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TitleApplication of artificial intelligence technology to increase productivity, quality and energy efficiency in heavy industry
LicencePlease note the adoption of the Open Government Licence - Canada supersedes any previous licences.
AuthorSzladow, A J
Source 1995, 225 pages, Open Access logo Open Access
PublisherCanada Centre for Mineral and Energy Technology
Lang.English; French
Mediapaper; on-line; digital
File formatpdf (Adobe® Reader®)
SubjectsEconomics and Industry; Science and Technology; mineral industry; iron; cement, commodity; mining; petroleum industry; oil; gas; Artificial intelligence; Productivity; Energy efficiency; Quality control; Automation; Steel; Forestry industry; Pulp and paper industry
Illustrationsbar graphs; tables; flow diagrams; pie charts; histograms; sketches; schematic representations
ProgramGovernment of Canada, Green Plan
Released1995 01 01; 2019 08 22; 2019 09 23
Automate or emigrate have become the practices of North American heavy industry during the 1990's in order to compete with the inexpensive labour, rich resource base and low regulatory environments in Asia and South America. To automate means to develop human/machine systems with specialized problem-solving capabilities. It also means to capture human expertise and knowledge on a computer. A key element in heavy industry's automation strategies has been advanced system control technologies and, lately, Artificial Intelligence (AI) technologies.
This study assesses the applications and benefits of AI systems implemented in heavy industry. It focuses on intelligent systems aimed at increased productivity, quality and energy efficiency in five industrial sectors: iron and steel, cement, mining and metallurgy, oil and gas, and pulp and paper. The study identified 177 applications of intelligent technologies in the areas of process control and monitoring, scheduling and planning, fault diagnosis and maintenance, and design. It evaluated the benefits to be accrued from intelligent systems and listed examples of improvements in productivity, quality and energy efficiency in each of the above application areas. The study also assessed the critical issues associated with, and barriers to, application of intelligent systems in the industry, based on interviews and a survey of developers and users of intelligent systems.
In addition to the industry-wide assessment, the study looked at intelligent systems implemented or demonstrated in each of the five sectors. For each sector, a summary of the systems implemented by the application type, geographic location and technology used has been compiled including descriptions of the systems. In total, 177 intelligent applications are described for the five sectors - 57 systems with detailed information on developers, implementation methods, and cost and benefits, and 120 systems with general information on solutions applied and benefits reported. As a supplement to this study, two appendices were prepared containing a comprehensive review of the AI tools available for development of intelligent systems, and the current AI trends and markets.
The study shows that although they are relatively new to the industry, AI technologies offer attractive solutions for the development of advanced control systems, management of production workflow, and training of staff. In addition to productivity and quality improvements, intelligent systems can significantly reduce energy use in energy intensive operations through better control and scheduling of production, and reduction of work disruptions. Intelligent technologies are no longer a concept or a program for tomorrow. They are a realistic solution for today's problems in heavy industry.

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