Operational methods for minimization of energy consumption of manufacturing equipment

This paper develops operational methods for the minimization of the energy consumption of manufacturing equipment. It is observed that there can be a significant amount of energy savings when non-bottleneck (i.e. underutilized) machines/equipment are turned off when they will be idle for a certain amount of time. Using this fact, several dispatching rules are proposed. A detailed performance analysis indicates that the proposed dispatching rules are effective in decreasing the energy consumption of especially underutilized manufacturing equipment. In addition, a multi-objective mathematical programming model is proposed to minimize the energy consumption and total completion time. Using this approach, a production manager will have a set of non-dominated solutions (i.e. the set of efficient solutions) which he/she can use to determine the most efficient production sequence which will minimize the total energy consumption while optimizing the total completion time.

[1]  David N. Kordonowy,et al.  A power assessment of machining tools , 2002 .

[2]  R. S. Laundy,et al.  Multiple Criteria Optimisation: Theory, Computation and Application , 1989 .

[3]  Lawrence E. Whitman,et al.  Data collection framework on energy consumption in manufacturing , 2006 .

[4]  Askiner Gungor,et al.  Issues in environmentally conscious manufacturing and product recovery: a survey , 1999 .

[5]  Ajd Fred Lambert,et al.  Disassembly sequencing: A survey , 2003 .

[6]  P. Werbos,et al.  Beyond Regression : "New Tools for Prediction and Analysis in the Behavioral Sciences , 1974 .

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

[8]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[9]  Y. Asiedu,et al.  Product life cycle cost analysis: State of the art review , 1998 .

[10]  Luca Benini,et al.  Dynamic Power Management , 1998 .

[11]  Luca Benini,et al.  Energy-efficient design of battery-powered embedded systems , 1999, Proceedings. 1999 International Symposium on Low Power Electronics and Design (Cat. No.99TH8477).

[13]  Sharad Malik,et al.  Power analysis of embedded software: a first step towards software power minimization , 1994, IEEE Trans. Very Large Scale Integr. Syst..

[14]  Vaidyanathan Jayaraman,et al.  Production planning for closed-loop supply chains with product recovery and reuse: an analytical approach , 2006 .

[15]  Luca Benini,et al.  Dynamic power management for portable systems , 2000, MobiCom '00.

[16]  Subbarao Kambhampati,et al.  Planning and Scheduling , 1997, The Computer Science and Engineering Handbook.

[17]  Jan Karel Lenstra,et al.  Complexity of machine scheduling problems , 1975 .

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

[19]  M Ross.  Efficient energy use in manufacturing. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[20]  Michael Pinedo,et al.  Scheduling: Theory, Algorithms, and Systems , 1994 .

[21]  Jay B. Ghosh,et al.  Scheduling with tool changes to minimize total completion time: A study of heuristics and their performance , 2003 .

[22]  Han Hoogeveen,et al.  Multicriteria scheduling , 2005, Eur. J. Oper. Res..

[23]  G. Shedler,et al.  Simulation of Nonhomogeneous Poisson Processes by Thinning , 1979 .

[24]  Krishnendu Chakrabarty,et al.  Energy-conscious, deterministic I/O device scheduling in hard real-time systems , 2003, IEEE Trans. Comput. Aided Des. Integr. Circuits Syst..