Novel project and operations management strategies to adapt cyclical mineral industries to a new industry age and circular economy

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The Industry 4.0 heralds a revolution and proposes new ways to increase the performance and flexibility of industrial processes. Meanwhile, circular economy concepts penetrate the industrial world, encouraging a further reduction in environmental impacts and waste quantities. The Industry 4.0 and circular economy pose new production and management challenges to industrial operations to maximize utility and value creation. ***The mining industry must not remain indifferent to these challenges. First, a mining operation comprises a value chain involved in the conversion of rock or other raw material to an intermediate saleable product. Within the chain, process control and interdependencies are extremely complicated. The mining sector also has structural characteristics of cyclicality, resource degradation, complex market dynamics, mine-specific constraints, and high uncertainty. Intricate precedence relationships among these processes further complicate operation management, as do internal challenges of each operation. Finally, sparse data lead to poor predictions and technical risks. ***This research program proposes cutting-edge advancements through machine learning and artificial intelligence with the aid of “big data” obtained from digitalization (e.g., sensors, automation, wireless communication, radar, robotics, cloud computing, and the internet of things) and from cognitive science, which traces human behavior. The research will also be extended to incorporate human factors, ergonomics, human-computer relations, decision analysis, and systems engineering into mine operation and maintenance planning throughout cognitive engineering in such a way as to understand mechanisms affecting interactions among human intelligence, processes, and equipment. Additional goals are real-time online optimization, as well as reactive and proactive optimization strategies. ***Throughout this five-year program, two MEng and two Ph.D. students will be trained, contributing to a new generation of mining engineers who specialize in data analytics, modeling, and optimization through machine learning and cognitive engineering. ***The outcome of this research proposal will be novel mine operation and project management strategies for the mining industry. Hence, process plant and machine efficiencies will be increased through more accurate and detailed design; resilient planning and scheduling; mine optimization; orebody characterization; environmental and safety management; equipment prognostics; and reliability, availability, and maintenance approaches that follow Industry 4.0 and circular economy concepts. ***This research will help the Canadian mining industry to grasp the new industrial revolution and acquire new tools to increase the productivity, environmental compliance, performance, and efficiency of mining operations.