
- Official starting date request
- Request for information on advance payments to RTD performers under the contract
- Technical issues regarding CIRCA
Amendment to the contract
Originally the proposal MILQ-QC-TOOL has been written and entered for consideration in the 2003 call for projects under the CRAFT facility. After two rounds of modifications the project has been selected for funding during the 2005 call. For two participants in the consortium (Rouveen, NL and St. Jozef, B) the delay caused a problem in taking up the responsibilities required to fulfil the project. This became only apparent in August 2005, after signing the contract (21/7/05 & 28/7/05). They cited lack of time as the and other obligations as the reason for no longer being able to participate. This was discussed and two new candidates were proposed to take up the open places (Farmer House Products, NL and Capra, B). In September 2006, it became clear that Laksyma was not able to fulfil its obligations as a participant and they dropped from the consortium. Another dairy that was interested to take its place, Gordon Prod, of Romania was proposed and incorporated.
The reason for wanting to keep the consortium at the original number (16) was twofold. Firstly, the overhead cost of maintaining the website and using the knowledge beyond the project’s time horizon requires a good number of active dairies. In the description of the project sixteen dairies was deemed the minimum. Secondly. During the project, it is necessary to have enough variety in the products and types of milk to validate the model for a broad number of scenario’s.
Official starting date request
Upon the advice of Mr. Alás-Mingues, we sent a letter requesting for the official starting date of the project. On behalf of the consortium a letter was sent requesting to start the project on 16/1/06 or any other date the Commission deemed correct as the starting date. We received a letter detailing us that the official starting date was 16/9/05. This posed some challenges to the planning. In August 2007 an extension was asked to finish the project by 31 December 2007. The latter was necessary to finish the work on the training manual and the e-learning tool.
Organisation of reviews and meetings
With reference to organisation of reviews and meetings it can be mentioned that the first official meeting for the whole consortium was held at the NIZO food research premises on 26/1/06. Both research and technology partners and the majority of the SME’s were present. The objectives of the research have been presented and a first presentation of the prototype model was given.
A technical meeting between NIZO food research and Wirelessinfo was held from 1-2 August 2006. The purpose of this meeting was to discuss the technical functionalities of the heat optimisation model and the platform on which it will run. In depth interaction between NIZO food research and Wirelessinfo facilitates the development from the heat treatment model internet application.
New dates for meetings have been agreed. Technical and project management meetings have been scheduled for 31 October – 1 November 2006 and a consortium partners workshop has been planned for 16/11/06. A prototype of the application was presented to the consortium partners.
A Beta-testing session has been organized on 23 January 2007. Bettinehoeve, Farmer House Products and Van Dijk Kaasmakerij were present to test the application.
On 14-15 March 2007 a joint technical and project management meeting took place in Prague, Czech Republic.
The official launch of the application took place on 14 June 2007 in Ede, the Netherlands. On 15 June 2007 a project management meeting was held. In the months July until December various meetings took place with individual SME’s to model specific processes.
2 Task 5.2 – Exploitation and dissemination
It has been investigated if intellectual property rights play a role in the exploitation and dissemination of the WebSim-MILQ application.
No intellectual rights are being registered. The product itself is a software tool that can be protected by supplying an executable file only to the users.
The full proposal for exploitation and dissemination of the knowledge is annexed as D18. Also, according to the fixed reporting format it will be reiterated in the section dealing with these aspects.
The highlights are as follows:
1) The consortium proposes that NIZO food research will be appointed as the agent to exploit the WebSim-MILQ application.
2) NIZO food research will ensure that sufficient IT knowledge will be available to run the application. It is suggested that Wirelessinfo will be the subcontractor for this purpose.
3) The consortium appoints a representative among themselves to deal with NIZO food research. Once a year the results will be communicated to the participating consortium members.
4) Consortium members formally accept ownership of WebSim-MILQ and the rights and obligations that come with ownership. The rights are entitlements to revenue sharing, the obligations are to keep the application running.
During the project, and this will continue after the project, dissemination took further place through a number of conference presentations, papers, (semi-) popular articles and participation in the living labs award and a business game award, which was actually won.
3 Deviations from the project work program and corrective actions
Inclusion of new consortium members caused timing issues. However, parallel running of tasks kept delays to an absolute minimum.
4 Deliverables
|Deliverables |
|D15 Draft plan for using and disseminating knowledge |
|D16 Licence contract for system maintenance and help-desk facilities |
|D17 Consortium agreement |
|D18 Final plan for using and disseminating knowledge |
|D19. 12 and 27-month progress report |
The deliverables for the project activity described in work package 5 are management related. This report (D19 – 27 months) fulfils the annual reporting obligation and will be uploaded in the deliverables section from CIRCA. The draft plan for the usage and dissemination of knowledge has been uploaded after the Period 1 report was submitted. The final dissemination plan will be uploaded as D18 and can be found in the reporting section with the same name.
|Del. no. |Deliverable name |WP no. |Date due (project |Actual delivery date |Person-months |Lead participant |
| | | |Month) | | | |
|D15 |Draft plan for using and dissemination |5 |12 |16/9/06 |1 |Van Dijk |
| |knowledge | | | | | |
|D16 |Licence contract |5 |23 |15/12/07 |0.5 |Van Dijk |
|D17 |Consortium agreement |5 |23 |15/12/07 |0.5 |Van Dijk |
|D18 |Final plan for using and dissemination |5 |27 |15/12/07 |1 |Van Dijk |
| |knowledge | | | | | |
|D19 |Yearly reports |5 |12, 27 |15/03/07 |3 |Van Dijk |
| | | | |30/01/08 | | |
5 Milestones
Milestones are being reported in the table presented below.
|Milestone no. |Milestone name |WP no. |Date due |Actual delivery date |Lead Contractor |
|Month 23 |Month 23: Licence contract and consortium agreement |5 |01/09/07 |15/12/07 |Van Dijk |
|Month 27 |Month 27: Final review report. |5 |15/12/07 |31/12/07 |Van Dijk |
|Month 27 |Month 27: Final Plan for using and disseminating |5 |15/12/07 |31/12/07 |Van Dijk |
| |knowledge | | | | |
Consortium Management
Consortium management is one of the tasks of the SME coordinator which is described in work package 5. Some problems have occurred as detailed in section 3.5.1.
The consortium partners can work relatively independent on this project since the model allows for each participant to select one production process in their own organisation for optimization of heat treatment. Contacts between consortium partners and researchers are usually one on one except for the three workshops that took place.
Questions regarding the working of the consortium were addressed using the consortium agreement as the resource document. A number of questions regarded confidentiality of the results and a number of questions were addressed regarding the management structure of the project. Some facilitating between consortium members and RTD performers clarified the data and process needs of NIZO food research.
Both NIZO food research and Wirelessinfo have performed well on the research tasks. In NIZO food research Dr. ir. Maarten Schutyser has replaced Dr. ir. Maykel Verschueren as project manager.
In the consortium two new partners have been incorporated, Capra NV (B) and Farmer House Products (NL) although no formal acceptance decision has been received yet. Two initial members have been dropped, Rouveen (NL) and St. Jozef (B).
Laksyma (CZ) has also been dropped from the consortium in September 2006. Gordon Prod of Romania has been included in February 2007.
The kick off meeting in Ede on 26 January 2006 was instrumental in having as many SME’s as possible together to go over all the information that was forwarded to them by mail and conveyed in one on one sessions. All work packages were presented and this resulted in a lively interaction among the participants and research providers.
A technical meeting was held between NIZO food research and Wirelessinfo on 1 and 2 August 2006. Maarten Schutyser started with a presentation about the MILQ project and the progress that has been made since the start of the project. Maarten Schutyser continued with a presentation about the approach NIZO food research follows to optimize a pasteurization process. This was done by presenting a case study. It was highlighted which data are required for implementation of a pasteurization process in NIZO Premia.
A technical meeting took place on 31 October and 1 November 2006. This was combined with a project management meeting on 1 November to discuss and monitor progress.
On 16 November 2006 a consortium meeting and workshop was organized in Ede. The prototype model was presented and practical issues concerning the consortium were discussed. On 21 January 2007 Beta testing of the model took place with selected consortium members.
In March, 14-15 another technical meeting took place combined with a management meeting. Progress was monitored and proposals for dissemination have been discussed.
A workshop was held on 14 June 2007 to educate all partners on the use of the model. Individual activities continued with the participating SMEs until the end of the project. On 15 June another management meeting took place to decide on elementary issues surrounding proposals for post project dissemination.
In the following chart the work planning is illustrated, showing the timing of the different workpackages and their components.
| | |Month | | | | | |
| | |after | | | | | |
| | |start | | | | | |
| | |of the | | | | | |
| | |project| | | | | |
|D1 |Work sheet with process and product data |1 |NIZO |15 |R |CO |3 |
|D2 |Work sheet with experimental data |1 |NIZO |39 |R |CO |9 |
|D3 |Work sheet with validation data |1 |NIZO |23 |R |CO |14 |
|D4 |Customised models – first prototype |2 |NIZO |29 |P |RE |12 |
|D5 |Evaluation of comments SMEs on first |2 |NIZO |6 |R |RE |18 |
| |prototype | | | | | | |
|D6 |Report with results of optimised heat |2 |NIZO |24 |R |PU |18 |
| |treatment | | | | | | |
|D7 |Secure Internet page with public and |3 |Wirelessinfo |4 |P |PU |6 |
| |private part | | | | | | |
|D8 |Hosting, support and maintenance during |3 |Wirelessinfo |4 |O |RE |7 |
| |the project | | | | | | |
|D9 |Web database structure |3 |Wirelessinfo |3 |O |RE |8 |
|D10 |Brief report of test results simulation |3 |Wirelessinfo |4 |R |RE |16 |
| |environment | | | | | | |
|D11 |Brief report future maintenance protocol |3 |Wirelessinfo |1 |R |CO |21 |
|D12 |User Manual |4 |NIZO |5 |R |RE |16 |
|D13 |Report help-desk protocol |4 |NIZO |6 |R |CO |21 |
|D14 |Models available on the Internet |4 |NIZO |10 |P |CO |24 |
|D15 |Draft plan for using and dissemination |5 |Van Dijk |1 |R |RE |12 |
| |knowledge | | | | | | |
|D16 |Licence contract |5 |Van Dijk |0.5 |O |CO |23 |
|D17 |Consortium agreement |5 |Van Dijk |0.5 |O |CO |23 |
|D18 |Final plan for using and dissemination |5 |Van Dijk |1 |R |RE |24 |
| |knowledge | | | | | | |
|D19 |Yearly reports |5 |Van Dijk |3 |R |RE |12,24 |
| | | |TOTAL |179 | | | |
[pic]
-----------------------
[1] R = Report, P = Prototype, D = Demonstrator, O = Other
[2] PU = Public, PP = Restricted to other programme participants (including the Commission Services), RE = Restricted to a group specified by the consortium (including the Commission Services), CO = Confidential, only for members of the consortium (including the Commission Services).
[3] R = Report, P = Prototype, D = Demonstrator, O = Other
[4] PU = Public, PP = Restricted to other programme participants (including the Commission Services), RE = Restricted to a group specified by the consortium (including the Commission Services), CO = Confidential, only for members of the consortium (including the Commission Services).
[5] Project month
-----------------------
Application
QSim03Wrapper
QSim03.dll
Request (XML)
Response (XML)
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