Therblig-embedded value stream mapping method for lean energy machining

To improve energy efficiency, extensive studies have focused on the cutting parameters optimization in the machining process. Actually, non-cutting activities (NCA) occur frequently during machining and this is a promising way to save energy through optimizing NCA without changing the cutting parameters. However, it is difficult for the existing methods to accurately determine and reduce the energy wastes (EW) in NCA. To fill this gap, a novel Therblig-embedded Value Stream Mapping (TVSM) method is proposed to improve the energy transparency and clearly show and reduce the EW in NCA. The Future-State-Map (FSM) of TVSM can be built by minimizing non-cutting activities and Therbligs. By implementing the FSM, time and energy efficiencies can be improved without decreasing the machining quality, which is consistent with the goal of lean energy machining. The method is validated by a machining case study, the results show that the total energy is reduced by 7.65%, and the time efficiency of the value-added activities is improved by 8.12%, and the energy efficiency of value-added activities and Therbligs are raised by 4.95% and 1.58%, respectively. This approach can be applied to reduce the EW of NCA, to support designers to design high energy efficiency machining processes during process planning.

[1]  Paul Xirouchakis,et al.  Evaluating the use phase energy requirements of a machine tool system , 2011 .

[2]  Juan Yang.  EMergy accounting for the Three Gorges Dam project: three scenarios for the estimation of non-renewable sediment cost , 2016 .

[3]  Theocharis Alexopoulos,et al.  On a generalized approach to manufacturing energy efficiency , 2014 .

[4]  T. Gutowski,et al.  Electrical Energy Requirements for Manufacturing Processes , 2006 .

[5]  Fei Liu,et al.  Multi-objective optimization of machining parameters considering energy consumption , 2013, The International Journal of Advanced Manufacturing Technology.

[6]  Girish Kant,et al.  Prediction and optimization of machining parameters for minimizing power consumption and surface roughness in machining , 2014 .

[7]  Christoph Herrmann,et al.  Energy oriented simulation of manufacturing systems - Concept and application , 2011 .

[8]  Ernst Worrell,et al.  Empirical investigation of energy efficiency barriers in Italian manufacturing SMEs , 2013 .

[9]  Stefan Velchev,et al.  Empirical models for specific energy consumption and optimization of cutting parameters for minimizing energy consumption during turning , 2014 .

[10]  Jinwoo Park,et al.  Optimization of production scheduling with time-dependent and machine-dependent electricity cost for industrial energy efficiency , 2013 .

[11]  Shun Jia,et al.  Therblig-based energy supply modeling of computer numerical control machine tools , 2014 .

[12]  S. Bagaber,et al.  Multi-objective optimization of cutting parameters to minimize power consumption in dry turning of stainless steel 316 , 2017 .

[13]  Zhaohui Deng,et al.  A process parameters optimization method of multi-pass dry milling for high efficiency, low energy and low carbon emissions , 2017 .

[14]  Dimitris Mavrikios,et al.  A perspective on manufacturing strategy: Produce more with less , 2008 .

[15]  Lin Li,et al.  Multi-objective optimization of milling parameters – the trade-offs between energy, production rate and cutting quality , 2013 .

[16]  Thorsten Pawletta,et al.  A discrete-event simulation approach to predict power consumption in machining processes , 2011, Prod. Eng..

[17]  Yan Wang,et al.  A modeling method for hybrid energy behaviors in flexible machining systems , 2015 .

[18]  Shun Jia,et al.  Therblig-based energy demand modeling methodology of machining process to support intelligent manufacturing , 2014, J. Intell. Manuf..

[19]  Yingxue Yao,et al.  Optimization of cutting parameters for energy saving , 2014 .

[20]  Gianni Campatelli,et al.  Optimization of process parameters using a Response Surface Method for minimizing power consumption in the milling of carbon steel , 2014 .

[21]  Patrik Thollander,et al.  Barriers to and driving forces for energy efficiency in the non-energy intensive manufacturing industry in Sweden , 2006 .

[22]  P. Balachandra,et al.  Barriers to energy efficiency in small industry clusters: Multi-criteria-based prioritization using the analytic hierarchy process , 2006 .

[23]  Christoph Herrmann,et al.  Economic and environmental value stream map (E2VSM) simulation for multi-product manufacturing systems , 2016 .

[24]  Sanja Petrovic,et al.  An investigation into minimising total energy consumption and total weighted tardiness in job shops , 2014 .

[25]  Massimo Paolucci,et al.  Energy-aware scheduling for improving manufacturing process sustainability: A mathematical model for flexible flow shops , 2012 .

[26]  Giuliano Bissacco,et al.  Real time power consumption monitoring for energy efficiency analysis in micro EDM milling , 2015 .

[27]  G. Miragliotta,et al.  Energy management based on Internet of Things: practices and framework for adoption in production management , 2015 .

[28]  T. Gutowski,et al.  Environmentally benign manufacturing: Observations from Japan, Europe and the United States , 2005 .

[29]  Christoph Herrmann,et al.  Green Manufacturing and Sustainable Manufacturing Partnership Title Towards Energy and Resource Efficient Manufacturing : A Processes and Systems Approach Permalink , 2012 .

[30]  John W. Sutherland,et al.  A new approach to scheduling in manufacturing for power consumption and carbon footprint reduction , 2011 .

[31]  Jun Xie,et al.  A method for predicting the energy consumption of the main driving system of a machine tool in a machining process , 2015 .

[32]  Konrad Wegener,et al.  Methods for evaluation of energy efficiency of machine tools , 2015 .

[33]  Shun Jia,et al.  Machining activity extraction and energy attributes inheritance method to support intelligent energy estimation of machining process , 2016, J. Intell. Manuf..

[34]  Francisco J. Campa,et al.  An integrated process–machine approach for designing productive and lightweight milling machines , 2011 .

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

[36]  Joaquín B. Ordieres Meré,et al.  Optimizing the production scheduling of a single machine to minimize total energy consumption costs , 2014 .

[37]  Girish Kant,et al.  Optimization of Machining Parameters for Improving Energy Efficiency using Integrated Response Surface Methodology and Genetic Algorithm Approach , 2017 .

[38]  Shahin Rahimifard,et al.  Simulation of energy consumption in the manufacture of a product , 2013, Int. J. Comput. Integr. Manuf..

[39]  Andrea Trianni,et al.  Quick-E-scan: A methodology for the energy scan of SMEs , 2010 .

[40]  Sami Kara,et al.  Unit process energy consumption models for material removal processes , 2011 .

[41]  William Faulkner,et al.  Sustainable Value Stream Mapping (Sus-VSM): methodology to visualize and assess manufacturing sustainability performance , 2014 .

[42]  中華人民共和国国家統計局.  China statistical yearbook , 1988 .

[43]  Liang Gao,et al.  Energy-efficient multi-pass turning operation using multi-objective backtracking search algorithm , 2016 .

[44]  John Cosgrove,et al.  A methodology for determining auxiliary and value-added electricity in manufacturing machines , 2015 .

[45]  H. Van Landeghem,et al.  Analysing the effects of Lean manufacturing using a value stream mapping-based simulation generator , 2007 .

[46]  Fouad Al-Mansour,et al.  Energy efficiency trends and policy in Slovenia , 2011 .

[47]  Hari Singh,et al.  Optimizing power consumption for CNC turned parts using response surface methodology and Taguchi's technique—A comparative analysis , 2008 .

[48]  Li Li,et al.  Selection of optimum parameters in multi-pass face milling for maximum energy efficiency and minimum production cost , 2017 .

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

[50]  Andrea Matta,et al.  Energy oriented multi cutting parameter optimization in face milling , 2016 .

[51]  Hakkı Özgür Ünver,et al.  Modelling and optimization of energy consumption for feature based milling , 2016 .

[52]  Paul Mativenga,et al.  The effect of Auxiliary Units on the Power Consumption of CNC Machine tools at zero load cutting , 2015 .

[53]  Sami Kara,et al.  Towards Energy and Resource Efficient Manufacturing: A Processes and Systems Approach , 2012 .

[54]  Sudarsan Ghosh,et al.  Machining parameters optimization for satisfying the multiple objectives in machining of MMCs , 2017 .

[55]  Marco Taisch,et al.  Energy management in production: A novel method to develop key performance indicators for improving energy efficiency , 2015 .

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

[57]  Shun Jia,et al.  Energy modeling for variable material removal rate machining process: an end face turning case , 2016 .

[58]  Alexander Verl,et al.  A generic energy consumption model for decision making and energy efficiency optimisation in manufacturing , 2009 .

[59]  Konrad Wegener,et al.  The Total Energy Efficiency Index for machine tools , 2016 .

[60]  Carmita Camposeco-Negrete,et al.  Optimization of cutting parameters using Response Surface Method for minimizing energy consumption and maximizing cutting quality in turning of AISI 6061 T6 aluminum , 2015 .

[61]  Timothy G. Gutowski,et al.  An Environmental Analysis of Machining , 2004 .

[62]  Rajesh Kumar Bhushan,et al.  Optimization of cutting parameters for minimizing power consumption and maximizing tool life during machining of Al alloy SiC particle composites , 2013 .

[63]  Hua Zhang,et al.  Energy consumption model and its simulation for manufacturing and remanufacturing systems , 2016 .

[64]  Fei Liu.  The Complexity and Strategy for Establishing Product Energy Consumption Allowance in Discrete Manufacturing Industry , 2015 .

[65]  Marcello Braglia,et al.  A new value stream mapping approach for complex production systems , 2006 .

[66]  Congbo Li,et al.  Multi-objective parameter optimization of CNC machining for low carbon manufacturing , 2015 .

[67]  Sangkee Min,et al.  Development of an energy consumption monitoring procedure for machine tools , 2012 .

[68]  Sami Kara,et al.  Carbon emissions and CES™ in manufacturing , 2008 .

[69]  Marco Taisch,et al.  Energy management in manufacturing: Toward eco-factories of the future – A focus group study , 2016 .

[70]  Athulan Vijayaraghavan,et al.  Automated energy monitoring of machine tools , 2010 .

[71]  C. Herrmann,et al.  An environmental perspective on Lean production , 2008 .

[72]  Fazleena Badurdeen,et al.  Sustainable value stream mapping (Sus-VSM) in different manufacturing system configurations: application case studies , 2014 .

[73]  Yan He,et al.  An on-line approach for energy efficiency monitoring of machine tools , 2012 .

[74]  Sounak Kumar Choudhury,et al.  Optimization of cutting parameters for maximizing tool life , 1999 .