Generation of Optimized Robotic Assembly Sequence using Soft Computing Methods

The assembly process is one of the most time consuming and expensive manufacturing activities. The cost of assembly on an average is 10-30% of the manufacturing cost of a commercial product. The ratio between cost and performance of assembly has gradually increased with respect to the other phases of the manufacturing process and in recent years, this fact has caused a growing interest by industry in this area. Robotic assembly system which comes under the automated assembly system ncorporates the use of robots for performing the necessary assembly tasks. This is one of the most flexible assembly systems to assemble various parts into desired assembly (usable end-product). Robotic assembly systems are the programmable and have the flexibility to handle a wide range of styles and products, to assemble the same products in different ways, and to recover from errors. Robotic assembly has the advantage of greater process capability and scalability. It is faster, more efficient and precise than any conventional process. A variety of optimization tools are available for application to the problem. It is difficult to model the present problem as an n-p problem. Finding the best sequence generation involves the conventional or soft-computing methods by following the procedures of search algorithms