Reconfigurable Production Line Design Method for Human Workers – Robotic Cell Collaborated Line Considering Worker’s Attitude Toward Work
Daiki Kajita and Nobuyuki Moronuki
Tokyo Metropolitan University
6-6 Asahigaoka, Hino, Tokyo 191-0065, Japan
In recent years, manufacturing companies have faced difficulties in securing sufficient production capabilities at factories because of many regional risks, such as natural calamities and epidemics. A production line should be designed to be reconfigured to adapt to various risks for satisfying its demands. This paper proposes a flexible and reconfigurable production line composed of a combination of line workers and multipurpose equipment called robotic cells. A robotic cell performs work (similar to a worker) using a programmable arm robot. The required tasks are allocated to workers or robots. However, it is difficult to design the line configuration and task allocation, because the number of combinations is large. Additionally, the production efficiency fluctuates depending on the correlations between the worker’s attitude, skill level, and allocated tasks. This paper describes a production-line design method using a genetic algorithm. The proposed method maximizes the availability ratio and minimizes the cost of the production line by considering the worker’s attitude toward the work.
-  Y. Yamazaki, K. Sugito, and S. Tsuchiya, “Development of flexible manufacturing system,” J. Robot. Mechatron., Vol.26, No.4, pp. 426-433, doi: 10.20965/jrm.2014.p0426, 2014.
-  J. Rybicka, A. Tiwari, and S. Enticott, “Testing a Flexible Manufacturing System Facility Production Capacity through Discrete Event Simulation: Automotive Case Study,” Int. J. of Industrial and Manufacturing Engineering, Vol.10, No.4, pp. 719-723, doi: 10.5281/zenodo.1123707, 2016.
-  P. Tsarouchi, A.-S. Matthaiakis, S. Makris, and G. Chryssolouris, “On a human-robot collaboration in an assembly cell,” Int. J. of Computer Integrated Manufacturing, Vol.30, No.6, pp. 580-589, doi: 10.1080/0951192X.2016.1187297, 2016.
-  J. C. Mateus, D. Claeys, V. Limère, J. Cottyn, and E.-H. Aghezzaf, “A structured methodology for the design of a human-robot collaborative assembly workplace,” The Int. J. of Advanced Manufacturing Technology, Vol.102, No.5-8, pp. 2663-2681, doi: 10.1007/s00170-019-03356-3, 2019.
-  A. Rega, F. Vitolo, C. Di Marino, and S. Patalano, “A knowledge-based approach to the layout optimization of human–robot collaborative workplace,” Int. J. on Interactive Design and Manufacturing, Vol.15, No.1, pp. 133-135, doi: 10.1007/s12008-020-00742-0, 2021.
-  X. Niu, H. Ding, and Y. Xiong, “A hierarchical approach to generating precedence graphs for assembly planning,” Int. J. of Machine Tools & Manufacture, Vol.43, No.14, pp. 1473-1486, doi: 10.1016/S0890-6955(03)00168-8, 2003.
-  A. Enomoto, D. Tsutsumi, N. Yamamoto, Q. Bayasi, T. Suzuki, K. Iida, T, Sasaki, J. Hirai, T. Shibata, K. Okita, E. Ohtsu, K. Kuroya, and S. Nemoto, “Generation Algorithm of Assembly Sequence Based on Assembly Order Rules and Geometric Constraints for the Purpose of Fast Automatic Generation of Assembly Animation and 3D Work Instruction Sheets,” J. of the Japan Society for Precision Engineering, Vol.79, No.8, pp. 790-797, doi: 10.2493/jjspe.79.790, 2013 (in Japanese).
-  M. Sugi, I. Matsumura, Y. Tamura, T. Arai, and J. Ota, “Usability Analysis of Information on Worker’s Hands in Animated Assembly Manuals,” Int. J. Automation Technol., Vol.12, No.4, pp. 524-532, doi: 10.20965/ijat.2018.p0524, 2018.
-  D. Kajita, A. Enomoto, D. Tsutsumi, and N. Moronuki, “Assembly motion automatic planning technology using geometric constraint conditions (Calculation of start, end and via point for parts assembly task using 3D CAD data),” Trans. of the JSME, Vol.85, No.875, p. 18-00491, doi: 10.1299/transjsme.18-00491, 2019 (in Japanese).
-  F. M. Proctor, G. van der Hoorn, and R. Lipman, “Automating Robot Planning Using Product and Manufacturing Information,” Procedia CIRP, Vol.43, pp. 208-213, doi: 10.1016/j.procir.2016.02.139, 2016.
-  J. Michniewicz, G. Reinhart, and S. Boschert, “CAD-Based Automated Assembly Planning for Variable Products in Modular Production Systems,” Procedia CIRP, Vol.44, pp. 44-49, doi: 10.1016/j.procir.2016.02.016, 2016.
-  C. Kardos, A. Kovács, and J. Váncza, “Towards Feature-based Human-robot Assembly Process Planning,” Procedia CIRP, Vol.57, pp. 516-521, doi: 10.1016/j.procir.2016.11.089, 2016.
-  L. Johannsmeier and S. Haddadin, “A Hierarchical Human-Robot Interaction-Planning Framework for Task Allocation in Collaborative Industrial Assembly Processes,” IEEE Robotics and Automation Letters, Vol.2, No.1, pp. 41-48, doi: 10.1109/LRA.2016.2535907, 2017.
-  J. E. Gomar, C. T. Haas, and D. P. Morton, “Assignment and Allocation Optimization of Partially Multiskilled Workforce,” J. of Construction Engineering and Management, Vol.128, No.2, pp. 103-109, doi: 10.1061/(ASCE)0733-9364(2002)128:2(103), 2002.
-  F. Ranz, V. Hummel, and W. Sihn, “Capability-based Task Allocation in Human-robot Collaboration,” Procedia Manufacturing, Vol.9, pp. 182-189, doi: 10.1016/j.promfg.2017.04.011, 2017.
-  R. D. Parashakti and M. Ekhsan, “The Effect of Discipline and Motivation on Employee Performance in PT Samsung Elektronik Indonesia,” J. of Research in Business, Economics, and Education, Vol.2, No.3, pp. 653-660, 2020.
-  M. Rafiq and T. Chin, “Three-Way Interaction Effect of Job Insecurity, Job Embeddedness and Career Stage on Life Satisfaction in A Digital Era,” Int. J. of Environmental Research and Public Health, Vol.16, No.9, Aricle 1580, doi: 10.3390/ijerph16091580, 2019.
-  T. Ohashi, M. Iwata, S. Arimoto, and S. Miyakawa, “Extended Assemblability Evaluation Method (AEM),” JSME Int. J. Series C: Mechanical Systems, Machine Elements and Manufacturing, Vol.45, No.2, pp. 567-574, doi: 10.1299/jsmec.45.567, 2002.
-  A. A. Malik and A. Bilberg, “Complexity-based task allocation in human-robot collaborative assembly,” Industrial Robot: the Int. J. of Robotics Research and Application, Vol.46, No.4, pp. 471-480, doi: 10.1108/IR-11-2018-0231, 2019.
-  K. Hirana, T. Nozaki, T. Suzuki, S. Okuma, K. Itabashi, and F. Fujiwara, “Quantitative Evaluation for Skill Controller Based on Comparison with Human Demonstration,” IEEE Trans. on Control System Technology, Vol.12, No.4, pp. 609-619, doi: 10.1109/TCST.2004.824955, 2004.
-  M. S. Erden and B. Marić, “Assisting manual welding with robot,” Robotics and Computer-Integrated Manufacturing, Vol.27, No.4, pp. 818-828, doi: 10.1016/j.rcim.2011.01.003, 2011.
-  U. Körner, K. Müller-Thur, T. Lunau, N. Dragano, P. Angerer, and A. Buchner, “Perceived stress in human-machine interaction in modern manufacturing environments – Results of a qualitative interview study,” Stress & Health, Vol.35, No.2, pp. 187-199, doi: 10.1002/smi.2853, 2019.
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