Emergy-based evaluation and improvement for sustainable manufacturing systems considering resource efficiency and environment performance

Abstract Sustainable manufacturing, regarded as resource efficient, environment-friendly and customer satisfaction production, is major driving force for sustainable development. With growing demand for decoupling between resources and world economic development, accelerating sustainable manufacturing has become an important strategy. Therefore, a novel method based on emergy theory is proposed to perform the comprehensive evaluation and improvement of manufacturing systems. Firstly, drivers and challenges are analyzed, and the boundary and connotation of manufacturing systems are defined. Then, an emergy-based calculation model of the energy, material, service and waste is presented considering the variety and dimension of the input and output of manufacturing systems. The model expresses the mechanism of the transfer, coupling and conversion of the emergy for manufacturing systems. Besides, some indicator systems are established including functional emergy indicators, structural emergy indicators, eco-efficiency emergy indicators and sustainability indicators of manufacturing systems. The inner link between the economic, environment and social benefits of manufacturing systems is revealed through these indicators. On this basis, an improvement benchmarking card is developed to achieve the excellent quality, high efficiency, energy reduction, resource saving and environmental protection of manufacturing systems. Finally, a case study illustrates the practicability of the proposed method, and results show that the proposed method provides theoretical support for evaluating and improving the sustainability of manufacturing systems to coordinate the resources and development of the manufacturing industry.

[1]  Egon Müller,et al.  Providing energy data and information for sustainable manufacturing systems by Energy Cards , 2015 .

[2]  S. G. Deshmukh,et al.  An integrated approach for analysing the enablers and barriers of sustainable manufacturing , 2017 .

[3]  Xin Ma,et al.  Predicting the oil production using the novel multivariate nonlinear model based on Arps decline model and kernel method , 2016, Neural Computing and Applications.

[4]  Shun Jia,et al.  Emergy based sustainability evaluation of remanufacturing machining systems , 2018 .

[5]  Ibrahim H. Garbie,et al.  DFSME: design for sustainable manufacturing enterprises (an economic viewpoint) , 2013 .

[6]  Guangdong Tian,et al.  Green decoration materials selection under interior environment characteristics: A grey-correlation based hybrid MCDM method , 2018 .

[7]  Zeyi Sun,et al.  Customer-side electricity load management for sustainable manufacturing systems utilizing combined heat and power generation system , 2015 .

[8]  Y. Wang,et al.  Time-of-use based electricity demand response for sustainable manufacturing systems , 2013 .

[9]  Adriana Giret,et al.  Rescheduling in job-shop problems for sustainable manufacturing systems , 2017 .

[10]  Jingzheng Ren,et al.  Optimization of emergy sustainability index for biodiesel supply network design , 2015 .

[11]  M. Taisch,et al.  Sustainable manufacturing: trends and research challenges , 2012 .

[12]  MengChu Zhou,et al.  Disassembly Sequence Planning Considering Fuzzy Component Quality and Varying Operational Cost , 2018, IEEE Transactions on Automation Science and Engineering.

[13]  Karl R. Haapala,et al.  Integrating Sustainable Manufacturing Assessment into Decision Making for a Production Work Cell , 2015 .

[14]  Hua Zhang,et al.  A two-stage optimization method for energy-saving flexible job-shop scheduling based on energy dynamic characterization , 2018, Journal of Cleaner Production.

[15]  Yanlong Cao,et al.  Optimising the machining time, deviation and energy consumption through a multi-objective feature sequencing approach , 2018 .

[16]  Peter Ball,et al.  The emergence of sustainable manufacturing practices , 2012 .

[17]  Vimal KEK,et al.  LCA Integrated ANP Framework for Selection of Sustainable Manufacturing Processes , 2016, Environmental Modeling & Assessment.

[18]  Francesco Calise,et al.  Optimal operating strategies of combined cooling, heating and power systems: A case study for an engine manufacturing facility , 2017 .

[19]  M A Sinclair,et al.  Global drivers, sustainable manufacturing and systems ergonomics. , 2015, Applied ergonomics.

[20]  Lin Li,et al.  Potential capability estimation for real time electricity demand response of sustainable manufacturing systems using Markov Decision Process , 2014 .

[21]  Nan Li,et al.  Management of sustainable manufacturing systems-a review on mathematical problems , 2017, Int. J. Prod. Res..

[22]  Shun Jia,et al.  An investigation into methods for predicting material removal energy consumption in turning , 2018, Journal of Cleaner Production.

[23]  W. Chen,et al.  Emergy-based sustainability evaluation of Erhai Lake Basin in China , 2018 .

[24]  Ying Liu,et al.  Therblig-embedded value stream mapping method for lean energy machining , 2017 .

[25]  Minda Ma,et al.  Do commercial building sector-derived carbon emissions decouple from the economic growth in Tertiary Industry? A case study of four municipalities in China. , 2019, The Science of the total environment.

[26]  Wei Cai,et al.  Development of dynamic energy benchmark for mass production in machining systems for energy management and energy-efficiency improvement , 2017 .

[27]  Wei Cai,et al.  Energy benchmarking rules in machining systems , 2018 .

[28]  S. Ulgiati,et al.  Identifying the environmental support and constraints to the Chinese economic growth—An application of the Emergy Accounting method , 2013 .

[29]  Howard T. Odum,et al.  Environmental Accounting: Emergy and Environmental Decision Making , 1995 .

[30]  Angappa Gunasekaran,et al.  World-class sustainable manufacturing: framework and a performance measurement system , 2015 .

[31]  Chen Peng,et al.  Minimising the machining energy consumption of a machine tool by sequencing the features of a part , 2017 .

[32]  David Dornfeld,et al.  Moving towards green and sustainable manufacturing , 2014 .

[33]  Gang Yang,et al.  Sustainability evaluation of a steel production system in China based on emergy , 2016 .

[34]  Haizhong An,et al.  Emergy network analysis of Chinese sectoral ecological sustainability , 2018 .

[35]  M. Rosen INDICATORS FOR THE ENVIRONMENTAL IMPACT OF WASTE EMISSIONS: COMPARISON OF EXERGY AND OTHER INDICATORS , 2009 .

[36]  Kang He,et al.  Developing the ecological compensation criterion of industrial solid waste based on emergy for sustainable development , 2018, Energy.

[37]  Sergio Ulgiati,et al.  Energy and eMergy evaluation of bioethanol production from wheat in Henan Province, China , 2008 .

[38]  Mélanie Despeisse,et al.  Sustainable manufacturing tactics and cross-functional factory modelling , 2013 .

[39]  Julian M. Allwood,et al.  Reducing climate change gas emissions by cutting out stages in the life cycle of office paper , 2007 .

[40]  Laine Mears,et al.  Energy, economy, and environment analysis and optimization on manufacturing plant energy supply system , 2016 .

[41]  Claudio Boer,et al.  The incoming global technological and industrial revolution towards competitive sustainable manufacturing , 2008 .

[42]  Y. Geng,et al.  An emergy accounting based regional sustainability evaluation: A case of Qinghai in China , 2018 .

[43]  Mark T. Brown,et al.  Assessing the global environmental sources driving the geobiosphere: A revised emergy baseline , 2016 .

[44]  Wim Dewulf,et al.  Pro-active Life Cycle Engineering Support Tools , 2003 .

[45]  Jose Arturo Garza-Reyes,et al.  A lean and cleaner production benchmarking method for sustainability assessment: A study of manufacturing companies in Brazil , 2018 .

[46]  Angappa Gunasekaran,et al.  Composite sustainable manufacturing practice and performance framework: Chinese auto-parts suppliers' perspective , 2015 .

[47]  Wei Cai,et al.  An energy-consumption model for establishing energy-consumption allowance of a workpiece in a machining system , 2016 .

[48]  S. Feng,et al.  Categorization of indicators for sustainable manufacturing , 2013 .

[49]  Radu Godina,et al.  Proposal of a Sustainable Circular Index for Manufacturing Companies , 2017 .

[50]  Minda Ma,et al.  What drives the carbon mitigation in Chinese commercial building sector? Evidence from decomposing an extended Kaya identity. , 2018, The Science of the total environment.

[51]  Wei Cai,et al.  Fine energy consumption allowance of workpieces in the mechanical manufacturing industry , 2016 .

[52]  Wei Cai,et al.  An energy management approach for the mechanical manufacturing industry through developing a multi-objective energy benchmark , 2017 .

[53]  Marco Casazza,et al.  Enhancing the Sustainability Narrative through a Deeper Understanding of Sustainable Development Indicators , 2017 .

[54]  Hao Zhang,et al.  A conceptual model for assisting sustainable manufacturing through system dynamics , 2013 .

[55]  Shun Jia,et al.  Energy modeling method of machine-operator system for sustainable machining , 2018, Energy Conversion and Management.

[56]  Neven Duić,et al.  Reducing the CO2 emissions in Croatian cement industry , 2013 .

[57]  Wei Cai,et al.  An analytical investigation on energy efficiency of high-speed dry-cutting CNC hobbing machines , 2018 .

[58]  Utpal Roy,et al.  Development and utilization of a Process-oriented Information Model for sustainable manufacturing , 2015 .

[59]  Kuan Yew Wong,et al.  Strategy selection for sustainable manufacturing with integrated AHP-VIKOR method under interval-valued fuzzy environment , 2016 .

[60]  F. Abnisa,et al.  A review on pyrolysis of plastic wastes , 2016 .

[61]  H. Noorman,et al.  Key Green Engineering Research Areas for Sustainable Manufacturing: A Perspective from Pharmaceutical and Fine Chemicals Manufacturers , 2011 .

[62]  Peter Ball,et al.  Steps towards sustainable manufacturing through modelling material, energy and waste flows , 2012 .

[63]  Pascal Mognol,et al.  Sustainable manufacturing: evaluation and modeling of environmental impacts in additive manufacturing , 2013, The International Journal of Advanced Manufacturing Technology.

[64]  Wei Cai,et al.  A tool for assessing the energy demand and efficiency of machining systems: Energy benchmarking , 2017 .