Abstract : E ective conduct with End of Life (EOL) products is a hot research topic in
green and smart manufacturing. For EOL product recycling and remanufacturing,
a fundamental problem is to design an effcient disassembly line under
consideration of stochastic task processing times. This problem focuses on
selecting alternative task processes, determining the number of opened workstations,
and assigning operational tasks to the workstations. The goal is to
minimize the total cost consisting of workstation operational cost and hazardous
component processing cost. Most existing works assume that the
probability distribution of task processing times can be estimated, however,
it is often not likely to access the complete probability distribution due to
various difficulties. Therefore, this study investigates disassembly line design
with the assumption that only the mean, standard deviation and an upper
bound of task processing times are known. Our main contributions include:
(i) a new decomposition color graph is proposed to intuitively describe all
possible processes, (ii) a new distribution-free model is proposed, and (iii)
some problem properties are established to solve the model. Experimental
results show that the distribution-free model can effectively deal with
stochastic task processing times without given probability distributions.
