Industrial optimization lies on the crossroads between mathematics, computer science, engineering and management. This book presents these fields in interdependence as a conversation between theoretical aspects of mathematics and computer science and the mathematical field of optimization theory at a practical level. The 19 case studies that were conducted by the author in real enterprises in cooperation and co-authorship with some of the leading industrial enterprises, including RWE, Vattenfall, EDF, PetroChina, Vestolit, Sasol, and Hella, illustrate the results that may be reasonably expected from an optimization project in a commercial enterprise. The book is aimed at persons working in industrial facilities as managers or engineers; it is also suitable for university students and their professors as an illustration of how the academic material may be used in real life. It will not make its reader a mathematician but it will help its reader in improving his plant.
This book describes different approaches for solving industrial problems like product design, process optimization, quality enhancement, productivity improvement and cost minimization. Several optimization techniques are described. The book covers case studies on the applications of classical as well as evolutionary and swarm optimization tools for solving industrial issues. The content is very helpful for industry personnel, particularly engineers from the Operation, R&D and Quality Assurance sectors, and also the academic researchers of different engineering and/or business administration background.
This book highlights the analytics and optimization issues in industry, to propose new approaches, and to present applications of innovative approaches in real facilities. In the past few decades there has been an exponential rise in the application of artificial intelligence for solving complex and intricate problems arising in industrial domain. The versatility of these techniques have made them a favorite among scientists and researchers working in diverse areas. The book is edited to serve a broad readership, including computer scientists, medical professionals, and mathematicians interested in studying computational intelligence and their applications. It will also be helpful for researchers, graduate and undergraduate students with an interest in the fields of Artificial Intelligence and Industrial problems. This book will be a useful resource for researchers, academicians as well as professionals interested in the highly interdisciplinary field of Artificial Intelligence.
In Optimization of Industrial Unit Processes, the term "optimization" means the maximizing of productivity and safety while minimizing operating costs. In a fully optimized plant, efficiency and productivity are continuously maximized while levels, temperatures, pressures, or flows float within their allowable limits. This control philosophy differs from earlier approaches - where levels and temperatures were controlled at constant values, and plant productivity was only an accidental, uncontrolled consequence of those controlled variables. With this approach, the sides of a multivariable control envelope are the various constraints while inside the envelope the process is continuously moved to maximize efficiency and productivity. Because one must understand a process before one can control it (let alone optimize it), Optimization of Industrial Unit Processes discusses the "personality" and characteristics of each process in term of its time constants, gains, and other unique features. This book provides information for engineers who design or operate industrial plants and who seek to increase the profitability of their plants. It recognizes that all industrial processes involve operations such as material transportation, heat transfer, and reactions. Therefore each plant consists of a combination of basic unit operations and can be optimized by maximizing the efficiency, and minimizing the operating cost, of the individual unit operations from which it is composed. Optimization of Industrial Unit Processes discusses real world processes - where pipes leak, sensors plug, and pumps cavitate - offering practical solutions to real problems. Each control system described in the book works, illustrating the state of the art in controlling a particular unit operation. This second edition reflects the continual improvement and evolution of control systems as well as anticipates future advances. Béla G. Lipták speaks on Post-Oil Energy Technology on the AT&T Tech Channel.
This book presents recent advances in optimization and control methods with applications to industrial engineering and construction management. It consists of 15 chapters authored by recognized experts in a variety of fields including control and operation research, industrial engineering and project management. Topics include numerical methods in unconstrained optimization, robust optimal control problems, set splitting problems, optimum confidence interval analysis, a monitoring networks optimization survey, distributed fault detection, nonferrous industrial optimization approaches, neural networks in traffic flows, economic scheduling of CCHP systems, a project scheduling optimization survey, lean and agile construction project management, practical construction projects in Hong Kong, dynamic project management, production control in PC4P and target contracts optimization. The book offers a valuable reference work for scientists, engineers, researchers and practitioners in industrial engineering and construction management.
As optimization techniques have developed, a gap has arisen between the people devising the methods and the people who actually need to use them. Research into methods is necessarily long-term and located usually in academic establishments; whereas the application of an optimization technique, normally in an industrial environment, has to be justified financially in the short term. The gap is probably inevitable; but there is no need for textbooks to reflect it. Teaching of optimization techniques separately from their connection with applications is pointless. This book gives a detailed exposition of the techniques. In this first volume, T. A. J. Nicholson demonstrates the full range of techniques available to the practitioner for the solution of varying problems. For each technique, the background reasoning behind its development is explained in simple terms; where helpful it is supported by a geometrical argument; and the iterative algorithm for finding the optimum is defined clearly. These steps enable the reader not only to see plainly what is happening in the method but also to reach a level of understanding necessary to write computer programs for optimization techniques. Problems are tackled in the same way--by searching a feasible region for an optimum. This approach helps the reader to develop the most essential of all skills--selecting appropriate techniques for different circumstances. The numerous worked examples in the text, supported by worked solutions, and the exercises at the end of the chapters are important aids to learning and to teachers. This book serves as an introduction to optimization techniques for students as well as a reference work for the practitioner in business and industry.
This book offers a broad, in-depth overview that reflects the requirements, possibilities and limits of mathematical optimization and, especially, stochastic optimization in the energy industry.
Delves into the core and functional areas in the upstream oil and gas industry covering a wide range of operations and processes Oil and gas exploration and production (E&P) activities are costly, risky and technology-intensive. With the rise in global demand for oil and fast depletion of easy reserves, the search for oil is directed to more difficult areas – deepwater, arctic region, hostile terrains; and future production is expected to come from increasingly difficult reserves – deeper horizon, low quality crude. All these are making E&P activities even more challenging in terms of operations, technology, cost and risk. Therefore, it is necessary to use scarce resources judiciously and optimize strategies, cost and capital, and improve business performance in all spheres of E&P business. Optimization and Business Improvement Studies in Upstream Oil and Gas Industry contains eleven real-life optimization and business improvement studies that delve into the core E&P activities and functional areas covering a wide range of operations and processes. It uses various quantitative and qualitative techniques, such as Linear Programing, Queuing theory, Critical Path Analysis, Economic analysis, Best Practices Benchmark, Business Process Simplification etc. to optimize Productivity of drilling operations Controllable rig time loss Deepwater exploration strategy Rig move time and activity schedule Offshore supply vessel fleet size Supply chain management system Strategic workforce and human resource productivity Base oil price for a country Standardize consumption of materials Develop uniform safety standards for offshore installations Improve organizational efficiency through business process simplification The book will be of immense interest to practicing managers, professionals and employees at all levels/ disciplines in oil and gas industry. It will also be useful to academicians, scholars, educational institutes, energy research institutes, and consultants dealing with oil and gas. The work can be used as a practical guide to upstream professionals and students in petroleum engineering programs.
This collection of challenging and well-designed test problems arising in literature studies also contains a wide spectrum of applications, including pooling/blending operations, heat exchanger network synthesis, homogeneous azeotropic separation, and dynamic optimization and optimal control problems.
In a world with highly competitive markets and economic instability due to capitalization, industrial competition has increasingly intensified. In order for many industries to survive and succeed, they need to develop highly effective coordination between supply chain partners, dynamic collaborative and strategic alliance relationships, and efficient logistics and supply chain network designs. Consequently, in the past decade, there has been an explosion of interest among academic researchers and industrial practitioners in innovative supply chain and logistics models, algorithms, and coordination policies. Mathematically distinct from classical supply chain management, this emerging research area has been proven to be useful and applicable to a wide variety of industries. This book brings together recent advances in supply chain and logistics research and computational optimization that apply to a collaborative environment in the enterprise.
