An immune algorithm approach to the scheduling of a flexible PCB flow shop

Scheduling is an important task in manufacturing. It involves assigning jobs to machines in a particular order so as to meet the manufacturing target. With the increase in manufacturing complexity, conventional scheduling techniques for generating a reasonable manufacturing schedule have become ineffective. An immune algorithm (IA), which is a new evolutionary algorithm, can be used to tackle complex scheduling problems and produce a reasonable manufacturing schedule within an acceptable time. This paper describes an IA approach to the scheduling of a flexible flow shop for PCB manufacturing. An overview of the flexible flow shop problem and the basic notions of an IA are first presented. Subsequently, the details of an IA approach are described and implemented. A case study of a flexible flow shop for the manufacture of PCBs for communication equipment was then conducted. The results obtained are compared with those computed by genetic algorithms (GAs), which are well-known evolutionary algorithms. From the case study, it was established that IAs outperformed GAs. The details of the case study as well as the comparative study are described.