Augmented process control and maintenance interface for an alcohol fermentation plant.

Galzina, Vjekoslav ; Saric, Tomislav ; Lujic, Roberto 等

1. INTRODUCTION

Keeping operation variables stable was previously only objective of a given process control. New objectives put in front of process industry as result of variable working conditions ask for reliable control and monitoring system for supervision (Tellez-Angiano at al., 2008). Final solution has to be modular, time and cost effective in deployment and maintenance. Two main tasks in this example needed to be satisfied: one is to preserve self-sufficiency of control and monitoring system for fermentation plant and enable connection with other present systems in refinery and factory. In recent period, ethanol alcohol as alternative fuel product draws progressive attention. New ways of production, new sources of feedstock and control are presented recently (Balat, 2009; Cinar et al. 2003). New control paradigms and strategies are tested and deployed, like ones in evaluated literature where fuzzy logic (Karakuzo et al., 2006, Balic & Majdandzic, 2008; Zhao, 2008), neural networks (Meleiro & Maciel Filho, 2000) and genetic algorithms for process identification and control (Campello et al., 2003) were used. Process industry supervision and control is considered complex doe to high integration (Cinar et al., 2003; Charbonnier et al., 2005). This all makes more difficult to preserve safety, process and maintenance demands at local and consequently global factory level. An advanced control system should provide displays which are oriented toward the total process rather than towards only individual parameters (Barker et al., 2005; Tellez-Angiano et al., 2008) furthermore it could stand for every supervision and control system generally speaking.

2. ALCOHOL RAFINERY

Sugar beet molasses, as by-product of sugar production, is commonly used as substrate for ethanol and yeast biomass production. Ethanol usage is as technical alcohol, in alcoholic beverages production and as alternative fuel. Fig. 1. presents general scheme of alcohol refinement from sugar molasses. Main focus in this paper is on fermenters and preparation of constituents for batch-feed fermentation supervision and control in refinery as central unit in alcohol production. Molasses preparation, and latter distillation and rectification are not covered in this paper, only as information interchanges between these systems in function.

[FIGURE 1 OMITTED]

3. FERMENTATION PLANT INTERFACE DESIGN

A properly designed plant interface system should provide displays and interfaces, which operator can use to supervise and control all available process activity. The interaction is dual: active in controlling the process or passive in monitoring the system and process behaviour (Barker et al., 2005). Input data from other systems are: status of molasses preparation system, concentration of molasses, flows; status of distillation and rectification columns, main flows, temperatures and concentrations; general supply status; general communication status of relevant systems. System must maintain self- sufficiency even if other control systems fail (working on last known set points until operator declare otherwise).

Process control interface is the means by which the operators, site supervisors, maintenance engineers and system administrators interact with the system. Process operators need to know present and past process data, trends and alarms and be able to control process in the desired way. Supervisor need to check historical trends and give direction for operators accordingly. A maintenance engineer has to have entrance for equipment usage, its parameters and all other relevant data (Barker et al., 2005). System administrator has local and remote access for database administration and system health control, setup and configuration screens for controllers parameters and system behavioural configuration. All of these functions needed to be taken in to the consideration in process control interface design and deployment. Design considerations have to be taken by human oriented approach in goal of realization better integration of procedures, control and alarm system (Carvalho et al., 2008; Cinar et al., 2003; Nachreiner et al., 2006). New setup configuration consists of one central process controller and one central personal computer with two monitors (one for process control operations and other for alarms and messages) for process control interface. At Fig. 2. detail of main process control operations is shown. Operators usually keep this screen active for the period of normal operation of system.

[FIGURE 2 OMITTED]

3.1 Acid dilution

Acid dilution is one of safety critical from maintenance and control point of view because of aggressive media used. Sulphuric acid is strong mineral acid and its dilution in water is highly exothermic reaction. Industrial concentrated sulphuric acid is stored in outside monthly tanks and mixed with molasses after dilution. Because of water, relative lower density it tends to float on acid and process needs to be closely monitored and controlled to avoid dangerous splatter and boiling if water is accidentally added in acid. Main control value is temperature in mixing tank. Acid is 10% diluted (in mass concentration). Diluted acid is added to yeast milk and mixed. This mixture is further mixed with prepared molasses, water and nutrition salts mixture in pre-fermenter.

3.2 Process Supervision and Control

Supervision and control of fermenters is in main concern of operators beside control of quality of product by means of sample extraction and bio-chemical analysis (in present time manual). Main process control is modular programmable logic controller (PLC) based with Profibus and Industrial Ethernet communication connections to other systems (*). Control of continues variables is by means of standard and advanced software fuzzy proportional integral derivable algorithm (PID and fuzzy-PID). Parameters optimization is off-line particle swarm optimization for different work regimes of advanced control (start-up and normal) for mixture of water, diluted acid, molasses, additives and temperature control in pre-fermenter and standard for air, water and molasses flows in fermenters for error and error rate.

Alarms control have been divided in two screens, distinguishing acid dilution and fermenters control alarms and all other alarms; where others include approximately 100 valves, pumps and electrical drives status values. Relevant information for maintenance division is prepared in form of graphic signalization for operators (Fig.3)) and text alarms and messages interchange for maintenance division. User's remarks after first period of usage was taken in to the consideration, evaluated and implemented.

[FIGURE 3 OMITTED]

4. RESULTS AND CONCLUSION

The process control system presented in this paper uses adopted computer based interface as a replacement of former conventional interface. Implementation of new control system based on software algorithms was successful and replaced old conventional. Users have all relevant information on one place; and maintenance staff now can historically view and act preventively.

* Sample extraction and bio-chemical analysis for molasses needs to be fully automated and integrated in process control system to enable more autonomy optimisation of control parameters.

5. ACKNOWLEDGEMENTS

The authors would like to thank Sladorana d.d. Zupanja Sugar Factory where the research was performed at Alcohol refinery plant and its staff for their cooperation in the ongoing case study, especially maintenance division.

6. REFERENCES

Balat, M.; Balat, H. (2009). Recent trends in global production and utilization of bio-ethanol fuel, Applied Energy 86, 2273-2282

Balic, J. (Ed.); Majdanzic, N. (Ed.) (2008). Digital Factory, DAAAM International, ISBN 3-901509-67-4, Vienna

Barker, M.; Jawahar Rawtani J.; Mackay S. (2005). Operator and supervisor interface, Practical Batch Process Management, 86-92

Campello, R.J.G.B; Von Zuben, F.J.; Amaral, W.C.; Meleiro, L.A.C., Maciel Filho, R. (2003). Hierarchical fuzzy models within the framework and their application to bioprocess control, Chemical Engineering Science 58, 4259-4270

Carbonniere, S.; Garcia-Beltan, C.; Cadet, C.; Gentil, S. (2005). Trends extraction and analysis for complex system monitoring and decision support, Engineering Applications and Artificial Intelligence 18, 21-36

Carvalho P.V.R. et al. (2008). Human factor approach for evaluation and redesign of human-system interfaces of a nuclear power plant simulator, Displays 29, 273-284

Cinar et. al. (Ed.) (2003). Batch Fermentation: Modeling, Monitoring, and Control, Marcel Dekker, Inc., ISBN: 0-8247-4034-3, New York

Karakuzo, C.; Turker, M.& Ozturk, S. (2006). Modelling, on-line state estimation and fuzzy control of production scale fed-batch baker's yeast fermentation, Control Engineering

Practice 14, 959-974 Meleiro, L.A.C.& Maciel Filho, R. (2000). A self-tuning adaptive control applied to an industrial large scale ethanol production, Computers and Chemical Engineering 24, 925-930

Nachreiner, F.; Nickel, P. & Meyer, I. (2006). Human factors in process control systems: the design of human-machine interfaces, Safety Science 44, 5-26

Tellez-Angiano, A.; Rivas-Cruz, F.; Astorga-Zaragoza, C.-M.; Alcorta-Garcia, E. & Juarez-Romero, D. (2008). Process control interface system for a distillation plant, Computers Standards& Interfaces 31, 471-479

Venkateswarlu, C. & Gangiah, K. (1996). Fuzzy modeling and control of batch beer fermentation, Chemical Engineering Communications 138, 89-111

Zhao, S.-R. (2008). Study on temperature fuzzy control in ferment process, Journal of Tianjin Polytechnic University 27, 70-73

*** (2008) User manual: Supervision and control system--fermentation and deluted acid Sladorana d.d. Zupanja, version 2.1, Peritus Nodus, Slavonski Brod, Croatia