With the rapid development of new-generation information technology (NGIT), especially the deep integration of NGIT and manufacturing technology, great changes have taken place in the manufacturing service environment. Meanwhile, the energy usage of the manufacturing industry is intensifying, which results in more and more serious energy crisis. On the other hand, the energy consumption of a product in the entire life cycle is mostly decided by the design and manufacture process. So, energy-saving and emission-reduction is a key issue in design and manufacturing processes of a new product which must meet customers’ demands and also reduce energy consumption and environmental impact (Zhang and Li 2010). Energy consumption evaluation and analysis (ECEA) refers to the collection of energy consumption data of a product in its entire life cycle, the construction of the corresponding evaluation model, and the visualisation analysis of the evaluation result. Its aim is to achieve statistical management of energy consumption, the analysis of key energy consumption points and to provide data support for decision-making. Thus, an effective ECEA approach of product life cycle is paramount for realising the above aims. In order to realise accurate ECEA, real-time and dynamic data are needed in the energy management of a product life cycle (Reap et al. 2008; Taisch, Cammarino, and Cassina 2011). However, current research mostly focuses on the way to obtain data from the energy consumption database, such as Chinese Life Cycle Database (CLCD) from China, Econvient from Switzerland, and European Reference Life Cycle Database (ELCD) from the European Union. These data, which come from industry statistics or technical literature, are mainly historical data. It is difficult to provide sufficient support for accurate analysis and decision-making of energy consumption for a current product (Seow, Rahimifard, and Woolley 2013). It has very important impact on product energy-saving. On the other hand, as the ECEA system is established from the perspective of product life cycle, the required data are necessarily related to the enterprise information systems (EISs) in the entire product life cycle. Therefore, in order to ensure data validity, the integration between ECEA system and EISs should also be considered. From the point of view of realising ECEA, many methods such as life cycle assessment (LCA) (Finnveden et al. 2009; Göschel, Schieck, and Schönherr 2012),economic input–output-LCA (Joshi 1999), life cycle costing (Gluch and Baumann 2004), life cycle simulation (Umeda et al. 2012), life cycle sustainability assessment (Kloepffer 2008), social life cycle assessment (Jørgensen et al. 2008), embodied energy model (Kara, Manmek, and Herrmann 2010) have been proposed to assess the environmental impacts and costs of product entire life cycle stages consisting of material extraction, manufacturing process, use, maintenance, etc. These methods have a very important role for energy-saving in the entire product life cycle. However, from the perspective of the users in practical application processes, the following issues still need to be addressed.