RFID Technology in Intelligent Tracking Systems in Construction Waste Logistics Using Optimisation Techniques

Construction waste disposal is an urgent issue for protecting our environment. This paper proposes a waste management system and illustrates the work process using plasterboard waste as an example, which creates a hazardous gas when land filled with household waste, and for which the recycling rate is less than 10% in the UK. The proposed system integrates RFID technology, Rule-Based Reasoning, Ant Colony optimization and knowledge technology for auditing and tracking plasterboard waste, guiding the operation staff, arranging vehicles, schedule planning, and also provides evidence to verify its disposal. It h relies on RFID equipment for collecting logistical data and uses digital imaging equipment to give further evidence; the reasoning core in the third layer is responsible for generating schedules and route plans and guidance, and the last layer delivers the result to inform users. The paper firstly introduces the current plasterboard disposal situation and addresses the logistical problem that is now the main barrier to a higher recycling rate, followed by discussion of the proposed system in terms of both system level structure and process structure. And finally, an example scenario will be given to illustrate the system’s utilization

Interpretive structural model of key performance indicators for sustainable manufacturing evaluation in automotive companies

This paper aims to analyze the interrelationships among the key performance indicators of sustainable manufacturing evaluation in automotive companies. The initial key performance indicators have been identified and derived from literature and were then validated by industry survey. Interpretive structural modeling (ISM) methodology is applied to develop a hierarchical structure of the key performance indicators in three levels. Of nine indicators, there are five unstable indicators which have both high driver and dependence power, thus requiring further attention. It is believed that the model can provide a better insight for automotive managers in assessing their sustainable manufacturing performance