ENERGY AND COST CONSCIOUS PROCESS ROUTING
Keywords:
Energy, Cost, Process Routing, Metal cutting, Sustainable ManufacturingAbstract
This paper presents the research work involved in development of an energy and cost conscious process routing system. Proposed system is based on total energy consumed by machine tools and manufacturing cost occurred during the manufacturing.Overall system is structured in the form of six different modules including modules for machine tool selection, cutting tool selection, time and cost estimation, energy estimation, impact assessment and process routing generation. Each module is designed by acquisition of technical information from different sources including published literature, catalogues, and consultation with domain experts. Artificial intelligence (AI) technique, state space search method is used to search all possible process routes and grey relational analysis is used to fix optimised process route in terms of energy and cost.Further a case study of a horizontal machining centre is demonstrated for developing the energy estimation models. Methodology followed in the present work for deriving energy estimation models are useful for any metal cutting industry and it does not require costly instruments. The usefulness of proposed system is tested in one medium scale industry having large variety of component and batch quantity manufacturing. The proposed system is helpful in reducing energy wastage and it provides a base for implementing potential energy saving strategies for sustainable manufacturing.
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Choi Y-C Xirouchakis P (2014), “A Production Planning in Highly automated Manufacturing System Considering Multiple Process Plans with Different Energy requirements”, International Journal of Advanced Manufacturing Technology, Vol. 70, 853-867.
CECIMO (2009), “Concept Description for CECIMO’s Self-regulatory Initiative (SRI) for the Sector Specific Implementation of the Directive 2005/32/EC”.
European Commission (2008), “Energy Efficiency in Manufacturing – The Role of ICT and Energy Efficiency – Consultation Group on Smart Manufacturing”.
Dahmus J B and Gutowski T G (2004), “An environmental analysis of machining”, ASME 2004 international mechanical engineering congress and exposition, American Society of Mechanical Engineers, 643-652.
Vijayaraghavan A and Dornfeld D (2010), “Automated energy monitoring of machine tools”, CIRP Annals-Manufacturing Technology, Vol. 59(1), 21-24.
Gutowski T Dahmus J and Thiriez A (2006), “Electrical Energy Requirements for Manufacturing Processes”, Proceedings of the 13th CIRP Conference on Life Cycle Engineering, Leuven, Belgium, 623–627.
Herrman C Bergmann L Thiede S and Zein A (2007),“Energy Labels for Production Machines – An Approach to Facilitate Energy Efficiency in Production Systems”, Proceedings of 40th CIRP International Seminar on Manufacturing Systems Location, Liverpool, UK.
Jeswiet J and Kara S (2008), “Carbon emissions and CES™ in manufacturing”, CIRP Annals-Manufacturing Technology, Vol. 57(1), 17-20.
Kara S and Li W (2011), “Unit process energy consumption models for material removal processes”, CIRP Annals - Manufacturing Technology, Vol. 60, 37–40.
Mativenga P T and Rajemi M F (2011), “Calculation of Optimum Cutting Parameters Based on Minimum Energy Footprint”, CIRP Annals, Vol. 60(1), 149–152.
Duflou J Kellens K Renaldi Guo Y and Dewulf W (2012), “Critical comparison of methods to determine the energy input for discrete manufacturing processes”, CIRP Annals - Manufacturing Technology, Vol.61, 63–66.
Weinert N Chiotellis S and Seliger G (2011),“Methodology for planning and operating energy-efficient production systems”, CIRP Annals - Manufacturing Technology, Vol. 60, 41–44.
Thiede S Posselt G and Herrmann C (2013), “SME appropriate concept for continuously improving the energy and resource efficiency in manufacturing companies”, CIRP Journal of Manufacturing Science and Technology, Vol. 6(3), 204-211.
Park H-S Nguyen T-T and Dang X-P (2016), “Energy-Efficient Optimization of Forging Process Considering the Manufacturing History”, International Journal of Precision Engineering and Manufacturing-Green Technology, Vol. 3(2), 147-154.
Sheng P Srinivasan M and Kobayashi S (1995), “Multiobjective process planning in environmentally conscious manufacturing: a feature-based approach”, CIRP Annals, Vol.44 (1), 433–437.
Srinivasan M and Sheng P (1999), “Feature-based process planning for environmentally conscious machining – Part 1: microplanning”, Robotics and Computer-Integrated Manufacturing, Vol. 15(3), 257-270.
He Y Liu F Cao H J and Zhang H (2007), “Process planning support system for green manufacturing”, Frontiers of Mechanical Engineering in China, Vol. 2(1), 104–109.
Jin K Zhang H C Balasubramaniam P and Nage S (2009), “A multiple objective optimization model for Environmental Benign Process Planning”, Proceedings 2009 IEEE 16th International Management, 869-873.
Newman S Nassehi A Imani-Asrai R and Dhokia V (2012), “Energy Efficient Process Planning for CNC Machining”, CIRP Journal of Manufacturing Science and Technology, Vol. 5,127–136.
Shin S J Suh S H and Stroud I (2015), “A green productivity based process planning system for a machining process”, Int., Journal of Production Research, Vol. 53(17), 5085-5105.
Dai M Tang D Xu Y and Li W (2014), “Energy-aware integrated process planning and scheduling for job shops”, ProcIMechE Part B: J Engineering Manufacture, 1–14.
Polgar K (1996), “Simplified Time Estimation for Basic Machining Operations”, M S Thesis, Department of Mechanical Engineering, Massachusetts Institute of Technology.
Hassan A Saidat A Dantan J-Y Martin P (2010),“Conceptual Process Planning- An Improvement Approach Using QFD, FMEA and ABC Methods” Robotics and Computer-Integrated Manufacturing, Vol. 26, 392-401.
Oberg E Jones F Hrotan H and Ryffel H (2004), “Machinery’s Handbook”, Industrial Press Inc, New York, 1085-1092.
Ghodake S Kumar R Singh N and Khandelwal H (2012), “Estimation of Green House Gas Emission from Indian Coal Based Thermal Power Plant”, IOSR J. of Engineering, Vol. 2(4), 591-597.
