Smart Objects System: A Generic System for Enhancing Operational Control

Many companies are making considerable investments in tracking technology, such as GPS and RFID. Although tracking technology captures vast amounts of information about the ongoing operations, companies struggle to effectively apply this captured information for enhancing their operational control. In order to contribute in solving this problem, this paper presents a generic system for enhancing operational control, which applies the captured information in a more effective way. The proposed system is based on the approach of intelligent products. The intelligent products represent physical objects, and are capable of autonomously performing some of the repetitive tasks required for operational control. The usefulness of the system is demonstrated by presenting the results of several applications of the system.

[1]  C. de Snoo,et al.  An empirical investigation of scheduling performance criteria , 2011 .

[2]  Rebecca Angeles,et al.  Rfid Technologies: Supply-Chain Applications and Implementation Issues , 2004, Inf. Syst. Manag..

[3]  Samir Chatterjee,et al.  A Design Science Research Methodology for Information Systems Research , 2008 .

[4]  Gerben G. Meyer,et al.  Effective monitoring and control with intelligent products , 2011 .

[5]  Jan Holmström,et al.  Intelligent Products: A survey , 2009, Comput. Ind..

[6]  Jan Holmström,et al.  Benefits of an item-centric enterprise-data model in logistics services: A case study , 2007, Comput. Ind..

[7]  Carles Sierra,et al.  Agent-Mediated Electronic Commerce , 2004, Autonomous Agents and Multi-Agent Systems.

[8]  Michel Gendreau,et al.  Intelligent Freight Transportation Systems : Assessment and the Contribution of Operations Research , 2009 .

[9]  Hans Wortmann,et al.  Robust Planning and Control Using Intelligent Products , 2009, AMEC/TADA.

[10]  Hendrik Van Brussel,et al.  Intelligent products: Agere versus Essere , 2009, Comput. Ind..

[11]  John Collins,et al.  The Supply Chain Management Game for the 2007 Trading Agent Competition , 2004 .

[12]  Karlos Artto,et al.  Intelligent products - a step towards a more effective project delivery chain , 2003, Comput. Ind..

[13]  Kenneth N. McKay,et al.  Practical Production Control: A Survival Guide for Planners and Schedulers , 2004 .

[14]  Gerben G. Meyer,et al.  Intelligent Products for Monitoring and Control of Road-Based Logistics , 2010, 2010 International Conference on Management and Service Science.

[15]  Nigel Slack,et al.  Operations management , 1994 .

[16]  Valentin Robu,et al.  Agent-Mediated Electronic Commerce. Designing Trading Strategies and Mechanisms for Electronic Markets , 2013, Lecture Notes in Business Information Processing.

[17]  Sanjay E. Sarma,et al.  Auto ID systems and intelligent manufacturing control , 2003 .

[18]  Gerben G. Meyer,et al.  Production monitoring and control with intelligent products , 2011 .

[19]  Jan Holmström,et al.  Agent-based model for managing composite product information , 2006, Comput. Ind..

[20]  Alan R. Hevner,et al.  Design Science in Information Systems Research , 2004, MIS Q..

[21]  P. Baker,et al.  The Handbook of Logistics and Distribution Management , 2001 .

[22]  Michel Gendreau,et al.  Planned Route Optimization For Real-Time Vehicle Routing , 2007 .

[23]  Gerben G. Meyer,et al.  Situation Awareness for Improved Operational Control in Cross Docks: An Illustrative Case Study , 2012 .