Optimisation of work flow

AeroSpace Technologies of Australia (ASTA) is a supplier of aircraft components for several of the world's major aircraft manufacturers. Its anticipation of a substantial increase in demand has led to concern as to its ability to satisfy customer imposed schedules. ASTA's main concern is scheduling at its five autoclaves. The autoclaves, which are large pressurised ovens in which components are cured before non destructive testing and final assembly, appear to be the bottlenecks in ASTA's manufacturing process. ASTA came to the Australian Mathematics-in-Industry Study Group (MISG) with the objective of developing an optimised loading plan for the autoclaves to improve their utilisation while meeting demand for final components. This report discusses the results of an intensive three day study by the MISG group working on the ASTA problem. Its findings were that: • Modifying the way in which Materials Requirements Planning (MRP) is used may usefully increase autoclave utilisation. • A single product which will account for 60% of factory hours could and should be scheduled separately. • It is feasible and very helpful to group products into a small number of sets with common autoclave processing requirements. • Integer programming models modelling the production line show considerable promise and should be developed further

Minimum Time Multi-UGV Surveillance

This chapter addresses the problem of concurrent task and path planning for a number of surveillance Unmanned Ground Vehicles (UGVs) such that a user defined area of interest is covered by the UGVs’ sensors in minimum time. We first formulate the problem, and show that it is in fact a generalization of the Multiple Traveling Salesmen Problem (MTSP), which is known to be N P-hard. We then propose a solution that decomposes the problem into three subproblems. The first is to find a maximal convex covering of the search area. Most results on static coverage use disjoint partitions of the search area, e.g., triangulation, to convert the continuous sensor positioning problem into a discrete one. However, by a simple example, we show that a highly overlapping set of maximal convex sets is better suited for minimum time coverage. The second subproblem is a combinatorial assignment and ordering of the sets in the cover. Since the Tabu search algorithm is known to perform well on various routing problems, we use it as a part of our proposed solution. Finally, the third subproblem utilizes a particular shortest path subroutine in order to find the vehicle paths, and calculate the overall objective function used in the Tabu search. The proposed algorithm is illustrated by a number of simulation examples