Decision support for sustainable manufacturing using decision guidance query language

Sustainability has become a very significant research topic as it impacts many different manufacturing industries. Therefore, the technologies for monitoring, analysing, evaluating and optimising the sustainability performance of manufacturing processes and systems are very critical for decision makers on the shop floor. This paper introduces a decision guidance management system that provides actionable recommendations through quantitative analysis of the sustainability measures of manufacturing processes and systems based on life cycle assessment. The system determines decision preferences through dynamically collected data and decision makers' responses, taking into account the prevailing constraints. Optimal decisions can be derived using mathematical and constraint programming. By using decision guidance query language, this methodology allows users to make optimal decisions without an extensive mathematical or operations research background. Knowledge of relational databases is sufficient for a user to formulate the optimisation problem and obtain optimal solutions. The methodology is demonstrated with a machining operation case study, in which a list of sustainability metrics are identified and sustainability modelling methods are proposed. Important sustainable machining performance measures are optimised, resulting in actionable recommendations.     

Integrated Simulation and Modelling Approach to Decision Making and Environmental Protection

This paper's objective is first to test the application of computer simulation and modelling tools in investigating the effects of applying sustainable manufacturing practices in a smelter plant, and second, to prove quantitatively and visually that 'sustainibility is free'. A simulation model is built to test and capture two different operating polices, 'Policy 1' and 'Policy 2', of an industrial system. In the case study, the simulation model is designed to reflect the effects of decision making in the activites found in a smelter plant, and to quantify the cost, sustainable and environmental consequences based on the decisions. Apart from providing a means of accurately measuring a system's performance, the purpose of using simulation tools is also to link the economic factors, such as productivity and total costs, as well as the sustainable factors, such as natural resource and energy consumption of a system. The simulation results prove quantitatively and visually that sustainability is not only 'free' but is, in fact, a far better proposition for economic growth in the medium to longer term than traditional forms of management.     

基于LCA的废旧资源循环利用节能减排效果评估模式与方法研究——以吉林省某钢铁企业为例

促进废旧资源循环利用是加快推进我国生态文明建设,完成节能减排目标的必然选择。本文基于生命周期评价模式,从微观企业层面入手,构建产品全生命周期基准流程,引入能量输入与环境输出参数,建立废旧资源循环利用节能减排效果量化核算模型,评估再生产品的节能减排经济成效,并以吉林省某钢铁企业为例,评估"废钢-电炉"短流程和"铁矿石-高炉-转炉"长流程的能源、环境、成本差异,辨识影响废钢再循环节能减排效果的主要因素和重要环节。结果显示,再生钢铁全生命周期与原生钢铁全生命周期相比,节能588.48kgce/t,节能率为84%;主要污染物中SO2减排率最高,达92%;CO2总减排1 180.92 kg/t,减排率为67%;总成本却高出198元/t。其中,炼铁工序的节能量和减碳量最大,烧结工序SO2、NOx和烟(粉)尘减排量最大,焦化工序COD和氨氮减排量最大,回收、加工处理、炼钢环节节能量和减碳量以及SO2、NOx和烟(粉)尘减排量均为负。成本方面,再生钢铁生产成本高于原生钢铁308元/t,虽然再生钢铁由于污染减排可节省56元/t的排污费并获取54元/t的碳交易收益,但都不足以扭转电炉炼钢费用较高的现状。因此,国家应在电炉炼钢方面给予钢企及相关企业适当的财税扶持政策,在电价方面给予钢企一定的优惠或补贴,并完善废钢回收加工体系等,以促进废钢循环利用。基于LCA的废旧资源循环利用节能减排效果评估可以实现对产品生命周期全过程的资源、环境、成本的优化管理。