Skip to main content
SpringerLink
Log in

An Integrated Mining and Metallurgical Enterprise Enabling Continuous Process Optimization

  • Chapter
Innovative Process Development in Metallurgical Industry

Abstract

A holistic approach to operational excellence is becoming important as mining and metallurgical companies are presented with various challenges. More specifically, the survival of many mining companies depends on the capability to make well-informed and timely decisions that achieve dynamic and continuous optimization, despite various complexities surrounding the industry.

This chapter focuses on leveraging recent advancements in information technologies, sensors, measurement tools, real-time optimization of process control, and automation in the mining and metallurgical industries. In particular, the chapter elucidates with examples how such technologies, tools, and processes can be an enabler for an “integrated metallurgical enterprise.” In addition, the importance of a systematic approach to data analytics has been emphasized in this chapter with an aim to convert operational information into business intelligence.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 169.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Alvarez, E. (2005). Advanced process control to meet the needs of the metallurgical industry. World of Metallurgy: ERZMETALL, 58(3), 123.

    Google Scholar 

  • Arora, V. (2007). Improving plant operations. Retrieved from http://www.schneider-electric.ca/documents/solutions/success_story/136-adelaide-broghton-cement-in-australia.pdf.

  • Bassett, R. (2013, May). Understanding wireless technology, Automation World.

    Google Scholar 

  • Bergh, L. G., Lucic, E. M., & Zuleta, F. M. (2007). Supervisory control project of copper solvent extraction pilot plant. In R. L. Stephen & G. A. Eltringham (Eds.), Process control, optimization and six sigma (Vol. 7). Montreal, QC, Canada: The Canadian Institute of Mining, Metallurgy and Petroleum.

    Google Scholar 

  • BHP-Billiton. (2013). Retrieved from http://www.stepchangeglobal.com/wp-content/uploads/2013/09/IROC-Brochure-201305031.pdf.

  • Burke, T. (2008). OPC and Intro OPC UA, Presentation at OPC UA DevCon. Munich.

    Google Scholar 

  • Cameron, D. A., & Durlofsky, L. J. (2014). Optimization and data assimilation for geological carbon storage. Taylor & Francis Group/CRC Press.

    Google Scholar 

  • Chauhan, N. (2013). Modernizing machine to machine interaction—A platform for igniting the next industrial revolution. GE Software White paper, Retrieved September, 2013.

    Google Scholar 

  • Enterprise gateway (2010)—A MOM solution for integrating production and maintenance in real time (5G Automatika Internal Report 240310).

    Google Scholar 

  • Fielding, R. T. (2000). Architectural styles and the design of network-based software architectures. Irvine, CA: University of California.

    Google Scholar 

  • Fortuna, L., Graziani, S., Rizzo, A., & Xibilia, M. G. (2007). Soft sensors for monitoring and control of industrial processes. London: Springer.

    Google Scholar 

  • Gehman, D. (2013, May). ISA-95: Integrating manufacturing’s future, Automation World.

    Google Scholar 

  • Gillot, P. (2006). Pit-to-plant optimization at morila gold mines. In Proceedings of the SAG 2006 conference, Vancouver.

    Google Scholar 

  • Isokangas, E., Sonmez, B., Wortley, M., & Valery, W. (2012). Using smarttag to track ore in process integration and optimization projects: Some case studies in a variety of applications. In Platinum 2012, SAIMM conference.

    Google Scholar 

  • Iwanitz, F., & Lange, J. (2006). OPC: Fundamentals, implementation, and application. Heidelberg, Germany: Hüthing.

    Google Scholar 

  • Markoja, B. (2011, December). Cidra SONARtrac flowmeters: An alternative flow measurement technology. Paper presented at ISTOG Winter Conference, Florida, USA.

    Google Scholar 

  • McKee, D. (2013). Understanding mine to mill, A monograph published by the Co-operative Research Centre for Optimizing Resource Extraction (CRC ORE). Brisbane, Australia.

    Google Scholar 

  • Mumbi, M. (2012). Process optimization of mixed copper ores through real-time mineralogical analysis. Presentation from Quantum Minerals, Zambia.

    Google Scholar 

  • Rajaieyamchee, M. A., & Bratvold, R. B. (2009). Real time decision support in drilling operations using Bayesian decision networks. SPE 124247, 2009 SPE EUROPEC/EAGE Annual Conference and Exhibition held in New Orleans, Lousiana, USA.

    Google Scholar 

  • Renner, D., La Rosa, D., DeKlerk, W., Valery, W., Sampson, P., Noi, S. et al. (2006). AngloGold Ashanti Iduapriem mining and milling process integration and optimization, Vol. 1. SAG 2006 Conference Proceedings, Vancouver.

    Google Scholar 

  • Schlaepfer, R., & Koch, M. (2014). Industry 4.0—Challenges and solutions for the digital transformations and use of exponential technologies, Deloitte.

    Google Scholar 

  • Sherring, A. (2012). Automation and remote collaboration: Will it change the future of mining? Presented at the Honeywell Users Group Symposium, extract written in the PACE magazine.

  • Sinclair. M. (2012). Remote Collaboration Centres (Honeywell). Retrieved from https://www.posccaesar.org/svn/pub/PCA/MemberMeeting/201210/Day2/RemoteCollaborationCenters-MikeSinclair-Oct2012.pdf.

  • Skonnard, A., & Gudgin, M. (2001). Essential XML quick reference. Upper Saddle River, NJ: Addison-Wesley.

    Google Scholar 

  • Thermoslag, ver. 2. (2010). Swedish Steel Producers Association.

    Google Scholar 

  • Zamora, C., Schifferli, G., Castelli, L., & Bonomelli, A. (2010). Kairos mining: A comprehensive approach to sustained long term benefits in copper processing plant automation. Paper presented at the 42nd Annual Canadian Mineral Processors Conference, Ottawa, Retrieved June 19–21, 2010.

    Google Scholar 

  • Zurawski, R. (Ed.). (2005). Industrial communication technology handbook (Industrial technology series, Vol. 1, pp. 7–10). Boca Raton, FL: CRC Press. Retrieved 4 Feb 2013. ISBN 0849330777. LCCN 2004057922.

Further Reading

  • Alsmeyer, F. (2006). Automatic adjustment of data compression in process information management systems. In W. Marquardt & C. Pantelides (Ed.), Proceedings of the 16th European Symposium on Computer Aided Process Engineering. Garmisch-Partenkirchen, Germany. Retrieved May 9, 2009, from http://bit.ly/tWouV.

  • American National Standards Institute/International Society of Automation, ANSI/ISA-99.00.01-2007. (2007). Security for industrial automation and control systems: Concepts, terminology and models. Research Triangle Park, NC: ISA.

    Google Scholar 

  • Anderson, B. D. O., & Moore, J. B. (1979). Optimal filtering. Upper Saddle River, NJ: Prentice-Hall.

    Google Scholar 

  • Anderson, R. J. (2008). Security engineering: A guide to building dependable distributed systems. Hoboken, NJ: Wiley. ISBN 978-0-470-06852-6.

    Google Scholar 

  • ANSI/ISA-95.00.01-2000. (2000). Enterprise-control system integration Part 1: Models and terminology. Research Triangle Park, NC: ISA.

    Google Scholar 

  • ANSI/ISA-95.00.02-2001. (2001). Enterprise-control system integration Part 2: Object model attributes. Research Triangle Park, NC: ISA.

    Google Scholar 

  • ANSI/ISA-95.00.03-2005. (2005). Enterprise-control system integration, Part 3: Models of manufacturing operations management. Research Triangle Park, NC: ISA.

    Google Scholar 

  • ANSI/ISA-95.00.05-2007. (2007). Integration, Part 5: Business-to-manufacturing transactions. Research Triangle Park, NC: ISA.

    Google Scholar 

  • ANSI/ISA-99.00.01-2007. (2007). Security for industrial automation and control systems: Concepts, terminology and models. Research Triangle Park, NC: ISA.

    Google Scholar 

  • Åström, K. J., & Hägglund, T. (2006). Advanced PID control. Research Triangle Park, NC: ISA.

    Google Scholar 

  • Bemporad, A., & Morari, M. (1999). Control of systems integrating logic, dynamics, and constraints. Automatica, 35(3), 407–427.

    Article  Google Scholar 

  • Biehl, M., Prater, E., & McIntyre, J. (2004). Remote repair, diagnostics, and maintenance. Communications of the ACM, 47(11), 100.

    Article  Google Scholar 

  • Bondi, A. (2000). Characteristics of scalability and their impact on performance. In: ACM Proceedings of the 2nd International Workshop on Software and Performance (pp. 195–203). Ottawa, Canada, ISBN: 1-58113-195-X.

    Google Scholar 

  • Brandl, D. (2006). Design patterns for flexible manufacturing. Research Triangle Park, NC: ISA.

    Google Scholar 

  • Brändle, M., & Naedele, M. (2008, November/December). Security for process control systems: An overview. IEEE Security & Privacy, 6(6), 24–29.

    Google Scholar 

  • Bristol, E. H. (1990). Swinging door trending: adaptive trend recording? In ISA National Conference Proceedings. New Orleans, LA.

    Google Scholar 

  • Byres, E. J. (2002, September).The Myth of obscurity. InTech (p. 76). Research Triangle Park, NC: ISA.

    Google Scholar 

  • Chappell, D. A. (2003). Using S88 batch techniques to manage and control continuous processes. Woodcliff Lake, NJ: World Batch Forum.

    Google Scholar 

  • Cheever, G., & Schroeder, J. (2007). Remote service. ABB Review Special Report Automation Systems. Retrieved from May 01, 2009, from http://bit.ly/Lybsh.

  • Clark, D. (2008). Optimum process scheduling. International Mining, Retrieved January 2008.

    Google Scholar 

  • Cutler, C. R., & Ramaker, B. L. (1980). Dynamic matrix control—A computer control algorithm. In Proceedings Joint American Control Conference, San Francisco.

    Google Scholar 

  • DeMarco, T. (1982). Controlling software projects: Management, measurement & estimation. New York: Yourdon Press.

    Google Scholar 

  • Ebel, M., Drath, R., & Sauer, O. (2008). Automatische Projektierung eines Produktionsleitsystems der Fertigungstechnik mit Hilfe des Datenaustauschformats CAEX’ In atp—Automatisierungstechnische Praxis 50, Heft 5, Seiten 84–92. München: Oldenburg Industrieverlag.

    Google Scholar 

  • Electric Power Research Institute Advanced Control Room Alarm System. (2005). Requirements and implementation guidance (ERPI report 1010076). Palo Alto.

    Google Scholar 

  • Farb, D., & Gordon, B. (2005). Agent GXP FDA Part 11guidebook. Los Angeles, CA: University of HealthCare.

    Google Scholar 

  • Franke, R., & Vogelbacher, L. (2006). Nonlinear model predictive control for cost optimal startup of steam power plants. Automatisierungstechnik, 54(12), 630.

    Article  Google Scholar 

  • Fritzson, P. (2004). Object-oriented modeling and simulation with Modelica 2.1. Piscataway, NJ: IEEE Press.

    Google Scholar 

  • Früh, K. F., & Maier, U. (2004). Handbuch der Prozessautomatisierung (3rd ed.). München, Germany: Oldenbourg Industrie.

    Google Scholar 

  • Ganz, C., & Layes, M. (1998). Modular turbine control software: A software architecture for the ABB gas turbine family control system. Second international workshop on development and evolution of software architectures for product families, Las Palmas.

    Google Scholar 

  • Garcia, R. G., & Gelle, E. (2006). Applying and adapting the IEC 61346 standard to industrial automation applications. IEEE Transaction on Industrial Informatics, 2(3), 185–191.

    Article  Google Scholar 

  • Garpinger, O. (2009). Design of Robust PID Controllers with Constrained Control Signal Activity (Licentiate Thesis). Lund University, Sweden.

    Google Scholar 

  • Grosspietsch, K. -E., & Kirrmann, H. (2002). Fehlertolerante Steuerungs- und Regelungssyteme. Automatisierungtechnik at, 50(8).

    Google Scholar 

  • Gutermuth, G., & Hausmanns, Ch. (2007). Kostenstruktur und Untergliederung von Automatisierungsprojekten. In atp—Automatisierungstechnische Praxis 49, Heft 11, Sieten 40–47. München: Oldenburg Industrieverlag.

    Google Scholar 

  • Hägglund, T. (1999). Automatic detection of sluggish control loops. Control Engineering Practice, 7, 1505–1511.

    Article  Google Scholar 

  • Hall, K. H., Staron, R. J., & Zoitl, A. (2009). Challenges to industry adoption of the IEC 61499 standard on event-based function blocks, downloaded from IEEE Xplore on March 25, 2009, 1-4244-0865-2/07.

    Google Scholar 

  • Harris, T. (1989). Assessment of control loop performance. The Canadian Journal of Chemical Engineering, 67, 856–861.

    Article  Google Scholar 

  • Hölscher, H., & Rader, J. (1986). Microcomputers in safety technique, An aid to orientation for developer and manufacturer. Rheinland, Germany: TÜV.

    Google Scholar 

  • Horch, A. (1999). A simple method for detection of stiction in process control loops. Control Engineering Practice, 7(10), 1221–1231.

    Article  Google Scholar 

  • IBM Globalization. (2009). www.ibm.com/software/globalization (Last retrieved May 22, 2009).

  • IEC 61508-3. (1998). Functional safety of electrical/electronic/programmable electronic safety-related systems—Software requirements. Geneva, Switzerland: IEC.

    Google Scholar 

  • IEC 61511. (2003). Functional safety—Safety instrumented systems for the process industry sector. Geneva, Switzerland: IEC.

    Google Scholar 

  • IEC 61511-1. (2008). Functional safety—Safety instrumented systems for the process industry sector -Part 1: Framework, definitions, system, hardware and software requirements. Geneva, Switzerland: IEC.

    Google Scholar 

  • IEC 61513. (2001). Nuclear power plants—Instrumentation and control for systems important to safety. Geneva, Switzerland: IEC.

    Google Scholar 

  • IEC 62061. (2005). Safety of machinery—Functional safety of safety-related electrical, electronic and programmable electronic control systems. Geneva, Switzerland: IEC.

    Google Scholar 

  • International Electrochemical Commission, IEC 61346. (1996). Industrial systems, installations and equipment, and industrial products—Structuring principle and reference designations. Parts 1–4.

    Google Scholar 

  • International Electrotechnical Commission. (2003). IEC 61131-3: Programmable controllers—Part 3: programming languages Edition 2.0.. Geneva, Switzerland: IEC. ISBN 2-8318-6653-7.

    Google Scholar 

  • International Electrotechnical Commission (IEC 61346). (1996). Industrial systems, installations and equipment and industrial products—Structuring principles and reference designations.

    Google Scholar 

  • International Electrotechnical Commission (IEC 61508–1). (1998). Functional safety of electrical/electronic/programmable electronic safety-related systems—General requirements. Geneva, Switzerland: IEC.

    Google Scholar 

  • International Electrotechnical Commission (IEC 61508–2). (2000). Functional safety of electrical/electronic/programmable electronic safety-related systems—Requirements for electrical/electronic programmable electronic safety-related systems. Geneva, Switzerland: IEC.

    Google Scholar 

  • International Electrotechnical Commission. (2006). IEC 61508: Functional safety of electrical/electronic/programmable electronic safety-related systems, Parts 1 to 4. Geneva, Switzerland.

    Google Scholar 

  • ISA-88.00.05. (2010). Batch control Part 5: Implementation models and terminology for modular equipment control (working draft standard). Research Triangle Park, NC: ISA.

    Google Scholar 

  • ISA-88.01. (1995). Batch control Part 1: Models and terminology (R2006). Research Triangle Park, NC: ISA. See also IEC 61512.

    Google Scholar 

  • Isaksson, A. J., & Graebe, S. F. (1999). Analytical PID parameter expressions for higher order systems. Automatica, 35(6), 1121–1130.

    Article  Google Scholar 

  • Isaksson, A. J., & Graebe, S. F. (2002). Derivative filter is an integral part of PID design. IEE Proceedings - Control Theory and Applications, 149(1), 41–45.

    Article  Google Scholar 

  • Jaikumar, R. (1993). 200 years to CIM. IEEE Spectrum, 30, 26–27.

    Article  Google Scholar 

  • Johannesson, G. (1994). Object-oriented process Automation with SattLine. Lund, Sweden: Studentlitteratur.

    Google Scholar 

  • John, K. H., & Tiegelkamp, M. (2001). IEC 61131-3: Programming industrial automation systems, English edition. Heidelberg, Germnay: Springer. ISBN 3-540-67752-6.

    Book  Google Scholar 

  • Kristiansson, B., & Lennartson, B. (2006). Robust tuning of PI and PID controllers. IEEE Control Systems Magazine, 26(1), 55–69.

    Article  Google Scholar 

  • Laubner, R., & Gohner, P. (1999). Prozessautomatisierung 2. New York: Springer. ISBN 3-540-65319-8.

    Book  Google Scholar 

  • Li, Y., Ang, K. H., & Chong, G. C. Y. (2006). Patents, software and hardware for PID control. IEEE Control Systems Magazine, 26(1), 42–54.

    Article  Google Scholar 

  • Liefeldt, A., Gutermuth, G., Beer, P., Basenach, S., & Alznauer, R. (2005). Effizientes Engineering—Begleitende Fortschrittskontrolle grober Projekte der Automatisierungstechnik. In atp—Automatisierungstechnische Praxis 47, Heft 7, Seiten 60–64.

    Google Scholar 

  • Maciejowski, J. M. (2002). Predictive control with constraints. Upper Saddle River, NJ: Prentice-Hall.

    Google Scholar 

  • Mahnke, W., Leitner, S. H., & Damm, M. (2009). OPC unified architecture. New York: Springer.

    Book  Google Scholar 

  • Meyer, B. (2000). Object-oriented software construction. Upper Saddle River, NJ: Prentice Hall.

    Google Scholar 

  • Microsoft Go Global Developer Center. (2009). msdn.microsoft.com/goglobal (Last retrieved May 22, 2009).

    Google Scholar 

  • Müller, J., Gote, M., & DeLeeuw, V. (2007, January). NAMUR Umfrage plant asset management, Automatisierungstechnische Praxis Atp.

    Google Scholar 

  • NAMUR NA 35. (2003). Abwicklung von PLT-Projekten/Handling PCT Projects, NAMUR Worksheet NA35, Version of March 24, 2003. Available from www.namur.de.

  • NAMUR NE 100. (2007). Use of lists of properties in process control engineering workflows. Namur Recommendation NE100, Version 3.1. of November 2, 2007. Available from www.namur.de.

  • Narasimhan, S., & Jordache, C. (1999). Data reconciliation and gross error detection. Houston, TX: Gulf Professional.

    Google Scholar 

  • O’Brien, L. (2002). Total automation business for the process industries world wide outlook—Market analysis and forecast through 2006. Boston, MA: ARC Advisory Group.

    Google Scholar 

  • O’Dwyer, A. (2006). Handbook of PI and PID controller tuning rules (2nd ed.). London: Imperial College Press.

    Book  Google Scholar 

  • OPC foundation. (2002). Alarms and events custom interface standard V1.1.

    Google Scholar 

  • OPC Foundation. (2002). Alarms and events custom interface standard version 1.10.

    Google Scholar 

  • OPC Foundation. (2008, December). Analyzer devices (Draft version 0.30.00).

    Google Scholar 

  • OPC Foundation. (2003). OPC foundation data access custom interface standard V3.00.

    Google Scholar 

  • OPC. (2009, February). OPC historical data access specification version 1.2 OPC UA Spec. Part 1—Concepts (version 1.01); OPC. (2009, February). UA Spec. Part 2—Security model (version 1.01); OPC. (2009, February). UA Spec. Part 3—Address space model (version 1.01); OPC. (2009, February). UA Spec. Part 4—Services (version 1.01); OPC. (2009, February). UA Spec. Part 5—Information model (version 1.01); OPC. (2009, February). UA Spec. Part 6—Mappings (version 1.0); OPC. (2009, February). UA Spec. Part 7—Profiles (version 1.0); OPC. (2009, February). UA Spec. Part 8—Data access (version 1.01); OPC (2007, November). UA Spec. Part 9—Alarms and conditions (Draft version 0.93q); OPC. (2007, January). UA Spec. Part 10—Programs (version 1.00); OPC. (2007, January). UA Spec. Part 11—Historical access (version 1.00); OPC. (2007, November). UA Spec. Part 12—Discovery (Draft version 1.00.03); OPC. (2008, July). UA Spec. Part 13—Aggregates (RC version 1.0); OPC. (2008, December). UA devices (Draft Version 0.75).

    Google Scholar 

  • Pettersson, J., Ledung, L., & Zhang, X. (2006). Decision support for Pulp Mill operations based on large-scale on-line optimization. In Preprints of Control Systems 2006, Tampere, Finland, Retrieved 6–8 June.

    Google Scholar 

  • Rao, C. V. (2000). Moving horizon strategies for the constrained monitoring and control of nonlinear discrete-time systems. Ph.D. Thesis, University of Wisconsin.

    Google Scholar 

  • Reierson, B. (2006, April). Myths and realities of asset optimization. Plant Engineering Retrieved from www.plantengineering.com/article/CA6308016.html.

  • Richalet, J., Rault, A., Testud, J. L., & Papon, J. (1978). Model predictive heuristic control: Applications to industrial processes. Automatica, 14, 413–428.

    Article  Google Scholar 

  • Rivera, D. E., & Morari, M. (1987). Control relevant model reduction problems for SISO H2, Hinf, and u-Controller synthesis. International Journal of Control, 46(2), 505–527.

    Article  Google Scholar 

  • Rode, M., Franke, R., & Krüger, M. (2003, March). Model predictive control for boiler start-up. ABB Review. Available from http://www.abb.com/abbreview.

  • Sarma, P., Chen, W. H. (2008). Applications of optimal control theory for efficient production optimization of realistic reservoirs. IPTC 12480, Paper presented at the International Petroleum Technology Conference help in Kuala Lumpur, Malaysia, Retrieved December 3–5, 2008.

    Google Scholar 

  • Samad, T., McLaughlin, P., & Lu, J. (2007). System architecture for process automation: Review and trends. Journal of Process Control, 17, 191–201.

    Article  Google Scholar 

  • Sauter, T. (2007). The continuing evolution of integration in manufacturing automation. IEEE Industrial Engineering Electronics Magazine, 1, 10–19.

    Article  Google Scholar 

  • Scholten, B. (2007). The road to integration: A guide to applying the ISA-95 standard in manufacturing. Research Triangle Park, NC: ISA.

    Google Scholar 

  • Seborg, D. E., Edgar, T. F., & Mellichamp, D. A. (2003). Process dynamics and control (2nd ed.). Hoboken, NJ: Wiley.

    Google Scholar 

  • Shobrys, D. E., & White, D. C. (2000). Planning, scheduling and control systems: Why can they not work together. Computers and Chemical Engineering, 24, 163–173.

    Article  Google Scholar 

  • Siewiorek, D. P., & Swarz, R. S. (1982). The theory and practice of reliable system design. Bedford, England: Digital Press. ISBN 0-932376-13-4.

    Google Scholar 

  • Skogestad, S. (2003). Simple analytic rules for model reduction and PID controller tuning. Journal of Process Control, 13, 291–309.

    Article  Google Scholar 

  • Song, F. J. (1996). Next generation of structural engineering automation systems. In Computing in civil engineering (pp. 494–500). New York.

    Google Scholar 

  • Thomasson, F. Y. (1995). Controller tuning methods. In N. J. Sell (Ed.), Process control fundamentals for the pulp and paper industry. Norcross, GA: TAPPI Press.

    Google Scholar 

  • Thornhill, N. F. (2005). Finding the source of nonlinearity in a process with plant-wide oscillation. IEEE Transactions on Control System Technology, 13, 434–443.

    Article  Google Scholar 

  • Thornhill, N. F., & Horch, A. (2007). Advances and new directions in plant-wide disturbance detection and diagnosis. Control Engineering Practice, 15, 1196–1206.

    Article  Google Scholar 

  • Thornhill, N. F., Shouk, M. A. A., & Shah, S. L. (2004). The impact of compression on data-driven process analyses. Journal of Process Control, 14, 389–398.

    Article  Google Scholar 

  • U.S. Food and Drug Administration. FDA 21 CFR Part 11. Available from http://www.fda.gov/cder/gmp/index.htm.

  • Unicode Consortium. (2006). The Unicode standard, version 5.0. Upper Saddle River, NJ: Addison-Wesley.

    Google Scholar 

  • Valdez, G., Sandberg, D. G., Immonen, P., & Matsko, T. (2008). Coordinated control and optimization of a complex industrial power plant. Power Engineering Magazine, pp.124–134. Retrieved November.

    Google Scholar 

  • VanDoren, V. (2008). Advances in control loop optimization. Control Engineering. Retrieved January 5, 2008, from http://www.controleng.com/article/CA6559117.html.

  • VDI/VDE. (2008). Plant asset management (PAM) in the process industry—Definition, model, task, benefit. VDI/VDE Guideline No. 2651.

    Google Scholar 

  • VDI/VDE 2182. (2007, August). VDI guideline IT security for industrial automation—General model, Sheet 1; Draft for comments. Gründruck VDI. Berlin, Germany: Beuth.

    Google Scholar 

  • Watson, M. J., Liakopoulos, A., Brzakovic, D., & Georgakis, C. (1995). Wavelet techniques in the compression of process data. In Proceedings of the American Control Conference, Seattle, WA.

    Google Scholar 

  • Whitt, M. D. (2004). Successful instrumentation and control systems design. Research Triangle Park, NC: ISA. ISBN 978-1-5617-992-1.

    Google Scholar 

  • Woods, D. D. (1995). The alarm problem and directed attention in dynamic fault management. Ergonomics, 38(11), 2371.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. 5G Automatika Ltd., 203-203 Colonnade Road, Ottawa, ON, Canada, K2E7K3

    Ananth Seshan

  2. Barrick Gold Corporation, 161 Bay Street, Suite 3700, Toronto, ON, Canada, M5J 2S1

    B. K. Gorain

Authors
  1. Ananth Seshan
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. B. K. Gorain
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ananth Seshan .

Editor information

Editors and Affiliations

  1. Process Research Ortech Inc., Mississauga, Ontario, Canada

    Vaikuntam Iyer Lakshmanan

  2. Process Research Ortech, Inc., Mississauga, Ontario, Canada

    Raja Roy

  3. RAM Consultants, Scottsdale, Arizona, USA

    V. Ramachandran

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Seshan, A., Gorain, B.K. (2016). An Integrated Mining and Metallurgical Enterprise Enabling Continuous Process Optimization. In: Lakshmanan, V., Roy, R., Ramachandran, V. (eds) Innovative Process Development in Metallurgical Industry. Springer, Cham. https://doi.org/10.1007/978-3-319-21599-0_11

Download citation

Publish with us

Policies and ethics

Search

Navigation