Abstract: For efficient use of value stream mapping (VSM) for multi-varieties and small batch production in a data-rich environment enabled by Industry 4.0 technologies, a systematic framework of VSM to rejuvenate traditional lean tools is proposed. It addresses the issue that traditional VSM requires intensive on-site investigation and replies on experience, which hinders decision-making efficiency in dynamic and complex environments. The proposed framework follows the data-information-knowledge hierarchy model, and demonstrates how data can be collected in a production workshop, processed into information, and then interpreted into knowledge. In this paper, the necessity and limitations of VSM in automated root cause analysis are first discussed, with a literature review on lean production tools, especially VSM and VSM-based decision making in Industry 4.0. An implementation case of a furniture manufacturer in China is presented, where decision tree algorithm was used for automated root cause analysis. The results indicate that automated VSM can make good use of production data to cater for multi-varieties and small batch production with timely on-site waste identification and analysis. The proposed framework is also suggested as a guideline to renew other lean tools for reliable and efficient decision-making.

工业4.0时代精益生产的自动化价值流分析框架

[1]Badia A, 2014. Data, information, knowledge: an information science analysis. Journal of the Association for Information Science and Technology, 65(6):1279-1287.

[2]Balaji V, Venkumar P, Sabitha MS, et al., 2020. DVSMS: dynamic value stream mapping solution by applying IIoT. Sādhanā, 45(1):38.

[3]Buer SV, Strandhagen JO, Chan FTS, 2018. The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda. International Journal of Production Research, 56(8):2924-2940.

[4]Chen JC, Chen KM, 2014. Application of ORFPM system for lean implementation: an industrial case study. The International Journal of Advanced Manufacturing Technology, 72(5-8):839-852.

[5]Deuse J, Weisner K, Hengstebeck A, et al., 2015. Gestaltung von produktionssystemen im kontext von industrie 4.0. In: Botthof A, Hartmann EA (Eds.), Zukunft der Arbeit in Industrie 4.0. Springer Vieweg, Berlin, Germany, p.99-109 (in German).

[6]Dombrowski U, Richter T, Krenkel P, 2017. Interdependencies of industrie 4.0 & lean production systems: a use cases analysis. Procedia Manufacturing, 11:1061-1068.

[7]Dotoli M, Fanti MP, Rotunno G, et al., 2011. A lean manufacturing procedure using value stream mapping and the analytic hierarchy process. Proceedings of IEEE International Conference on Systems, Man, and Cybernetics, p.1193-1198.

[8]Drath R, Horch A, 2014. Industrie 4.0: hit or hype? [industry forum]. IEEE Industrial Electronics Magazine, 8(2):56-58.

[9]Fonseca LM, 2018. Industry 4.0 and the digital society: concepts, dimensions and envisioned benefits. Proceedings of the International Conference on Business Excellence, 12(1):386-397.

[10]Gao Q, Shi RB, Wang G, 2016. Construction of intelligent manufacturing workshop based on lean management. Procedia CIRP, 56:599-603.

[11]Hartmann L, Meudt T, Seifermann S, et al., 2018. Value stream method 4.0: holistic method to analyse and design value streams in the digital age. Procedia CIRP, 78:249-254.

[12]Huang ZY, Kim J, Sadri A, et al., 2019. Industry 4.0: development of a multi-agent system for dynamic value stream mapping in SMEs. Journal of Manufacturing Systems, 52:1-12.

[13]Kagermann H, Wahlster W, Helbig J, 2013. Securing the Future of German Manufacturing Industry: Recommendations for Implementing the Strategic Initiative Industrie 4.0. Final Report of the Industrie 4.0 Working Group.

[14]Khanchanapong T, Prajogo D, Sohal AS, et al., 2014. The unique and complementary effects of manufacturing technologies and lean practices on manufacturing operational performance. International Journal of Production Economics, 153:191-203.

[15]Kolberg D, Knobloch J, Zühlke D, 2017. Towards a lean automation interface for workstations. International Journal of Production Research, 55(10):2845-2856.

[16]Ku CC, Chien CF, Ma KT, 2020. Digital transformation to empower smart production for industry 3.5 and an empirical study for textile dyeing. Computers & Industrial Engineering, 142:106297.

[17]Lian YH, van Landeghem H, 2007. Analysing the effects of lean manufacturing using a value stream mapping-based simulation generator. International Journal of Production Research, 45(13):3037-3058.

[18]Lins T, Oliveira RAR, 2020. Cyber-physical production systems retrofitting in context of industry 4.0. Computers & Industrial Engineering, 139:106193.

[19]Longo F, Nicoletti L, Padovano A, 2017. Smart operators in industry 4.0: a human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context. Computers & Industrial Engineering, 113:144-159.

[20]Ma J, Wang Q, Zhao ZB, 2017. SLAE-CPS: smart lean automation engine enabled by cyber-physical systems technologies. Sensors, 17(7):1500.

[21]Mayr A, Weigelt M, Kühl A, et al., 2018. Lean 4.0–a conceptual conjunction of lean management and industry 4.0. Procedia CIRP, 72:622-628.

[22]Meudt T, Metternich J, Abele E, 2017. Value stream mapping 4.0: holistic examination of value stream and information logistics in production. CIRP Annals, 66(1):413-416.

[23]Moeuf A, Pellerin R, Lamouri S, et al., 2018. The industrial management of SMEs in the era of industry 4.0. International Journal of Production Research, 56(3):1118-1136.

[24]Papacharalampopoulos A, Giannoulis C, Stavropoulos P, et al., 2020. A digital twin for automated root-cause search of production alarms based on KPIs aggregated from IoT. Applied Sciences, 10(7):2377.

[25]Peruzzini M, Gregori F, Luzi A, et al., 2017. A social life cycle assessment methodology for smart manufacturing: the case of study of a kitchen sink. Journal of Industrial Information Integration, 7:24-32.

[26]Prinz C, Kreggenfeld N, Kuhlenkotter B, 2018. Lean meets industrie 4.0–a practical approach to interlink the method world and cyber-physical world. Procedia Manufacturing, 23:21-26.

[27]Rahani AR, Al-Ashraf M, 2012. Production flow analysis through value stream mapping: a lean manufacturing process case study. Procedia Engineering, 41:1727-1734.

[28]Ramadan M, 2016. RFID-enabled Dynamic Value Stream Mapping for Smart Real-time Lean-based Manufacturing System. PhD Thesis, University of Duisburg-Essen, Duisburg, Germany.

[29]Ramadan M, Al-Maimani H, Noche B, 2017. RFID-enabled smart real-time manufacturing cost tracking system. The International Journal of Advanced Manufacturing Technology, 89(1-4):969-985.

[30]Ramadan M, Salah B, Othman M, et al., 2020. Industry 4.0-based real-time scheduling and dispatching in lean manufacturing systems. Sustainability, 12(6):2272.

[31]Rohani JM, Zahraee SM, 2015. Production line analysis via value stream mapping: a lean manufacturing process of color industry. Procedia Manufacturing, 2:6-10.

[32]Rossini M, Costa F, Staudacher AP, et al., 2019. Industry 4.0 and lean production: an empirical study. IFAC-PapersOnLine, 52(13):42-47.

[33]Sanders A, Elangeswaran C, Wulfsberg J, 2016. Industry 4.0 implies lean manufacturing: research activities in industry 4.0 function as enablers for lean manufacturing. Journal of Industrial Engineering and Management, 9(3):811-833.

[34]Schönemann M, Kurle D, Herrmann C, et al., 2016. Multi-product EVSM simulation. Procedia CIRP, 41:334-339.

[35]Shahin M, Chen FF, Bouzary H, et al., 2020. Integration of lean practices and industry 4.0 technologies: smart manufacturing for next-generation enterprises. The International Journal of Advanced Manufacturing Technology, 107(5-6):2927-2936.

[36]Solding P, Gullander P, 2009. Concepts for simulation based value stream mapping. Proceedings of the Winter Simulation Conference, p.2231-2237.

[37]Stadnicka D, Litwin P, 2019. Value stream mapping and system dynamics integration for manufacturing line modelling and analysis. International Journal of Production Economics, 208:400-411.

[38]Tamás P, 2016. Application of value stream mapping at flexible manufacturing systems. Key Engineering Materials, 686:168-173.

[39]Uriarte AG, Ng AHC, Moris MU, 2018. Supporting the lean journey with simulation and optimization in the context of industry 4.0. Procedia Manufacturing, 25:586-593.

[40]Wagner T, Herrmann C, Thiede S, 2017. Industry 4.0 impacts on lean production systems. Procedia CIRP, 63:125-131.

[41]Xu LD, Xu EL, Li L, 2018. Industry 4.0: state of the art and future trends. International Journal of Production Research, 56(8):2941-2962.