De volgende stap in flexibel en kostenbesparend produceren
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1 De volgende stap in flexibel en kostenbesparend produceren Dr. Peter de Jong PO Box 20, 6710 BA Ede
2 Introducing NIZO food research (1) Founded in 1948, now leading European research company Roots in Dairy Industry Applying knowledge for implementable solutions Work with customers to achieve their goals Constant search for ways to improve food 200 professionals State-of-the-art facilities & food-grade pilot plant Located in Food Valley in The Netherlands ISO 9001:2000 certified 2
3 Introducing NIZO food research (2) Track record, a selection Starter cultures (CSK Food Enrichment) Process equipment (Casomatic) Expression systems (NICE) Products (various cheeses, NIZO butter process) Processing models (e.g. Premia) Taste solutions (PeptoPro Sports at Olympic Games 2004) 21,0 18,0 15,0 12,0 9,0 6,0 3,0 0,0 Autonomous annual Growth Partner in TIFN (Top Institute Food & Nutrition) and Kluyver Centre for Genomics of Industrial fermentation 3
4 World of our customers Flexibility Sustainability Production costs Speed 4
5 Case 1: Process scan Nenatal (Premia Premia) Customer need Reduction of processing costs by less fouling (target: 80%) Improved powder properties Solution 1. Process audit 2. Evaluation of process with computer models (Premia ) 3. Design new temperature-time profile during heat treatment 4. Test in pilot plant 5. Implementation Results Run time increased from 2 to 12 hours Improved solubility of powder 5
6 Case 2: Model-based control (Premic Premic) Customer need Cost reduction Constant quality (e.g. from different co-packers) Solution 1. Partnership Honeywell-NIZO 2. Process simulation models predicting operation costs and product properties 3. Models used to build model-based process controller (Premic ) 4. IN: product specs, OUT: optimal set-point values Results Operational excellence Cost reduction of 10-50% 6
7 Test inline-troebelheidsensor inline offline Tijd (min) Case 3: Intelligent cleaning (OptiCIP OptiCIP+) Customer need Extended production time of falling film evaporators and preheating equipment Validated, efficient cleaning Solution 1. Database: composition processing conditions fouling degree cleaning conditions cleaning effect 2. In-line turbidity and calcium sensors for controlling cleaning effect 3. Self-learning system (OptiCIP+) based on Premic technology 4. After production OptiCIP+ determines optimal cleaning conditions and time Results Being demonstrated in whey factory Estimated annual cost reduction k Troebelheid inline (%) 7
8 Case 4: Production data generation (Micro pilot plant concept) Customer need Kinetic data of process-induced product changes Fast process and product development / up scaling Solution 1. Building micro pilot plant (heater, cheese production, drying) 2. In-line sensors of product changes 3. In-line coupling to process simulation models (Premia ) 4. In-line determination of kinetic data (bacteria inactivation, protein denaturation, etc.) Results 75% reduction in development time Inactivation experiments for bacterial spores within 4 h 8
9 Take home message World wide process scans resulted in reduced operation costs (~15-50%) less fouling efficient and short cleaning less product losses Process and product models help to food manufacturers to gain more flexibility, sustainable processing, reduced costs and short development time 9
10 Why NIZO (we enable the next steps ) And the next step is the future factory Desk-top R&D De hele R&D-afdeling op het bureau van de R&D manager Computer regelt op smaak Type de gewenste productspecificaties in en het computer-systeem doet de rest High-tech food Voedingsmiddelenindustrie neemt technologieën uit de chemische en defensieindustrie over Meten van smaak De operator in de fabriek weet van te voren in hoeverre de consument het product zal waarderen Melkbad Restwater wordt gebruikt als drinkwater en in zwembaden 10
11 Thank you for your attention 11
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