DATA ANALYTICS SUPPORTING LEAN MANUFACTURING TOWARDS INDUSTRY 4.0 THROUGH SIMULATION: A REVIEW

Soufhwee Abdul Rahman, Effendi Bin Mohamad, Azrul Abdul Rahman, Ihwan Hamdala, Aisyah Larasati, supawi pawenang, Teruaki Ito

Abstract


The Lean Manufacturing (LM) system has been increasingly used in many industrial applications, worldwide, in the last 3 decades. The LM system is based on sound philosophy and includes several tools and principles, which permit its usage in eliminating wastes and decreasing the production costs. Though the conventional LM is helpful, the new paradigm, i.e., Industry 4.0, has started challenging the system. The traditional LM system cannot analyse the complex issues present in the existing competitive market on its own. This is because the Industry 4.0 is based on data which is more diverse, complex and fast. In this review, the researchers have attempted to identify the solution for the current scenario. Literature survey showed that simulation was a relevant tool that could be used for addressing the complexity-based issues related to the new concept. Though the combination of the simulation and LM system helped in understanding the problems, there still existed a gap in the LM system with regards to the merging of the 2 technologies of Industry 4.0. 

Keywords


Data analytics ; simulation ; industry 4.0 ; lean manufacturing

Full Text:

PDF

References


Roblek V, Meško M, Krapež A. A complex view of industry 4.0. Sage Open. 2016 Jun;6(2):2158244016653987.

Nordin N, Deros BM, Wahab DA. A survey on lean manufacturing implementation in Malaysian automotive industry. International Journal of Innovation, Management and Technology. 2010 Oct 1;1(4):374.

Stecher BM, Kirby SN, Barney H, Pearson ML, Chow M. Organizational improvement and accountability: Lessons for education from other sectors. Rand Corporation; 2004 Feb 19.

Womack JP, Womack JP, Jones DT, Roos D. Machine that changed the world. Simon and Schuster; 1990.

Mostafa S, Dumrak J, Soltan H. A framework for lean manufacturing implementation. Production & Manufacturing Research. 2013 Dec 1;1(1):44-64.

Womack JP, Jones DT, Roos D. The machine that changed the world: the story of lean production. 1991. New York: Rawson Associates. 2003.

Womack JP, Jones DT. Lean thinking—banish waste and create wealth in your corporation. Journal of the Operational Research Society. 1997 Nov 1;48(11):1148-.

Hines P, Holweg M, Rich N. Learning to evolve: a review of contemporary lean thinking. International journal of operations & production management. 2004 Oct 1;24(10):994-1011.

Wagner T, Herrmann C, Thiede S. Industry 4.0 impacts on lean production systems. Procedia CIRP 63: 125–131.

Zhou K, Liu T, Zhou L. Industry 4.0: Towards future industrial opportunities and challenges. In2015 12th International conference on fuzzy systems and knowledge discovery (FSKD) 2015 Aug 15 (pp. 2147-2152). IEEE.

The Network Cisco’s Technology News Site. Doug Webster: Cisco Visual Networking Index Predicts Near-Tripling of IP Traffic by 2020. Available from: https://newsroom.cisco.com/press-release-content?articleId=177121.

[Accessed 10th November 2019].

Schröders T, Cruz-Machado V. Sustainable lean implementation: An assessment tool. InProceedings of the Ninth International Conference on Management Science and Engineering Management 2015 (pp. 1249-1264). Springer, Berlin, Heidelberg.

Sundar R, Balaji AN, Kumar RS. A review on lean manufacturing implementation techniques. Procedia Engineering. 2014 Jan 1;97:1875-85.

Tortorella GL, Fettermann D. Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies. International Journal of Production Research. 2018 Apr 18;56(8):2975-87.

Barton D, Court D. Making advanced analytics work for you. Harvard business review. 2012 Oct 1;90(10):78-83.

Detty RB, Yingling JC. Quantifying benefits of conversion to lean manufacturing with discrete event simulation: a case study. International Journal of Production Research. 2000 Jan 1;38(2):429-45.

Sargent RG. Verification and validation of simulation models. Journal of simulation. 2013 Feb 1;7(1):12-24.

Mohamad E, Ito T, Yuniawan D. Quantifying benefits of lean manufacturing tools implementation with simulation in coolant hose factory. Journal of Human Capital Development (JHCD). 2013 Dec 31;6(2):13-26.

Mohamad EB, Ibrahim MA, Sukarma L, Rahman MA, Shibghatullah AS, Salleh MR. Improved decision making in lean manufacturing using a simulation-based approach. International Journal of Agile Systems and Management. 2017;10(1):34-48.

Detty RB, Yingling JC. Quantifying benefits of conversion to lean manufacturing with discrete-event simulation: a case study. International Journal of Production Research. 2000 Jan 1;38(2):429-45.

Hsieh, S.J.T., 2002. Hybrid analytic and simulation models for assembly line design and production planning. Simulation Modelling Practice and Theory, 10(1-2), pp.87-108.

Abdulmalek FA, Rajgopal J. Analyzing the benefits of lean manufacturing and value stream mapping via simulation: A process sector case study. International Journal of production economics. 2007 May 1;107(1):223-36.

Anand G, Kodali R. Development of a framework for implementation of lean manufacturing systems. International Journal of Management Practice. 2009 Dec 2;4(1):95-116.

Ali M, Cullinane J. A study to evaluate the effectiveness of simulation-based decision support system in ERP implementation in SMEs. Procedia Technology. 2014 Jan 1;16:542-52.

Wang TK, Yang T, Yang CY, Chan FT. Lean principles and simulation optimization for emergency department layout design. Industrial Management & Data Systems. 2015 May 11;115(4):678-99.

Yang T, Kuo Y, Su CT, Hou CL. Lean production system design for fishing net manufacturing using lean principles and simulation optimization. Journal of Manufacturing Systems. 2015 Jan 1;34:66-73.

Villarreal B, Garza-Reyes JA, Kumar V. A lean thinking and simulation-based approach for the improvement of routing operations. Industrial Management & Data Systems. 2016 Jun 13;116(5):903-25.

Al-Fandi L, Lam SS, Ramakrishnan S. A framework to reduce problem complexity using lean concepts with simulation. InIIE Annual Conference. Proceedings 2011 (p. 1). Institute of Industrial and Systems Engineers (IISE).

Gurumurthy A, Kodali R. Design of lean manufacturing systems using value stream mapping with simulation: a case study. Journal of manufacturing technology management. 2011 May 3;22(4):444-73.

Mohamad E, Ibrahim MA, Shibghatullah AS, Rahman MA, Sulaiman MA, Rahman AA, Abdullah S, Salleh MR. A simulation-based approach for lean manufacturing tools implementation: a review. ARPN Journal of Engineering and Applied Sciences. 2016;11(5):3400-6.

Wy, J., Jeong, S., Kim, B.I., Park, J., Shin, J., Yoon, H. and Lee, S., 2011. A data-driven generic simulation model for logistics-embedded assembly manufacturing lines. Computers & Industrial Engineering, 60(1), pp.138-147.

Lee J, Kao HA, Yang S. Service innovation and smart analytics for industry 4.0 and big data environment. Procedia Cirp. 2014 Jan 1;16:3-8.

Rane AB, Sudhakar DS, Rane S. Improving the performance of assembly line: Review with case study. In2015 International Conference on Nascent Technologies in the Engineering Field (ICNTE) 2015 Jan 9 (pp. 1-14). IEEE.

Nunes IL. Integration of ergonomics and lean six sigma. A model proposal. Procedia Manufacturing. 2015 Jan 1;3:890-7.

Fanti MP, Iacobellis G, Ukovich W, Boschian V, Georgoulas G, Stylios C. A simulation-based Decision Support System for logistics management. Journal of Computational Science. 2015 Sep 1;10:86-96.

Salama S, Eltawil AB. A Decision Support System Architecture Based on Simulation Optimization for Cyber-Physical Systems. Procedia Manufacturing. 2018 Jan 1;26:1147-58.

Rao H, Goutam D, Basu S. Database Structure for a Multi-Stage Stochastic Optimization-Based Decision Support System for Asset–Liability Management of a Life Insurance Company. IIM Bangalore Research Paper. 2014 Aug 12(467).

Goienetxea Uriarte A, Ng AH, Urenda Moris M. Supporting the lean journey with simulation and optimization in the context of Industry 4.0. InProcedia Manufacturing 2018 (Vol. 25, pp. 586-593).

Ferrera E, Rossini R, Baptista AJ, Evans S, Hovest GG, Holgado M, Lezak E, Lourenço EJ, Masluszczak Z, Schneider A, Silva EJ. Toward Industry 4.0: efficient and sustainable manufacturing leveraging MAESTRI total efficiency framework. International Conference on Sustainable Design and Manufacturing 2017 Apr 26 (pp. 624-633). Springer, Cham.

Tao F, Qi Q, Liu A, Kusiak A. Data-driven smart manufacturing. Journal of Manufacturing Systems. 2018 Jul 1;48:157-69.

Goodall P, Sharpe R, West A. A data-driven simulation to support remanufacturing operations. Computers in Industry. 2019 Feb 1;105:48-60.


Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.