Genencor and PI

2. Genencor and PI Johan Saerens

3. GENENCOR INTERNATIONAL a Danisco Division A global leader in the development of biotechnology products for Bioproducts andAgriculture markets

4. FINLAND Jämsänkoski Hanko NETHERLANDS Leiden BELGIUM Brugge CHINA Beijing Wuxi JAPAN Tokyo USA Rochester, NY Palo Alto, CA Cedar Rapids, IA Beloit,WI SINGAPORE Beloit, Wisconsin ARGENTINA Arroyito Buenos Aires Mfg. R&D Admin. Genencor Locations • > 4 million liters of fermentation capacity

5. ACTIVITIES – GENENCOR • Genencor International • Manufacturing plant • Production of Enzymes • Market: • Feed • Grain Processing • Food • Biofuels • Textiles • Sweeteners • Cleaning Products

6. Hot Cook Conventional EtOH Process Phytase* Animal Feed with enhanced* nutritional value

7. 2nd Generation BioEthanol:Not starch but biomass [cellulose]-based

8. alpha-amylase pullulanase APPLICATION – STARCH DEGRADING ENZYMES glucoamylase Glucose glucose isomerase Fructose fungal amylase or beta-amylase Maltose

9. Kyoto ? • In Belgium the CO2 emission should be reducedwith11 MTon by 2012 • Calculation prof. Soetaert (University of Gent) : • Enzymen produced in Genencor Belgium will result in an CO2 reduction in their application of 2 MTon (worldwide) • Comparison : the Thornton windmill park will reduce CO2 emission by 1,6 MTon

10. Genencor High Level Production Process Where the enzyme is made. Fermentation Where the enzyme is purified. Where the enzyme is stabilized/standarized Formulated Product Recovery Product Storage

11. Batch PROCESS Genencor Brugge…

12. Data aquisition up to 1996 : manual/ internally developped software • PRO • Batch oriented • Integrated with Lab data • Variable charts, definable by the operator • Profiles • Based upon Hour After Inoculation • CONTRA • Manual input (90%) possible operator errors • Limited number of parameters (128/batch) • Based upon hours, no detailed data • No time reference. (totals over batches) • No interfacing with other programs (Excel..) • No data compressing -> slow • A lot of paper

13. What do we want, check with the users • Process engineer (they define where we can find money) • Batch oriented • Comparison between batches (GOLDEN batch principle) over the plant limits. • Fast & easy access to process data • scale up • continuous improvement, • transfer between plants, lower the number of batches needed for a transfer (10 #) • … • Be able to make any special calculation • Production engineers (they make the money) • Production data concerning occupation / batch information • Warehouse management • Raw material management • Event registration

14. What do we want, check with the users • Capital engineers (they spend a lot of money) • Real time trendings • Possibility to evaluate equipment • Utility officer / maintenance people (they really try to save the money) • Fast overview of his utility equipment status • Real time data from equipment • KPI / efficiencies of the systems to detect efficiency improvement

15. And then came: OSI PI • After a market evaluation of different products we came to OSI PI • Not a lot of automation effort. • Easily explained to the different end users • Use of process books • Use of excel interface • Use of batch functionality • Batch oriënted • Easy to use, maintain • Great interface to automation systems (delta V, ABB, Metso, Honeywell,…) so site independent. • Easy interface to LAB system (Unilab) • Rather low maintenance / maintenance costs

16. OSI PI use Functional Setup

17. OSI PI use in GENENCOR • +/- 50 000 tags world wide (small nevertheless efficient) • Plant servers: choise for system availability • All sites are having PI Batch working for fermentation. • The LIMS-to-PI interface is expanded to all other sites. • We are testing the SAP xMII tool; this tool is using a bidirectional interface to a PI server in the test environment. • How do we proceed for future (MES, Interfacing to SAP, Rlink, ….)

18. Process Engineers • Flexible Batch process droptank Sterilizer feedsystem seed fermentor withdrawal

19. Process engineers • Golden batch : analysis of f.e. cellulose feed • Gathering data from 2 batches and the running one • Get the batch reports • Find out which fermentors were used • What was the sterilizer used for cellulose • Find the TAG of the flowmeter • Find out the timing, when did the process start • The extract the data and analyse

20. Process engineers • Golden batch : analysis of time / temperature of sterilisation • Now with PI • Fill in the batch numbers • Choose the parameters you want to see • Push the button

21. Production engineers • Detailed planning / analysis

22. Capital engineers Engineers • Detailed evaluation: pump curves, VFD controlled systems

23. Capital engineers • Chillers : energy optimization

24. Maintenance Technicians

25. Utility officer

26. Conclusions • Very useful especially with our batch systems • Fast and quick responses • Multiple interfaces make connectivity very easy • PI used as a client tool and not a programming/IT task • Very user friendly and consistent in upgrades to existing configurations • Resulting in • Fast data gathering, fast introducing / transferring new products • Very good tool for analyzing the process resulting in less events, finding root causes and final fixes. • Preventive maintenance increases significantly up-time and reduces corrective actions (costs) • Optimizing processes based on good reliable data • Still a lot of opportunities to explore

27. Conclusions some numbers from Bruges plant… • Plant to plant transfert of products: number of trials to result in the same output : reduced from 10 -> 3# gain : 500k€ /transfer resulting in > 2 M€/yr only for Bruges plant • Reducing corrective maintenance by preventive actions. Capacity gain in fermentation due to an increase in availability of the equipment from 92% to 96%. • Justification data for optimizing the energy use: projects in 2008 resulted already in a yearly saving of >200 k€/yr on the electricity bill. • OSI PI has delivered an essential part into these successes