Investigation of the energy efficient sustainable manufacturing approach and its implementation perspectives

Abstract

In the last two decades, energy is becoming one of the main issues in the manufacturing industry as it contributes substantially to production cost, CO2 emissions, and other destructive environmental impact. Due to rising energy costs, environmental concerns and stringent regulations, manufacturing is increasingly driven towards sustainable manufacturing which needs to address the associated environmental, social and economic aspects simultaneously. One common approach is to achieve sustainability and to implement energy-resource efficient production management systems that enable optimisation of energy consumption and resource utilisation in the production system. However, by reducing energy consumption, the product quality and production cost may be compromised. To remain competitive in the dynamic environment, the energy-efficient management system should not only concern energy consumption but also maintain product quality and production efficiency. This thesis presents a development of the Energy-smart Production Management (e-ProMan) system which provides a systematic, virtual simulation that integrates manufacturing data relating to thermal effect and correlation analysis between energy flow, work flow and data flow for the heating, ventilation and air conditioning (HVAC) system and production process. First, the e-ProMan system comprises of the multidimensional analysis between energy flow, work flow and data flow. The results showed that the product quality is significantly affected by ambient temperature in CNC precision machining. Product quality appears to be improved at lower temperatures. This research highlights the significance of ambient temperature in sustainable precision machining. Second, the simulation experiment was modelled at the production process due to it being the main source of energy consumption in manufacturing. An up-hill workload scenario was found to be the most energy and cost-efficient production processes. In other words, energy consumption, CO2 emission and total manufacturing cost could be reduced when workload capacity and operating machine increase incrementally. Moreover, the e-ProMan system was modelled and simulated using the weather forecast and real-time ambient temperature to reduce energy consumption of the HVAC system. The e-ProMan system results in less energy consumption compared to the fuzzy control system. To conclude, the e-ProMan demonstrates energy efficiency at all relevant levels in the manufacturing: machine, process and plant. For the future research, the e-ProMan system needs to be applied and validated in actual manufacturing environments.