Design of Human-Centered Collaborative Assembly Workstations for the Improvement of Operators’ Physical Ergonomics and Production Efficiency: A Case Study

Industrial collaborative robotics is one of the main enabling technologies of Industry 4.0. Collaborative robots are innovative cyber-physical systems, which allow safe and efficient physical interactions with operators by combining typical machine strengths with inimitable human skills. One of the main uses of collaborative robots will be the support of humans in the most physically stressful activities through a reduction of work-related biomechanical overload, especially in manual assembly activities. The improvement of operators’ occupational work conditions and the development of human-centered and ergonomic production systems is one of the key points of the ongoing fourth industrial revolution. The factory of the future should focus on the implementation of adaptable, reconfigurable, and sustainable production systems, which consider the human as their core and valuable part. Strengthening actual assembly workstations by integrating smart automation solutions for the enhancement of operators’ occupational health and safety will be one of the main goals of the near future. In this paper, the transformation of a manual workstation for wire harness assembly into a collaborative and human-centered one is presented. The purpose of the work is to present a case study research for the design of a collaborative workstation to improve the operators’ physical ergonomics while keeping or increasing the level of productivity. Results demonstrate that the achieved solution provides valuable benefits for the operators’ working conditions as well as for the production performance of the companies. In particular, the biomechanical overload of the worker has been reduced by 12.0% for the right part and by 28% for the left part in terms of manual handling, and by 50% for the left part and by 57% for the right part in terms of working postures. In addition, a reduction of the cycle time of 12.3% has been achieved.

[1]  Alessio Maria Braccini,et al.  Exploring Organizational Sustainability of Industry 4.0 under the Triple Bottom Line: The Case of a Manufacturing Company , 2018, Sustainability.

[2]  Giovanni Carabin,et al.  Advanced Automation for SMEs in the I4.0 Revolution: Engineering Education and Employees Training in the Smart Mini Factory Laboratory , 2018, 2018 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM).

[3]  Renato Vidoni,et al.  The Opportunities and Challenges of SME Manufacturing Automation: Safety and Ergonomics in Human–Robot Collaboration , 2020, Industry 4.0 for SMEs.

[4]  Renato Vidoni,et al.  An evaluation methodology for the conversion of manual assembly systems into human-robot collaborative workcells , 2019, Procedia Manufacturing.

[5]  L McAtamney,et al.  RULA: a survey method for the investigation of work-related upper limb disorders. , 1993, Applied ergonomics.

[6]  S. M. García,et al.  2014: , 2020, A Party for Lazarus.

[7]  Renato Vidoni,et al.  Implementation of a Laboratory Case Study for Intuitive Collaboration Between Man and Machine in SME Assembly , 2020, Industry 4.0 for SMEs.

[8]  Veronique Limère,et al.  A structured methodology for the design of a human-robot collaborative assembly workplace , 2019, The International Journal of Advanced Manufacturing Technology.

[9]  Uwe Dombrowski,et al.  Interactive Simulation of Human-robot Collaboration Using a Force Feedback Device ☆ , 2017 .

[10]  Dan Högberg,et al.  Virtual Simulation of Human-Robot Collaboration Workstations , 2018, Advances in Intelligent Systems and Computing.

[11]  Kagermann Henning.  Recommendations for implementing the strategic initiative INDUSTRIE 4.0 , 2013 .

[12]  Sofie Burggraeve,et al.  Model-based Multi-Attribute Collaborative Production Cell Layout Optimization , 2019, 2019 20th International Conference on Research and Education in Mechatronics (REM).

[13]  T. Waters,et al.  Efficacy of the Revised NIOSH Lifting Equation to Predict Risk of Low Back Pain Due to Manual Lifting: Expanded Cross-Sectional Analysis , 2011, Journal of occupational and environmental medicine.

[14]  A Garg,et al.  Revised NIOSH equation for the design and evaluation of manual lifting tasks. , 1993, Ergonomics.

[15]  Ray Y. Zhong,et al.  Intelligent Manufacturing in the Context of Industry 4.0: A Review , 2017 .

[16]  Alexander Mertens,et al.  Human-Robot Collaboration in Manual Assembly – A Collaborative Workplace , 2018, Advances in Intelligent Systems and Computing.

[17]  Tom Chippendale.  About the company , 2015 .

[18]  Ole Madsen,et al.  Robot skills for manufacturing , 2016 .

[19]  Giovanni Belingardi,et al.  Safety Design and Development of a Human-Robot Collaboration Assembly Process in the Automotive Industry , 2018 .

[20]  MadsenOle,et al.  Robot skills for manufacturing , 2016 .

[21]  Klaus Bengler,et al.  Human Centered Assistance Applications for the working environment of the future , 2015 .

[22]  Bram Vanderborght,et al.  Design of a collaborative architecture for human-robot assembly tasks , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[23]  Daniela Colombini,et al.  Risk Assessment and Management of Repetitive Movements and Exertions of Upper Limbs , 2002 .