Master assembly network for alternative assembly sequences

Abstract

The fourth industrial revolution (I 4.0) is paving the way for change in manufacturing systems. A logical enabler for dynamic and adaptive manufacturing systems including smart automated guided vehicles (AGVs) is presented. It can respond to requests for changing operations sequences received digitally or via distributed sensors, and change the processing route according to pre-planned flow sequences and pre-determined alternatives. A novel method for generating a master assembly network with alternative sequences based on legacy assembly data for a product family is developed. A master assembly network is a generic multiple alternative assembly sequences for a group of product variants belonging to a family where they share some parts and have common product structure. The assembly network with alternative sequences for a new variant is extracted from the master assembly network. These alternative sequences increase the flexibility and adaptability of the assembly system to handle workshop disruptions such as change orders, machine breakdowns and tool failures. The developed method is inspired by the phylogenetic networks used in biology, namely the soft-wired galled network. A Genetic Algorithm is developed to generate the master assembly network that summarizes a set of conflicting rooted assembly sequence trees. A family of three control valves is used as a case study. The proposed method can be utilized in any manufacturing system that use alternative assembly sequence including those utilizing smart AGVs in and Industry 4.0 dynamic environment. The developed method decreases the time and cost of introducing a new product variant as well as increases the responsiveness of the manufacturing system.