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Therblig-based energy demand modeling methodology of machining process to support intelligent manufacturing

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Abstract

Energy efficiency has become an important factor that should be included in Intelligent Manufacturing due to the increasingly rising energy price and severe energy shortage issues. Energy demand modeling method is the foundation of improving the energy efficiency of manufacturing; therefore, an energy demand modeling methodology for machining processes is proposed. In this method, machining processes are divided into a series of activities, and Therblig, as one of the basic concepts of Motion study, is introduced to represent the basic energy demand unit. Moreover, a mathematical model of energy demand of machining processes is established by linking the activity and Therblig with machining state. Finally, case studies are performed to illustrate the validity and feasibility of the proposed methodology.

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Abbreviations

\(a_p\) :

Cutting depth (mm)

\(ATR\) :

Activity-Therblig relation matrix

\(d\) :

Diameter of cutting tool (mm)

\(E\) :

Energy consumption of the machining process (kJ)

\(E_j\) :

Energy consumption of Therblig in the whole machining process (kJ)

\(f\) :

Feed speed (mm/rv)

\(f_z\) :

Feed per tooth (mm/tooth)

\(F_c\) :

Cutting force (kN)

\(K_p\) :

Property of materials (\(\text{ kJ/cm}^{3}\))

\(L\) :

Cutting length (mm)

\(L_C \) :

Length cutter from the workpiece (mm)

\(MRR\) :

Material removal rate (cm3/s)

\(n\) :

Spindle rotation speed (r/min)

\(N\) :

Number of measurement points

\(P\) :

Cutting power (kW)

\(P_{e-in}\) :

Electrical power in (kW)

\(p_{ij}\) :

Power of Therblig \(j\) in activity \(i\) (kW)

\(P_{m-out} \) :

Mechanical power out (kW)

\(P_n\) :

Nominal power (kW)

\(P_{wl}\) :

Windage loss (kW)

\(P_{fl} \) :

Friction loss (kW)

\(P_{cl} \) :

Copper loss (kW)

\(P_{il} \) :

Iron loss (kW)

\(P_{sl} \) :

Stray loss (kW)

\(P_{sn} \) :

Unloaded spindle power (kW)

\(P_f^{r}\) :

Power of rapid positioning (kW)

\(P_x^{r}\) :

Power of x-axis feed motor during rapid positioning (kW)

\(P_y^{r}\) :

Power of y-axis feed motor during rapid positioning (kW)

\(P_z^{r}\) :

Power of z-axis feed motor during rapid positioning (kW)

\(P_f^{c}\) :

Power of cutting feed (kW)

\(P_x^c\) :

Power of x-axis motor at the speed of \(\text{ v}_{x}\) (kW)

\(P_y^c\) :

Power of y-axis motor at the speed of \(\text{ v}_{y}\) (kW)

\(P_z^c\) :

Power of z-axis motor at the speed of \(\text{ v}_{z}\) (kW)

\(P_{BM, i} \) :

Measured power of Therblig-BM of measurement point \(i\) (kW)

\(P_{Cut} \) :

Actual cutting power (kW)

\(P_{Tip-cutting} \) :

Cutting power of tool tip (kW)

\(s_{ij} \) :

Execution state of Therblig \(i\) in activity \(j\)

\(SEC\) :

Specific energy consumption (\(\text{ kJ/cm}^{3}\))

\(T\) :

Time matrix of activity of CNC machine tools

\(TP\) :

Power matrix of Therblig of CNC machine tools

\(TT\) :

Time matrix of Therblig of CNC machine tools

\(t\) :

Machining time (s)

\(t_{cutting} \) :

Cutting time (s)

\(t_i \) :

Execute time of activity \(i\)

\(v\) :

Cutting speed (m/min)

\(v_f \) :

Feed speed (m/min)

\(v_x \) :

X-axis feed speed (m/min)

\(v_y \) :

Y-axis feed speed (m/min)

\(v_z \) :

Z-axis feed speed (m/min)

\(V_m \) :

Volume of removal material (\(\text{ cm}^{3}\))

\(w\) :

Cutting width (mm)

\(z\) :

Number of teeth of cutter

\(\alpha \) :

Power loss coefficient

\(\eta \) :

Motor efficiency

\(\ell \) :

Motor load

\(\Delta X\) :

Move distances in X-axis (mm)

\(\Delta Y\) :

Move distances in Y-axis (mm)

\(\Delta X_f \) :

Feed distances in X-axis (mm)

\(\Delta Y_f \) :

Feed distances in Y-axis (mm)

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Acknowledgments

The authors gratefully thank all the anonymous reviewers for their valuable suggestions on the improvement of our paper and acknowledge the National Natural Science Foundation, China (No.51175464), and the Ningbo Science and Technology Innovation Team for supporting this research.

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Authors and Affiliations

  1. Zhejiang Province Key Laboratory of Advanced Manufacturing Technology, Department of Mechanical Engineering, Industrial Engineering Center, Zhejiang University, Hangzhou, 310027, Zhejiang, China

    Shun Jia, Renzhong Tang & Jingxiang Lv

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  1. Shun Jia
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Correspondence to Renzhong Tang.

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Jia, S., Tang, R. & Lv, J. Therblig-based energy demand modeling methodology of machining process to support intelligent manufacturing. J Intell Manuf 25, 913–931 (2014). https://doi.org/10.1007/s10845-012-0723-9

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