Total completion time minimization in a drilling sequence problem considering tool wear:an Ant algorithms approach

Abstract

Drilling is one of the most common machining operations. An Aircraft skin consists of hundreds of different-sized holes distributed over a large area. Automated drilling/riveting machines are used today to perform the drilling/riveting process on large aircraft skins. These machines are capital intensive and their maximum utilization is vital to their economic viability. An issue that affects the utilization of these machines is the drilling sequence because usually there is ’n’ number of holes that has to be visited. Determination of drilling sequence is similar to a Traveling Salesman Problem (TSP) and exhibits characteristics of an NP-hard problem. Two types of setups complicate this process further. Depending on the size of the holes, different-sized drills are selected, each size requiring a different setup for changing the tool. Also, as holes are drilled, the drill bits wear out and need to be replaced at the end of their tool life. This thesis presents an Ant-algorithm meta-heuristic to solve this sequencing problem. Results indicate that the procedure is effective in arriving at good solutions.