BUS606: Operations and Supply Chain Management

Assembly Line method has become a popular and important technique in production involving high volume. In view of its low cost production it has gradually replaced the traditional production methods.

Given a set of independent, identifiable and indivisible tasks of various durations, a set of precedence constraints among the tasks, one has to assign each taskto exactly one workstation in such a way that no precedence constraint is violated and the assignment is complete and optimal in some sense. By precedence constraints we mean the technical restriction which demands the completion of some tasks before undertaking another task. Thus, Balancing of Assembly line, which is a very high rate of output ensuring difficult optimization problem, is restricted by precedence constraints, and cycle time constraints.

Attempts to solve the line balancing problems started during 1950s. Initially, the main focus was to design and configure workstations and assign tasks to workstations in a heuristic manner. Bowman first considered the linear programming approach to arrive at an optimum solution tothe line balancing problem. Thereafter, several researchers used different optimization techniques for solving the problem of line balancing. Hoffman, Mansoor and Yadin and Geoffrion used mathematical programming approach to present a clear formulation of the problem and arrive at the solution. Baxey emphasized on the configuration of multiple workstations. Later, Integer programming procedure was used by Graves and Lamer for designing an assembly system. Sarin and Erel developed a cost model for the single product assembly line balancing problem for minimizing the total labour cost. Berger et al adopted Branch-and-bound algorithms for the multi-product assembly line balancing problem. The problem of balancing assembly lines with stochastic task processing times using simulated annealing was addressed by Suresh and Sahu. Pinnoi and Wilhelm used the branch and cut approach for system design. In 2002, Nicosia et al introduced the concept of cost and studied the problem of assigning operations to an ordered sequence of non-identical workstations, which also took into consideration the precedence relationships and cycle time restrictions. Erel et al presented a beam search-based method for the stochastic assembly line balancing problem in U-lines. Zhao et al dealt with sequence-to-customer goal with stochastic demands for a mixed-model assembly line for minimizing the number of stations. In 2006, a branch-and-bound based solution was proposed by Bukchin and Rabinowitch. Gu et al tried to solve assembly line balancing problem by estimation of distribution. Agarwal and Tiwari proposed a collaborative ant colony algorithm to stochastic mixed-model U-shaped disassembly line balancing and sequencing problem. Gamberini et al presented a multiple single-pass heuristic algorithm solving the problem of stochastic assembly line rebalancing. Roy and Khan addressed the optimization of an integrated line balancing process with workstation inventory management. Roy and Khan also tried to balance assembly line by minimizing balancing loss and system loss.