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The two-volume set IFIP AICT 535 and 536 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2018, held in Seoul, South Korea, in August 2018. The 129 revised full papers presented were carefully reviewed and selected from 149 submissions. They are organized in the following topical sections: lean and green manufacturing; operations management in engineer-to-order manufacturing; product-service systems, customer-driven innovation and value co-creation; collaborative networks; smart production for mass customization; global supply chain management; knowledge based production planning and control; knowledge based engineering; intelligent diagnostics and maintenance solutions for smart manufacturing; service engineering based on smart manufacturing capabilities; smart city interoperability and cross-platform implementation; manufacturing performance management in smart factories; industry 4.0 - digital twin; industry 4.0 - smart factory; and industry 4.0 - collaborative cyber-physical production and human systems.
The papers in this volume are the Applications papers presented at ES 2000, the Twentieth SGES International Conference on Knowledge Based Systems and Applied Artificial Intelligence, held in Cambridge in December 2000. The scope of the Application papers has expanded over recent years to cover not just innovative applications using traditional knowledge based systems, but also to include applications demonstrating the whole range of AI technologies. These papers continue to illustrate the maturity of AI as a commercially viable technology to solve real world problems. This is the eighth volume in the Applications and Innovations in Intelligent Systems series. The series serves as a key reference as to how AI technology has enabled organisations to solve complex problems and gain significant business benefits. The Technical Stream papers from ES 200 are published as a companion volume under the title Research and Development in Intelligent Systems XVII.
A comprehensive, one-stop synthesis of landslide science, for researchers and graduate students in geomorphology, engineering geology and geophysics.
This book illustrates how mine seismology can be used to improve underground safety standards. It describes several preventive actions that have been put into practice at the 5B Area of No. 5 Shaft Vaal Reefs gold mine after issuing seismic warnings. These included additional safety pillars, changes in mining sequences and directions, and a review of the mining strategy for the entire 5B area. The presented experiment with seismic warning concept was a success because it was an internal mine project. Further, the Vaal Reefs management adopted the philosophy that the success rate should be measured in the preventive actions taken, not in the success of the prediction itself. Reviewing these and other aspects, the book clearly demonstrates how mine seismology can effectively improve underground safety standards. Stefan Glazer’s book (...) addresses in a very comprehensive manner both technical and practical problems of implementing and then effectively using microseismic networks and data. (...) Stefan proves that through comprehensive microseismic data analysis the location of potential rock burst can be assessed and then prevention action plans can be developed, providing more confidence to management and workers that deposit[s] can be mine[d] safely. Michal Stawski, VP Strategic Geomechanical Specialist, PT Freeport Indonesia I began reading this story expecting to find a technical review of the science of seismology and its application in mining, [but] this book is much more than that. (...) This is a must-read for those managing seismically active mines and should provide a wake-up call to the industry as the complex morality surrounding the management of seismic risk needs to be clarified in order for this to advance. Eric Strom, Director Underground Mining, New Gold Inc. As a mining geotechnical practitioner having experience in large open pit and underground massive mining operations, I have learned that mining induced seismicity can have a significant impact on the safety and economics of operations. However, seismicity is a complex field that is generally left to specialists with little input from geotechnical engineers and engineering geologists. (...) This is a must read for mine seismologists, geotechnical practitioners and mining engineers alike, and will be a welcome and much needed addition to my own book cabinet. This will be [an] invaluable work as our industry progresses to the mining of new depths in both the underground and open pit environments. Desmond Mossop Pr.Sci.Nat., Principal Engineering Geologist, SRK Consulting
In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time. Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results. From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing. Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in your company’s data. The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them a business framework in which to assess the value, cost, and risk of potential analytical solutions. In addition, the book will provide the next generation of miners – undergraduate and graduate IT and mining engineering students – with an understanding of data analytics applied to the mining industry. By providing a book with chapters structured in line with the mining value chain, we will provide a clear, enterprise-level view of where and how advanced data analytics can best be applied. This book highlights the potential to interconnect activities in the mining enterprise better. Furthermore, the book explores the opportunities for optimization and increased productivity offered by better interoperability along the mining value chain – in line with the emerging vision of creating a digital mine with much-enhanced capabilities for modeling, simulation, and the use of digital twins – in line with leading “digital” industries.