Technical Paper Dual mode control strategy for the energy efficiency of complex and flexible manufacturing systems

被引:16
作者
Diaz, Jenny L. C. [1 ]
Ocampo-Martinez, Carlos [1 ]
Olaru, Sorin [2 ]
机构
[1] Univ Politecn Cataluna, Inst Robot & Informat Ind CSIC UPC, Automat Control Dept, Llorens i Artigas 4-6,Planta 2, Barcelona 08028, Spain
[2] Univ Paris Saclay, Univ Paris Sud, Lab Signals & Syst L2S, UMR CNRS 8506,Cent Supelec,CNRS, F-91190 Gif Sur Yvette, France
关键词
Dual mode control strategy; Model predictive control; Mixed-integer linear programming; Smart manufacturing systems; Flexible manufacturing;
D O I
10.1016/j.jmsy.2020.05.009
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The manufacturing industry is shifting towards smart manufacturing, in which both energy efficiency and flexibility are some of the main objectives of this digital transformation. In this regard, the control strategies for manufacturing systems should be able to support the requirements of this transformation with a low computational burden towards their implementation in real time. To this end, in this paper, a dual mode control strategy based on two control approaches is proposed to minimise the energy consumption of manufacturing systems without affecting their productivity, even when scenarios of flexible manufacturing are considered. The first control mode is based on model predictive control to determine an optimisation-based strategy for the constrained behaviour of the system. Then, the second mode builds on the assumption that the system exhibits a periodic behaviour and, thus, it will be able to switch to an autonomous control mode that avoids the resolution of an optimisation problem online. The proposed control strategy is tested in a manufacturing process line in which changes in the production programs are considered with the aim to test the performance in flexible manufacturing scenarios. The obtained results show that the computational burden could be significantly reduced while reducing global energy consumption without affecting the system productivity.
引用
收藏
页码:104 / 116
页数:13
相关论文
共 19 条
[1]   Data Collection for Energy Monitoring Purposes and Energy Control of Production Machines [J].
Abele, Eberhard ;
Panten, Niklas ;
Menz, Benjamin .
22ND CIRP CONFERENCE ON LIFE CYCLE ENGINEERING, 2015, 29 :299-304
[2]  
[Anonymous], 2013, IBM ILOG CPLEX optimization studio
[3]  
[Anonymous], 2002, Predictive Control With Constraints
[4]   Energy-aware scheduling for improving manufacturing process sustainability: A mathematical model for flexible flow shops [J].
Bruzzone, A. A. G. ;
Anghinolfi, D. ;
Paolucci, M. ;
Tonelli, F. .
CIRP ANNALS-MANUFACTURING TECHNOLOGY, 2012, 61 (01) :459-462
[5]   Energy efficiency in discrete-manufacturing systems: Insights, trends, and control strategies [J].
Diaz C, Jenny L. ;
Ocampo-Martinez, Carlos .
JOURNAL OF MANUFACTURING SYSTEMS, 2019, 52 :131-145
[6]   Energy use analysis and local benchmarking of manufacturing lines [J].
ElMaraghy, Hoda A. ;
Youssef, Ayman M. A. ;
Marzouk, Ahmed M. ;
ElMaraghy, Waguih H. .
JOURNAL OF CLEANER PRODUCTION, 2017, 163 :36-48
[7]   The evolution and future of manufacturing: A review [J].
Esmaeilian, Behzad ;
Behdad, Sara ;
Wang, Ben .
JOURNAL OF MANUFACTURING SYSTEMS, 2016, 39 :79-100
[8]  
Gajic Zoran, 2003, Linear Dynamic Systems And Signals
[9]  
Lofberg J., 2004, IEEE INT C ROB AUT T
[10]   Energy-efficient permutation flow shop scheduling problem using a hybrid multi-objective backtracking search algorithm [J].
Lu, Chao ;
Gao, Liang ;
Li, Xinyu ;
Pan, Quanke ;
Wang, Qi .
JOURNAL OF CLEANER PRODUCTION, 2017, 144 :228-238