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Explains and demonstrates techniques for solving large-scale production scheduling and planning problems in the process industries Bridges the gap between theory and practice in planning and scheduling Includes 78 illustrations, additional online material, and case studies highlighting real-world applications at leading firms in the process industry
Auteur
Georgios M. Kopanos is a Senior Scientist and the Optimisation Leader at Flexciton Ltd (United Kingdom). He holds an MSc in Engineering and Management of Energy Resources from the University of Western Macedonia (Greece), and a PhD from the Universitat Politecnica de Catalunya (Spain) sponsored by the Spanish Ministry of Education. He was a Postgraduate Research Associate in the Centre for Process Systems Engineering at Imperial College London (United Kingdom), an Assistant Professor in the School of Engineering at Nazarbayev University (Kazakhstan), and later a Lecturer in Process Systems Engineering at Cranfield University (United Kingdom). He has solved successfully large-scale production planning and scheduling problems for major industries from several sectors, such as food industries (including dairy as well as meat and fish processing industries), breweries, pharmaceuticals industries, textile industries, detergents industries, combined heat and power plants, and air separation plants.
Dr. Luis Puigjaner is Professor Emeritus of Chemical Engineering at the Universitat Politècnica de Catalunya (UPC) and Senior Director of the Centre for Process and Environmental Engineering (CEPIMA) at UPC, a non-profit agency for engineering services and environment audit. He graduated with honours obtaining the B.S.E.E. and M.S. (Engineering) from the Polytechnic University of Catalunya and the Ph.D. degree from the Polytechnic University of Madrid. He holds also M.S. and M.A. degrees from the University of Houston (Fulbright outstanding scholar achievement award) and University of Barcelona respectively. Professional experience includes teaching and research: NASA-Houston; Purdue U; U California-Berkeley; U California-Davis; IBM-San Jose Res Center; Stanford U; M.I.T.; Max Planck Institute; King's College London; U of Houston; Imperial College London; Cork Tech College; UNAM; UNICAMP; Hungarian Aca Sciences; Russian Aca. Sciences. Guest lecturer (Laudatio), Technishe Universität Dortmund (2012). Doctor Honoris Causa, UPB, Bucharest (2017). He has been Responsible scientist and partner leader: 45 EU sponsored projects (Programs JOULE, ESPRIT, BRITE, ECSC, APAS, GROWTH, IMS, IST INCO and FP7); 2 US-Spain projects; 37 national projects (CAICYT, CICYT, CIRIT, CEDETI, PROFIT, P4, Generalitat de Catalunya); over 100 projects industry supported; 26 TEMPUS and INTAS actions. Main research interests include Process Systems Engineering, Computer Aided Process Engineering and Biological Systems modeling simulation and optimization. He is the founder of CIMADE a leader Spin-off Company, which successfully commercialized MOPP & BOLD, the most advanced software created early 1995 for Design and Retrofit, Planning and Scheduling at large industrial scale, for batch, semi-continuous and continuous applications successfully implanted, by Companies like Bayer, Coca-Cola, DAMM, Francolor, Punto Blanco, etc. Academic aplications include, Purdue University, UPC.
Contenu
Part I: Overview.- Introduction.- State of the Art.- Methods and Tools.- Part II: Continuous Processes.- Production Planning and Scheduling of Parallel Continuous Processes.- Part III: Semicontinuous Processes.- Production Scheduling in Multistage Semicontinuous Process Industries.- Resource-Constrained Production Planning and Scheduling in Semicontinuous Process Industries.- Simultaneous Optimization of Production & Logistics Operations in Semicontinuous Process Industries.- Part IV: Batch Processes.- Production Scheduling in Large-Scale Multistage Batch Process Industries. Part V: Integrated-System Approach.- Integrated Operational and Maintenance Planning of Production and Utility Systems.- Part VI: Conclusions and Outlook.- Appendixes.