Assembly line balancing has gotten a considerable
place in industrial importance. Hence, a lot of
researchers are interested in this subject and several papers
have been published until now. Many exact, heuristic,
meta-heuristic, and hybrid approaches have been used to
solve this type of problems. Different rules are applied for
line balancing such as rank positional weight (RPW).
Assembly line balancing problems are considered mostly
in definite status, while the nature of manufacturing
systems is accompanied with uncertainty. In this paper,
we propose a model based on RPW algorithm considering
uncertain time parameters for stochastic assembly line
balancing. Also, two other methodologies of normal
distribution integration and Monte Carlo simulation are
developed. The effectiveness of the proposed model and
validity testing with respect to other two approaches are
illustrated using numerical examples.