Optimal production inventory decision with learning and fatigue behavioral effects in labor-intensive manufacturing

被引:6
作者
Fu, K. [1 ]
Chen, Zh [2 ]
Zhang, Y. [2 ]
Wee, H. M. [3 ]
机构
[1] Guangdong Univ Finance, Sch Business Adm, Dept Logist Management, Guangzhou 510521, Peoples R China
[2] Sun Yat Sen Univ, Sch Business, Dept Management Sci, Guangzhou 510275, Peoples R China
[3] Chung Yuan Christian Univ, Dept Ind Engn, 200 Chung Pei Rd, Taoyuan 32023, Taiwan
基金
中国国家自然科学基金;
关键词
Behavioral economics; Productivity; Human factor; Learning effect; Fatigue effect; Production inventory decision; TIME-VARYING DEMAND; PRODUCTION LOT-SIZE; CURVE; MODEL; REWORK; ERRORS;
D O I
10.24200/sci.2018.50614.1788
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Behavioral economics has received much attention recently. Learning and fatigue are two typical behavioral phenomena in industrial production operation processes. The existence of learning and fatigue results in a dynamic change in productivity. In this paper, a classical Economic Production Quantity (EPQ) model is extended to consider the behavioral economic value of learning and fatigue. Based on a real case study, each production cycle was divided into five phases, namely learning phase, stable phase, fatigue phase, fatigue recovery (rest) phase, and relearning phase. The new production inventory decision model was formulated with dynamic productivity and learning-stable-fatigue-recovery effect. Numerical simulation and sensitivity analysis showed that appropriate rest would alleviate employees' fatigue and increase productivity, resulting in a lower average production cost. On the other hand, when the rest time was too long, exceeding a certain value, it led to the decline of the actual labor productivity, resulting in an increase in the average cost of the system. (C) 2020 Sharif University of Technology. All rights reserved.
引用
收藏
页码:918 / 934
页数:17
相关论文
共 39 条
[31]  
Okogbaa O.G., 1983, EMPIRICAL MODEL MENT
[32]   MATHEMATICAL-MODELING OF THE EFFECT OF HUMAN LEARNING IN THE FINITE PRODUCTION INVENTORY MODEL [J].
SALAMEH, MK ;
ABDULMALAK, MAU ;
JABER, MY .
APPLIED MATHEMATICAL MODELLING, 1993, 17 (11) :613-615
[33]  
Sturm J.C., 2017, J INTELL MANUF, V28, P1
[34]   Optimal trade credit and lot size policies in economic production quantity models with learning curve production costs [J].
Teng, Jinn-Tsair ;
Lou, Kuo-Ren ;
Wang, Lu .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2014, 155 :318-323
[35]   Steady-state skill levels of workers in learning and forgetting environments: A dynamical system analysis [J].
Teyarachakul, Sunantha ;
Coemez, Dogan ;
Tarakci, Hakan .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2014, 232 (01) :9-21
[36]   Effect of Learning and Forgetting on Batch Sizes [J].
Teyarachakul, Sunantha ;
Chand, Suresh ;
Ward, James .
PRODUCTION AND OPERATIONS MANAGEMENT, 2011, 20 (01) :116-128
[37]  
Wright T. P., 1936, Journal of the Aeronautical Sciences, V3, P122, DOI DOI 10.2514/8.155
[38]   Vendor managed inventory (VMI) with consignment considering learning and forgetting effects [J].
Zanoni, Simone ;
Jaber, Mohamad Y. ;
Zavanella, Lucio E. .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2012, 140 (02) :721-730
[39]   Opportunities for research in behavioral operations management [J].
Zhao, Xiaobo ;
Zhao, Xiande ;
Wu, Yaozhong .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2013, 142 (01) :1-2