RFID-enabled real-time advanced planning and scheduling shell for production decision making

Abstract

In a radio frequency identification (RFID)-enabled real-time manufacturing environment, different decision makers are often confronted with the inconsistency between the highly synchronised information flow and unstandardised decision-making procedures, especially under conflicting objectives and dynamic situations. This study proposes an RFID-enabled real-time advanced production planning and scheduling shell (RAPShell, in short) to coordinate different decision makers across production processes. RAPShell has several key innovations. First, it uses RFID technology for enhancing information sharing, which provides the basis for coordinating decisions and operations of different parties involved in production planning, scheduling, execution and control. Second, it adopts Software as a Service (SaaS) model and a standard service-oriented architecture (SOA) with key modules, adaptive optimisation models, solution algorithms as well as scheduling rules developed and deployed as web services. Finally, extensible makeup language (XML)-based data models are utilised to achieve easy-to-deploy and simple-to-use system customisation and implementation. A case study demonstrates how RAPShell is customised and deployed in a small- and medium-sized company to facilitate the operations of typical production decision makers and operators. Benefits from qualitative and quantitative are discussed from the case study to show RAPShell's practical effectiveness and efficiency on production decision making.

Keywords:

• advanced planning and scheduling
• radio frequency identification
• real-time
• Software as a Service
• service-oriented architecture
• web service

Acknowledgements

Authors acknowledge financial support from 2009 Guangdong Modern Information Service Fund (GDIID2009IS048), 2010 Guangdong Department of Science and Technology Fund (2010B050100023), 2010 and 2011 National Nature Science Foundation of China (61074146, 51105081), International Collaborative Project of Guangdong High Education Institution (gjhz1005) and Key Laboratory of Internet of Manufacturing Things Technology and Engineering of Development and Reform Commission of Guangdong Province. Special thanks are given to our industrial collaborators and to Sunflower Gantt Chart for technical support.