Track: Artificial Intelligence

Abstract

Recent manufacturing confronted with high variety, low volume market demands, shorter manufacturing cycle times and huge fluctuations in production. In particular, developing countries like India have huge number of skilled workers but due to lack of proper training for skilled and multi-skilled workers, the manufacturing organizations not reaching their current customized requirements. The proposed Networked seru production offers great advantages to cope with the above mentioned requirements. Thus, it is necessary to reconfigure the  traditional conveyor lines using in current manufacturing systems with the seru production systems which is possible to achieve high flexibility of job shop and high efficiency of conveyer assembly lines. In this paper, we investigate the training and assaignment problem of workers on multiple reconfigured serus located on network of enterprises. Thereafter, with Ontology, knowledge has been converted into Extensible Markup Language (XML) schema of Web Ontology Language (OWL) documents to enhance the Interoperability of product data models and manufacturing resources located in a network. Moreover, a single-objective mathematical model has been developed to minimize total training cost, total processing times of each multi-skilled worker. Finally, case of Indian Electronics Company is solved with developed heuristic and multi-objective evolutionary algorithm.