Development of an integrated scheduling algorithm for operations management in the analytical services sector

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Actlabs is a company that provides end-to-end testing services, required by mining and exploration companies at every step of a mine's lifecycle in order to be able to proceed with development. Increased demand placed on testing laboratories by the mining and exploration companies over the last decade has lengthened turnaround times for Actlabs' customers, increasing the timeline for mine development and commissioning and resulting in high costs for mining companies due to delays or bad decisions taken when analyses results are not available on time. While capacity has increased in the industry, smart operations management systems have not kept pace, which has led to marginal improvement in efficiency, productivity and only marginal turnaround time improvements. Thus, it is imperative to develop a more efficient way to manage operations, shorten turnaround times and reduce costs for the mining industry. Actlabs has teamed up with researchers from the University of Waterloo to develop a computational-based infrastructure to improve their operations management. A scheduling algorithm that considers the stochastic nature of the demands, the processes (i.e. random quality failures) and the test results, as well as the optimal allocation of technical staff to the various services provided by Actlabs will be developed in this project. Due to the nature of the operations, new approaches will be developed to account for specific operational characteristics that may only occur in analytical services facilities. Although stochastic scheduling and personal reallocation have been widely studied in the literature, these techniques have not been applied to efficiently schedule operations management in the analytical services sector. This proposal aims to tackle these new challenges and train two graduate students while doing so, all while generating direct benefits to Actlabs and hence to Canada's mining sector.