Optimizing a disassembly process involves maximizing the number of disassembled valuable parts (cores) and minimizing the number of disassembly operations. Usually, some disassembly operations are in common among two or more cores, or sometimes removing a core requires prior removal of other cores (known as precedence relations); these correlations complicate the allocation of the disassembly cost to the cores. To overcome this complexity, the current optimization methods (decision trees) determine the optimum sequence of disassembly operations rather than the optimum set of cores to be disassembled. These methods become difficult to implement when the number of cores increases. In this paper, we developed a mechanized nongraphical approach to determine the optimum set of cores to be disassembled and their required disassembly operations based on the functionality statuses of the cores. This approach introduces a new characterization of the disassembly process and its precedence relations, and can be implemented conveniently using computer codes even when the product consists of many cores. The application of the method is explained with an example. Using this example, it was shown that the optimum disassembly can increase the net profit significantly compared with the complete disassembly.

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