A production schedule generator framework for pattern sequential mining

Scheduling is one of the fields that are crucial in the manufacturing industry. A good schedule improves productivity and may help in making related production decision. This paper proposes a schedule generator framework for mining sequential patterns in the production schedules. The aim of this study is to produce knowledge pattern through a set of sequence rules. This framework consists of a few phases of sequential pattern mining to extract certain patterns or knowledge embedded in schedules. The pattern or knowledge produced by this framework is illustrated in two ways that are comprised of a set of sequence rules and a set of frequent schedules.