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Research Article

Linking data science to lean production: a model to support lean practices

, &
Pages 6866-6887 | Received 30 Oct 2020, Accepted 13 Jun 2021, Published online: 06 Jul 2021

References

  • Abd Rahman, M. S., E. Mohamad, and A. A. Rahman. 2020. “Enhancement of Overall Equipment Effectiveness (OEE) Data by Using Simulation as Decision Making Tools for Line Balancing.” Indonesian Journal of Electrical Engineering and Computer Science 18 (2): 1040–1047.
  • Addo-Tenkorang, R., and P. T. Helo. 2016. “Big Data Applications in Operations/Supply-Chain Management: A Literature Review.” Computers & Industrial Engineering 101: 528–543.
  • Agarwal, R., and V. Dhar. 2014. “Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research.” Information Systems Research 25 (3): 443–448.
  • Agostini, Lara, and Roberto Filippini. 2019. “Organizational and Managerial Challenges in the Path Toward Industry 4.0.” European Journal of Innovation Management 22 (3): 406–421.
  • Akter, S., S. F. Wamba, A. Gunasekaran, R. Dubey, and S. J. Childe. 2016. “How to Improve Firm Performance Using big Data Analytics Capability and Business Strategy Alignment?” International Journal of Production Economics 182: 113–131.
  • Aldrich, C., and L. Auret. 2013. Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods. London: Springer.
  • Alkhoraif, A., H. Rashid, and P. McLaughlin. 2019. “Lean Implementation in Small and Medium Enterprises: Literature Review.” Operations Research Perspectives 6: 100089.
  • Antony, J., S. Gupta, and E. V. Gijo. 2018. “Ten Commandments of Lean Six Sigma: A Practitioners’ Perspective.” International Journal of Productivity and Performance Management 67 (6): 1033–1044.
  • Antony, J., and M. Sony. 2019. “An Empirical Study Into the Limitations and Emerging Trends of Six Sigma in Manufacturing and Service Organisations.” International Journal of Quality & Reliability Management 37 (3): 470–493.
  • Ashton, Triss, Nicholas Evangelopoulos, and Victor R Prybutok. 2015. “Quantitative Quality Control from Qualitative Data: Control Charts with Latent Semantic Analysis.” Quality & Quantity 49 (3): 1081–1099.
  • Baesens, B. 2014. Analytics in a Big Data World: The Essential Guide to Data Science and its Applications. New Jersey: John Wiley & Sons.
  • Bai, C., A. Satir, and J. Sarkis. 2019. “Investing in Lean Manufacturing Practices: An Environmental and Operational Perspective.” International Journal of Production Research 57 (4): 1037–1051.
  • Bailer, A. J., and N. I. Fisher. 2020. “Discussion of “A Review of Data Science in Business and Industry and a Future View”.” Applied Stochastic Models in Business and Industry 36 (1): 20–22.
  • Ballé, F., and M. Ballé. 2005. “Lean Development.” Business Strategy Review 16 (3): 17–22.
  • Barrad, S., S. Gagnon, and R. Valverde. 2020. “An Analytics Architecture for Procurement.” International Journal of Information Technologies and Systems Approach (IJITSA) 13 (2): 73–98.
  • Baryannis, George, Sahar Validi, Samir Dani, and Grigoris Antoniou. 2019. “Supply Chain Risk Management and Artificial Intelligence: State of the Art and Future Research Directions.” International Journal of Production Research 57 (7): 2179–2202.
  • Bazrkar, A., and S. Iranzadeh. 2017. “Prioritization of Lean Six Sigma Improvement Projects Using Data Envelopment Analysis Cross Efficiency Model.” Calitatea 18 (157): 72.
  • Belekoukias, I., J. A. Garza-Reyes, and V. Kumar. 2014. “The Impact of Lean Methods and Tools on the Operational Performance of Manufacturing Organisations.” International Journal of Production Research 52 (18): 5346–5366.
  • Belhadi, A., S. S. Kamble, K. Zkik, A. Cherrafi, and F. E. Touriki. 2020. “The Integrated Effect of Big Data Analytics, Lean Six Sigma and Green Manufacturing on the Environmental Performance of Manufacturing Companies: The Case of North Africa.” Journal of Cleaner Production 252: 119903.
  • Bevilacqua, M., F. E. Ciarapica, and I. De Sanctis. 2017. “Lean Practices Implementation and Their Relationships with Operational Responsiveness and Company Performance: An Italian Study.” International Journal of Production Research 55 (3): 769–794.
  • Bhamu, J., and K. S. Sangwan. 2014. “Lean Manufacturing: Literature Review and Research Issues.” International Journal of Operations & Production Management 34 (7): 876–940.
  • Bittencourt, V. L., Anabela Carvalho Alves, and Celina Pinto Leão. 2021. “Industry 4.0 Triggered by Lean Thinking: Insights from a Systematic Literature Review.” International Journal of Production Research 59 (5): 1496–1510.
  • Bortolotti, T., S. Boscari, and P. Danese. 2015. “Successful Lean Implementation: Organizational Culture and Soft Lean Practices.” International Journal of Production Economics 160: 182–201.
  • Buer, S. V., M. Semini, J. O. Strandhagen, and F. Sgarbossa. 2020. “The Complementary Effect of Lean Manufacturing and Digitalisation on Operational Performance.” International Journal of Production Research 59 (7): 1976–1992.
  • Buer, S. V., J. O. Strandhagen, and F. T. Chan. 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.
  • Cancino, C., J. M. Merigó, F. Coronado, Y. Dessouky, and M. Dessouky. 2017. “Forty Years of Computers & Industrial Engineering: A Bibliometric Analysis.” Computers & Industrial Engineering 113: 614–629.
  • Cao, L. 2017. “Data Science: a Comprehensive Overview.” ACM Computing Surveys (CSUR) 50 (3): 1–42.
  • Cavalieri, S., M. G. Salafia, and M. S. Scroppo. 2019. “Integrating OPC UA with web Technologies to Enhance Interoperability.” Computer Standards & Interfaces 61: 45–64.
  • Chadli, N., M. I. Kabbaj, and Z. Bakkoury. 2018, October. “Detection of Dataflow Anomalies in Business Process: An Overview of Modeling Approaches.” In Proceedings of the 12th International Conference on Intelligent Systems: Theories and Applications, 1–6.
  • Chawla, G., S. Bamal, and R. Khatana. 2018. “Big Data Analytics for Data Visualization: Review of Techniques.” International Journal of Computer Applications 182 (21): 37–40.
  • Chen, C., Y. Wang, G. Huang, and H. Xiong. 2019, December. “Hierarchical Demand Forecasting for Factory Production of Perishable Goods.” In 2019 IEEE International Conference on Big Data (Big Data), 188–193. IEEE.
  • Cheng, Y., K. Chen, H. Sun, Y. Zhang, and F. Tao. 2018. “Data and Knowledge Mining with Big Data Towards Smart Production.” Journal of Industrial Information Integration 9 (1): 1–13.
  • Chiarini, A. 2011. “Japanese Total Quality Control, TQM, Deming’s System of Profound Knowledge, BPR, Lean and Six Sigma.” International Journal of Lean Six Sigma 2 (4): 332–355.
  • Choo, A. S., K. W. Linderman, and R. G. Schroeder. 2007. “Method and Context Perspectives on Learning and Knowledge Creation in Quality Management.” Journal of Operations Management 25 (4): 918–931.
  • Ciano, M. P., P. Dallasega, G. Orzes, and T. Rossi. 2020. “One-to-One Relationships Between Industry 4.0 Technologies and Lean Production Techniques: A Multiple Case Study.” International Journal of Production Research 59 (5): 1386–1410.
  • Ciano, M. P., R. Pozzi, T. Rossi, and F. Strozzi. 2019. “How IJPR has Addressed ‘Lean’: A Literature Review Using Bibliometric Tools.” International Journal of Production Research 57 (15): 5284–5317.
  • Concolato, C. E., and L. M. Chen. 2017. “Data Science: A New Paradigm in the Age of Big-Data Science and Analytics.” New Mathematics and Natural Computation 13 (02): 119–143.
  • Conforti, V., A. Bulgarelli, V. Fioretti, F. Gianotti, G. Malaguti, M. Trifoglio, L. A. Antonelli, et al. 2017. “Procedures of Software Integration Test and Release for ASTRI SST-2M prototype Proposed for the Cherenkov Telescope Array.” In Proc. ICALEPS.
  • Cua, K. O., K. E. McKone, and R. G. Schroeder. 2001. “Relationships Between Implementation of TQM, JIT, and TPM and Manufacturing Performance.” Journal of Operations Management 19 (6): 675–694.
  • Dahlgaard-Park, S. M., and J. Pettersen. 2009. “Defining Lean Production: Some Conceptual and Practical Issues.” The TQM Journal 21 (2): 127–142.
  • Dan, Z., X. Jiapeng, Z. Yizhu, W. Jing, H. Siyu, and Z. Xiao. 2020. “Study on Sustainable Urbanization Literature Based on Web of Science, Scopus, and China National Knowledge Infrastructure: A Scientometric Analysis in CiteSpace.” Journal of Cleaner Production 264: 121–537.
  • Davenport, T. H., and D. J. Patil. 2012. “Data Scientist.” Harvard Business Review 90 (5): 70–76.
  • Dennis, P., and J. Shook. 2007. Lean Production Simplified: A Plain Language Guide to the World’s Most Powerful Production Systems. New York: Productivity Press.
  • Deuse, J., C. Heuser, B. Konrad, D. Lenze, T. Maschek, M. Wiegand, and P. Willats. 2018. “Pushing the Limits of Lean Thinking–Design and Management of Complex Production Systems.” In Closing the gap Between Practice and Research in Industrial Engineering, 335–342. Cham: Springer.
  • Dogan, O., and O. F. Gurcan. 2018. “Data Perspective of Lean Six Sigma in Industry 4.0 Era: A Guide to Improve Quality.” In Proceedings of the International Conference on Industrial Engineering and Operations Management Paris.
  • Donoho, David. 2017. “50 Years of Data Science.” Journal of Computational and Graphical Statistics 26 (4): 745–766.
  • Doolen, T. L., and M. E. Hacker. 2005. “A Review of Lean Assessment in Organizations: An Exploratory Study of Lean Practices by Electronics Manufacturers.” Journal of Manufacturing Systems 24 (1): 55–67.
  • Escobar, Carlos A, Jeffrey A Abell, Marcela Hernández-de-Menéndez, and Ruben Morales-Menendez. 2018a. “Process-Monitoring-for-Quality – Big Models.” Procedia Manufacturing 26: 1167–1179.
  • Escobar, C. A., and R. Morales-Menendez. 2019. “Process-Monitoring-for-Quality – A Robust Model Selection Criterion for the Logistic Regression Algorithm.” Manufacturing Letters 22: 6–10.
  • Escobar, Carlos A, Michael A Wincek, Debejyo Chakraborty, and Ruben Morales-Menendez. 2018b. “Process-Monitoring-for-Quality – Applications.” Manufacturing Letters 16: 14–17.
  • Fang, P., Y. Jiang, and R. Y. Zhong. 2018, December. “Real-Time Monitoring of Workshop Status Based on Internet of Things.” In Proceedings of the 2018 48th IEEE International Conference on Computers and Industrial Engineering (CIE 48), Auckland, New Zealand, 2–5.
  • Farooqui, A., K. Bengtsson, P. Falkman, and M. Fabian. 2020. “Towards Data-Driven Approaches in Manufacturing: an Architecture to Collect Sequences of Operations.” International Journal of Production Research 58 (16): 4947–4963.
  • Ferreira, Filipe, Ahm Shamsuzzoha, Americo Azevedo, and Petri Helo. 2015. “Virtual Enterprise Process Monitoring: An Approach Towards Predictive Industrial Maintenance.” Progress in Systems Engineering 330: 285–291.
  • Gaikwad, A., R. Yavari, M. Montazeri, K. Cole, L. Bian, and P. Rao. 2020. “Toward the Digital Twin of Additive Manufacturing: Integrating Thermal Simulations, Sensing, and Analytics to Detect Process Faults.” IISE Transactions 52 (11): 1–14.
  • Gamal Aboelmaged, M. 2010. “Six Sigma Quality: A Structured Review and Implications for Future Research.” International Journal of Quality & Reliability Management 27 (3): 268–317.
  • Gorodov, E. Y. E., and V. V. E. Gubarev. 2013. “Analytical Review of Data Visualization Methods in Application to Big Data.” Journal of Electrical and Computer Engineering 2013: 1–7.
  • Greasley, A., and J. S. Edwards. 2019. “Enhancing Discrete-Event Simulation with Big Data Analytics: A Review.” Journal of the Operational Research Society 72 (2): 247–267.
  • Gruber, T. 2009. “Ontology.” In The Encyclopedia of Database Systems, edited by L. Ling and M. Tamer Özsu, 1963–1965. New York, NY, USA: Springer.
  • Gupta, S., S. Modgil, and A. Gunasekaran. 2020. “Big Data in Lean Six Sigma: A Review and Further Research Directions.” International Journal of Production Research 58 (3): 947–969.
  • Guzikowski, S., J. Bergum, M. Cassidy, L. Dong, C. Lai, B. Patel, M. Randazzo, et al. 2010. “Applications of Model-Based Quality by Design for Reaction Engineering.” AIChE Annual Meeting, Salt Lake City, Utah.
  • Hahn, G. J. 2020. “Industry 4.0: A Supply Chain Innovation Perspective.” International Journal of Production Research 58 (5): 1425–1441.
  • Hajirahimova, M., and M. Ismayilova. 2018. “Big Data Visualization: Existing Approaches and Problems.” Problems of Information Technology 9: 72–83.
  • Hassani, A., and S. A. Ghannouchi. 2017. “Exploring the Integration of Business Process with Nosql Databases in the Context of BPM.” In International Conference on Intelligent Systems Design and Applications, 771–784. Cham: Springer.
  • Hazen, B. T., C. A. Boone, J. D. Ezell, and L. A. Jones-Farmer. 2014. “Data Quality for Data Science, Predictive Analytics, and Big Data in Supply Chain Management: An Introduction to the Problem and Suggestions for Research and Applications.” International Journal of Production Economics 154: 72–80.
  • Hazen, B. T., J. B. Skipper, C. A. Boone, and R. R. Hill. 2018. “Back in Business: Operations Research in Support of Big Data Analytics for Operations and Supply Chain Management.” Annals of Operations Research 270 (1–2): 201–211.
  • He, Q. P., and J. Wang. 2018. “Statistical Process Monitoring as a Big Data Analytics Tool for Smart Manufacturing.” Journal of Process Control 67: 35–43.
  • He, Q. P., J. Wang, and D. Shah. 2019. “Feature Space Monitoring for Smart Manufacturing via Statistics Pattern Analysis.” Computers & Chemical Engineering 126: 321–331.
  • He, Q Peter, Jin Wang, Devarshi Shah, and Nader Vahdat. 2017. “Statistical Process Monitoring for IoT-Enabled Cybermanufacturing: Opportunities and Challenges.” IFAC-PapersOnLine 50 (1): 14946–14951.
  • Heath, F. F., R. Hull, E. Khabiri, M. Riemer, N. Sukaviriya, and R. Vaculín. 2015, June. “Alexandria: Extensible Framework for Rapid Exploration of Social media.” In 2015 IEEE International Congress on Big Data, 483–490. IEEE.
  • Husain, W., L. W. Koon, L. T. Zhao, and N. T. B. A. Aziz. 2016, August. “A Proposed Framework for Enhancing a Supply Chain Management System to Support Flood Disaster Relief Operations.” In 2016 3rd International Conference on Computer and Information Sciences (ICCOINS), 25–30. IEEE.
  • Ito, T., M. S. Abd Rahman, E. Mohamad, A. A. Abd Rahman, and M. R. Salleh. 2020. “Internet of Things and Simulation Approach for Decision Support System in Lean Manufacturing.” Journal of Advanced Mechanical Design Systems, and Manufacturing 14: 2.
  • Jagadish, Hosagrahar Visvesva. 2015. “Big Data and Science: Myths and Reality.” Big Data Research 2 (2): 49–52.
  • Jain, Sanjay, Guodong Shao, and Seung-Jun Shin. 2017. “Manufacturing Data Analytics Using a Virtual Factory Representation.” International Journal of Production Research 55 (18): 5450–5464.
  • Jasti, N. V. K., and R. Kodali. 2015. “Lean Production: Literature Review and Trends.” International Journal of Production Research 53 (3): 867–885.
  • Jones, E. C., M. M. Parast, and S. G. Adams. 2010. “A Framework for Effective Six Sigma Implementation.” Total Quality Management 21 (4): 415–424.
  • Kajikawa, Y., J. Ohno, Y. Takeda, K. Matsushima, and H. Komiyama. 2007. “Creating an Academic Landscape of Sustainability Science: An Analysis of the Citation Network.” Sustainability Science 2 (2): 221–231.
  • Kamble, Sachin S, and Angappa Gunasekaran. 2020. “Big Data-Driven Supply Chain Performance Measurement System: A Review and Framework for Implementation.” International Journal of Production Research 58 (1): 65–86.
  • Kameswari, U Surya, and I. Ramesh Babu. 2016. “Sensor Data Analysis and Anomaly Detection Using Predictive Analytics for Process Industries.” In 2015 IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions (WCI), 1–8. IEEE.
  • Karlsson, C., and P. Åhlström. 1996. “Assessing Changes Towards Lean Production.” International Journal of Operations & Production Management 16 (2): 24–41.
  • Khalid, Z. M., and S. R. Zebaree. 2021. “Big Data Analysis for Data Visualization: A Review.” International Journal of Science and Business 5 (2): 64–75.
  • Khurana, M., and D. Kumar. 2017, December. “The Study of Data Analytics in Inventory Management.” In 2017 International Conference on Infocom Technologies and Unmanned Systems (Trends and Future Directions) (ICTUS), 140–144. IEEE.
  • Kim, S., C. Colicchia, and D. Menachof. 2016. “Ethical Sourcing: An Analysis of the Literature and Implications for Future Research.” Journal of Business Ethics, 1–20. doi:10.1007/s10551-016-3266-8.
  • Kipper, L. M., L. B. Furstenau, D. Hoppe, R. Frozza, and S. Iepsen. 2020. “Scopus Scientific Mapping Production in Industry 4.0 (2011–2018): A Bibliometric Analysis.” International Journal of Production Research 58 (6): 1605–1627.
  • Kluza, K., M. Baran, S. Bobek, and G. J. Nalepa. 2013. “Overview of Recommendation Techniques in Business Process Modeling.” In Proceedings of 9th Workshop on Knowledge Engineering and Software Engineering (KESE9), 46–57.
  • Köksal, G., İ Batmaz, and M. C. Testik. 2011. “A Review of Data Mining Applications for Quality Improvement in Manufacturing Industry.” Expert Systems with Applications 38 (10): 13448–13467.
  • Krafcik, J. F. 1988. “Triumph of the Lean Production System.” Sloan Management Review 30 (1): 41–52.
  • Krenczyk, D., and M. Jagodzinski. 2015. “ERP, APS and Simulation Systems Integration to Support Production Planning and Scheduling.” In 10th International Conference on Soft Computing Models in Industrial and Environmental Applications, 451–461. Cham: Springer.
  • Krumeich, Julian, Dirk Werth, and Peter Loos. 2016. “Prescriptive Control of Business Processes.” Business & Information Systems Engineering 58 (4): 261–280.
  • Kumar, Sandeep, Bhushan S. Purohit, Vikas Manjrekar, Vivek Singh, and Bhupesh Kumar Lad. 2018. “Investigating the Value of Integrated Operations Planning: A Case-Based Approach from Automotive Industry.” International Journal of Production Research 56 (22): 6971–6992.
  • Kuonen, D., and B. Loison. 2019. “Production Processes of Official Statistics and Analytics Processes Augmented by Trusted Smart Statistics: Friends or Foes?” Statistical Journal of the IAOS 35 (4): 615–622.
  • Kutschenreiter-Praszkiewicz, I. 2018. “Machine Learning in SMED.” Journal of Machine Engineering 18 (2): 31–40.
  • Ligęza, A. 2011. “BPMN – A Logical Model and Property Analysis.” Decision Making in Manufacturing and Services 5 (1-2): 57–67.
  • Liker, J. K. 2004. Toyota Way: 14 Management Principles from the World’s Greatest Manufacturer. New York, NY: McGraw-Hill Education.
  • Liker, J. K., and J. Morgan. 2011. “Lean Product Development as a System: A Case Study of Body and Stamping Development at Ford.” Engineering Management Journal 23 (1): 16–28.
  • Linderman, K., R. G. Schroeder, S. Zaheer, and A. S. Choo. 2003. “Six Sigma: A Goal-Theoretic Perspective.” Journal of Operations Management 3 (21): 193–203.
  • Liu, Q., K. Miao, and K. Lin. 2019, June. “Inventory Management of Automobile After-sales Parts Based on Data Mining.” In Proceedings of the 2019 3rd High Performance Computing and Cluster Technologies Conference, 195–199.
  • Lugert, A., A. Batz, and H. Winkler. 2018. “Empirical Assessment of the Future Adequacy of Value Stream Mapping in Manufacturing Industries.” Journal of Manufacturing Technology Management 29 (5): 886–906.
  • MacDuffie, J. P. 1995. “Human Resource Bundles and Manufacturing Performance: Organizational Logic and Flexible Production Systems in the World Auto Industry.” Ilr Review 48 (2): 197–221.
  • Mann, D. 2005. Creating a Lean Culture: Tools to Sustain Lean Conversion. New York: Productivity Press.
  • Marksberry, P. 2012. “Investigating “The Way” for Toyota Suppliers: A Quantitative Outlook on Toyota’s Replicating Efforts for Supplier Development.” Benchmarking: An International Journal 19 (2): 277–298.
  • Marodin, G. A., and T. A. Saurin. 2013. “Implementing Lean Production Systems: Research Areas and Opportunities for Future Studies.” International Journal of Production Research 51 (22): 6663–6680.
  • Mayr, A., M. Weigelt, A. Kühl, S. Grimm, A. Erll, M. Potzel, and J. Franke. 2018. “Lean 4.0 – A Conceptual Conjunction of Lean Management and Industry 4.0.” Procedia Cirp 72: 622–628.
  • McIntosh, R. I., S. J. Culley, A. R. Mileham, and G. W. Owen. 2000. “A Critical Evaluation of Shingo’s SMED (Single Minute Exchange of Die) Methodology.” International Journal of Production Research 38 (11): 2377–2395.
  • Meester, W. J., S. Steiginga, and C. A. Ross. 2017. A Brief History of Scopus: The World’s Largest Abstract and Citation Database of Scientific Literature. Research Analytics: Boosting University Productivity and Competitiveness THROUGH Scientometrics. 31.
  • Mehdiyev, Nijat, Andreas Emrich, Björn P Stahmer, Peter Fettke, and Peter Loos. 2017. “IPRODICT-Intelligent Process Prediction Based on Big Data Analytics.” BPM (Industry Track) 2017: 13–24.
  • Merigó, J. M., W. Pedrycz, R. Weber, and C. de la Sotta. 2018. “Fifty Years of Information Sciences: A Bibliometric Overview.” Information Sciences 432: 245–268.
  • Metzger, A., J. Franke, and T. Jansen. 2019. “Data-Driven Deep Learning for Proactive Terminal Process Management.” In BPM (Industry Forum), 190–201.
  • Meudt, T., J. Metternich, and E. Abele. 2017. “Value Stream Mapping 4.0: Holistic Examination of Value Stream and Information Logistics in Production.” CIRP Annals – Manufacturing Technology 66 (1): 413–416.
  • Meyer, A., L. Pufahl, K. Batoulis, D. Fahland, and M. Weske. 2015. “Automating Data Exchange in Process Choreographies.” Information Systems 53: 296–329.
  • Meyer, A., L. Pufahl, D. Fahland, and M. Weske. 2013. “Modeling and Enacting Complex Data Dependencies in Business Processes.” In Business Process Management. Vol. 8094., edited by F. Daniel, J. Wang, and B. Weber, 171–186. Berlin: Springer.
  • Möldner, A. K., J. A. Garza-Reyes, and V. Kumar. 2020. “Exploring Lean Manufacturing Practices’ Influence on Process Innovation Performance.” Journal of Business Research 106: 233–249.
  • Montoya, F. G., A. Alcayde, R. Baños, and F. Manzano-Agugliaro. 2018. “A Fast Method for Identifying Worldwide Scientific Collaborations Using the Scopus Database.” Telematics and Informatics 35 (1): 168–185.
  • Moreno, R., J. C. Pereira, A. López, A. Mohammed, and P. Pahlevannejad. 2019, November. “Time Series Display for Knowledge Discovery on Selective Laser Melting Machines.” In International Conference on Intelligent Data Engineering and Automated Learning, 280–290. Cham: Springer.
  • Mourtzis, D., P. Papathanasiou, and S. Fotia. 2016. “Lean Rules Identification and Classification for Manufacturing Industry.” Procedia CIRP 50: 198–203.
  • Negrão, L. L. L., M. Godinho Filho, and G. Marodin. 2017. “Lean Practices and Their Effect on Performance: A Literature Review.” Production Planning & Control 28 (1): 33–56.
  • Newman, M. E., and M. Girvan. 2004. “Finding and Evaluating Community Structure in Networks.” Physical Review E 69 (2): 026113.
  • Noori, B., and M. Latifi. 2018. “Development of Six Sigma Methodology to Improve Grinding Processes.” International Journal of Lean Six Sigma 9 (1): 50–63.
  • Osterman, P. 1994. “How Common is Workplace Transformation and Who Adopts It?” ILR Review 47 (2): 173–188.
  • Panizzolo, R. 1998. “Applying the Lessons Learned from 27 Lean Manufacturers: The Relevance of Relationships Management.” International Journal of Production Economics 55 (3): 223–240.
  • Papanagnou, C. I., and O. Matthews-Amune. 2018. “Coping with Demand Volatility in Retail Pharmacies with the Aid of Big Data Exploration.” Computers & Operations Research 98: 343–354.
  • Park, S. H., S. M. Dahlgaard-Park, and D. C. Kim. 2020. “New Paradigm of Lean Six Sigma in the 4th Industrial Revolution Era.” Quality Innovation Prosperity 24 (1): 1–16.
  • Patil, Ranjeet, and Balaji Thiagarajan. 2019. “Design Optimization through Blended Reliability, Six Sigma and Analytics Tools.” In 2019 Annual Reliability and Maintainability Symposium (RAMS), 1–3. IEEE.
  • Petrasch, R., and R. Hentschke. 2016, July. “Process Modeling for Industry 4.0 Applications: Towards an Industry 4.0 Process Modeling Language and Method.” In 2016 13th International Joint Conference on Computer Science and Software Engineering (JCSSE), 1–5. IEEE.
  • Pettersen, J. 2009. “Defining Lean Production: Some Conceptual and Practical Issues.” The TQM Journal 21 (2): 127–142.
  • Pettersen, K. J., R. B. Handfield, and G. L. Ragatz. 2005. “Supplier Integration Into New Product Development: Coordinating Product, Process and Supply Chain Design.” Journal of Operations Management 23 (3-4): 371–388.
  • Phuong, N. A., and T. Guidat. 2018, July. “Sustainable Value Stream Mapping and Technologies of Industry 4.0 in Manufacturing Process Reconfiguration: A Case Study in an Apparel Company.” In 2018 IEEE International Conference on Service Operations and Logistics, and Informatics (SOLI), 85–90. IEEE.
  • Provost, F., and T. Fawcett. 2013. “Data Science and Its Relationship to Big Data and Data-Driven Decision-Making.” Big Data 1 (1): 51–59.
  • Raman, S., N. Patwa, I. Niranjan, U. Ranjan, K. Moorthy, and A. Mehta. 2018. “Impact of Big Data on Supply Chain Management.” International Journal of Logistics Research and Applications 21 (6): 579–596.
  • Rejikumar, G., A. Aswathy Asokan, and V. R. Sreedharan. 2020. “Impact of Data-Driven Decision-Making in Lean Six Sigma: An Empirical Analysis.” Total Quality Management & Business Excellence 31 (3-4): 279–296.
  • Revina, A. 2018. “Assessing Process Suitability for AI-Based Automation. Research Idea and Design.” In International Conference on Business Information Systems, 697–706. Cham: Springer.
  • Ribeiro, M. I. B., A. J. G. Fernandes, and I. M. Lopes. 2020. “Digital Marketing: A Bibliometric Analysis Based on the Scopus Database Scientific Publications.” In Digital Marketing Strategies and Models for Competitive Business, edited by Fulya Acikgoz, Raquel Antunes, Maria Fernanda Augusto, Cardoso Sara, Erkan Ismail, Esteves Maria Micaela Dinis, Gago Pedro, et al., 52–73. Hershey, Pennsylvania: IGI Global.
  • Rosin, F., P. Forget, S. Lamouri, and R. Pellerin. 2020. “Impacts of Industry 4.0 Technologies on Lean Principles.” International Journal of Production Research 58 (6): 1644–1661.
  • Rubab, Saddaf, Syed A Taqvi, and Mohd Fadzil Hassan. 2019. “Realizing the Value of Big Data in Process Monitoring and Control: Current Issues and Opportunities.” In International Conference of Reliable Information and Communication Technology, 128–138. Springer.
  • Sancha, C., F. Wiengarten, A. Longoni, and M. Pagell. 2020. “The Moderating Role of Temporary Work on the Performance of Lean Manufacturing Systems.” International Journal of Production Research 58 (14): 4285–4305.
  • Sarkar, S., N. Ejaz, M. Kumar, and J. Maiti. 2020. “Root Cause Analysis of Incidents Using Text Clustering and Classification Algorithms.” In Proceedings of ICETIT 2019. Lecture Notes in Electrical Engineering. Vol. 605., edited by P. Singh, B. Panigrahi, N. Suryadevara, S. Sharma, and A. Singh, 707–718. Cham: Springer.
  • Saurin, T. A., G. A. Marodin, and J. L. D. Ribeiro. 2011. “A Framework for Assessing the Use of Lean Production Practices in Manufacturing Cells.” International Journal of Production Research 49 (11): 3211–3230.
  • Schäfer, Franziska, Christian Zeiselmair, Jonas Becker, and Heiner Otten. 2018. “Synthesizing CRISP-DM and Quality Management: A Data Mining Approach for Production Processes.” In 2018 IEEE International Conference on Technology Management, Operations and Decisions (ICTMOD), 190–195. IEEE.
  • Schwenzfeier, Nils, and Volker Gruhn. 2018. “Toward a Practical Process Model for Anomaly Detection Systems.” In 2018 IEEE/ACM 1st International Workshop on Software Engineering for Cognitive Services (SE4COG), 41–44. IEEE.
  • Sezen, B., I. S. Karakadilar, and G. Buyukozkan. 2012. “Proposition of a Model for Measuring Adherence to Lean Practices: Applied to Turkish Automotive Part Suppliers.” International Journal of Production Research 50 (14): 3878–3894.
  • Shah, R., A. Chandrasekaran, and K. Linderman. 2008. “In Pursuit of Implementation Patterns: The Context of Lean and Six Sigma.” International Journal of Production Research 46 (23): 6679–6699.
  • Shah, R., and P. T. Ward. 2003. “Lean Manufacturing: Context, Practice Bundles, and Performance.” Journal of Operations Management 21 (2): 129–149.
  • Shah, R., and P. T. Ward. 2007. “Defining and Developing Measures of Lean Production.” Journal of Operations Management 25 (4): 785–805.
  • Shahin, M., F. F. Chen, H. Bouzary, and K. Krishnaiyer. 2020. “Integration of Lean Practices and Industry 4.0 Technologies: Smart Manufacturing for Next-Generation Enterprises.” The International Journal of Advanced Manufacturing Technology 107: 2927–2936.
  • Shamsuzzoha, Ahm, Filipe Ferreira, Americo Azevedo, and Petri Helo. 2017. “Collaborative Smart Process Monitoring Within Virtual Factory Environment: An Implementation Issue.” International Journal of Computer Integrated Manufacturing 30 (1): 167–181.
  • Shao, G., S. J. Shin, and S. Jain. 2014, December. “Data Analytics Using Simulation for Smart Manufacturing.” In Proceedings of the Winter Simulation Conference 2014, 2192–2203. IEEE.
  • Sharma, S. K., R. D. Gupta, A. Kumar, and B. Singh. 2011. “Supplier Issues for Lean Implementation.” International Journal of Engineering Science and Technology 3 (5): 3900–3905.
  • Sivarajah, U., M. M. Kamal, Z. Irani, and V. Weerakkody. 2017. “Critical Analysis of Big Data Challenges and Analytical Methods.” Journal of Business Research 70: 263–286.
  • Souza, G. C. 2014. “Supply Chain Analytics.” Business Horizons 57 (5): 595–605.
  • Stojanovic, L., M. Dinic, N. Stojanovic, and A. Stojadinovic. 2016, December. “Big-Data-Driven Anomaly Detection in Industry (4.0): An Approach and a Case Study.” In 2016 IEEE International Conference on Big Data (Big Data), 1647–1652. IEEE.
  • Stojanovic, N., and D. Milenovic. 2018, December. “Data-Driven Digital Twin Approach for Process optimization: An Industry Use Case.” In 2018 IEEE International Conference on Big Data (Big Data), 4202–4211. IEEE.
  • Strozzi, F., C. Colicchia, A. Creazza, and C. Noè. 2017. “Literature Review on the ‘Smart Factory’ Concept Using Bibliometric Tools.” International Journal of Production Research 55 (22): 6572–6591.
  • Sturm, C., M. Fichtner, and S. Schönig. 2019. “Full Support for Efficiently Mining Multi-Perspective Declarative Constraints from Process Logs.” Information 10 (1): 29.
  • Sundar, R., A. N. Balaji, and R. S. Kumar. 2014. “A Review on Lean Manufacturing Implementation Techniques.” Procedia Engineering 97: 1875–1885.
  • Talia, D., P. Trunfio, and F. Marozzo. 2015. Data Analysis in the Cloud: Models, Techniques and Applications. Amsterdam: Elsevier.
  • Tan, K. H., Y. Zhan, G. Ji, F. Ye, and C. Chang. 2015. “Harvesting Big Data to Enhance Supply Chain Innovation Capabilities: An Analytic Infrastructure Based on Deduction Graph.” International Journal of Production Economics 165: 223–233.
  • Tang, J., and X. Yan. 2017. “Neural Network Modeling Relationship Between Inputs and State Mapping Plane Obtained by FDA–t-SNE for Visual Industrial Process Monitoring.” Applied Soft Computing 60: 577–590.
  • Tezel, A., L. Koskela, P. Tzortzopoulos, C. T. Formoso, and T. Alves. 2015. “Visual Management in Brazilian Construction Companies: Taxonomy and Guidelines for Implementation.” Journal of Management in Engineering 31 (6): 05015001.
  • Tjahjono, B., P. Ball, V. I. Vitanov, C. Scorzafave, J. Nogueira, J. Calleja, M. Minguet, et al. 2010. “Six Sigma: A Literature Review.” International Journal of Lean Six Sigma 1 (3): 216–233.
  • Toasa, R., M. Maximiano, C. Reis, and D. Guevara. 2018, June. “Data Visualization Techniques for Real-Time Information – A Custom and Dynamic Dashboard for Analyzing Surveys’ Results.” In 2018 13th Iberian Conference on Information Systems and Technologies (CISTI), 1–7. IEEE.
  • Tortorella, G. L., and D. Fettermann. 2018. “Implementation of Industry 4.0 and Lean Production in Brazilian Manufacturing Companies.” International Journal of Production Research 56 (8): 2975–2987.
  • Tortorella, Guilherme Luz, Ricardo Giglio, and Desirée H Van Dun. 2019. “Industry 4.0 Adoption as a Moderator of the Impact of Lean Production Practices on Operational Performance Improvement.” International Journal of Operations & Production Management. Emerald Publishing Limited 39 (6/7/8): 860–886.
  • Valamede, L. S., and A. C. S. Akkari. 2020. Lean 4.0: A New Holistic Approach for the Integration of Lean Manufacturing Tools and Digital Technologies.
  • Van der Aalst, W. 2011. Process Mining: Discovery, Conformance and Enhancement of Business Processes. Berlin: Springer-Verlag.
  • van der Aalst, W. M. 2018. “Process Discovery from Event Data: Relating Models and Logs Through Abstractions.” Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery 8 (3): e1244.
  • Van der Aalst, W., and E. Damiani. 2015. “Processes Meet Big Data: Connecting Data Science with Process Science.” IEEE Transactions on Services Computing 8 (6): 810–819.
  • Vicario, Grazia, and Shirley Coleman. 2020. “A Review of Data Science in Business and Industry and a Future View.” Applied Stochastic Models in Business and Industry 36 (1): 6–18.
  • Vitari, C., and E. Raguseo. 2020. “Big Data Analytics Business Value and Firm Performance: Linking with Environmental Context.” International Journal of Production Research 58 (18): 5456–5476.
  • Walha, A., F. Ghozzi, and F. Gargouri. 2019. “From User Generated Content to Social Data Warehouse: Processes, Operations and Data Modelling.” International Journal of Web Engineering and Technology 14 (3): 203–230.
  • Waller, M. A., and S. E. Fawcett. 2013. “Data Science, Predictive Analytics, and big Data: A Revolution That Will Transform Supply Chain Design and Management.” Journal of Business Logistics 34 (2): 77–84.
  • Waltman, L., N. J. van Eck, and E. C. Noyons. 2010. “A Unified Approach to Mapping and Clustering of Bibliometric Networks.” Journal of Informetrics 4 (4): 629–635.
  • Wamba, S. F., S. Akter, A. Edwards, G. Chopin, and D. Gnanzou. 2015. “How ‘Big Data’ can Make Big Impact: Findings from a Systematic Review and a Longitudinal Case Study.” International Journal of Production Economics 165: 234–246.
  • Wang, Z., and H. Zhao. 2016, June. “Empirical Study of Using Big Data for Business Process Improvement at Private Manufacturing Firm in Cloud Computing.” In 2016 IEEE 3rd international conference on cyber security and cloud computing (CSCloud), 129–135. IEEE.
  • Wang, B., J. Y. Zhao, Z. G. Wan, J. H. Ma, H. Li, and J. Ma. 2016. “Lean Intelligent Production System and Value Stream Practice.” Paper Presented at the 3rd International Conference on Economics and Management, ICEM 2016, Jiangsu.
  • Watson, G. H., and C. F. DeYong. 2010. “Design for Six Sigma: Caveat Emptor.” International Journal of Lean Six Sigma 1 (1): 66–84.
  • Womack, J. P., D. T. Jones, and D. Roos. 1990. The Machine That Changed the World. New York: Rawson Associates.
  • Woo, J. S., P. Suslow, R. Thorsen, R. Ma, S. Bakhtary, M. Moayeri, and A. Nambiar. 2019. “Development and Implementation of Real-Time web-Based Dashboards in a Multisite Transfusion Service.” Journal of Pathology Informatics 10 (3): 1–7.
  • Xu, L. D., E. L. Xu, and L. Li. 2018. “Industry 4.0: State of the Art and Future Trends.” International Journal of Production Research 56 (8): 2941–2962.
  • Xu, S., X. Zhang, L. Feng, and W. Yang. 2020. “Disruption Risks in Supply Chain Management: A Literature Review Based on Bibliometric Analysis.” International Journal of Production Research 58 (11): 3508–3526.
  • Yan, S., and X. Yan. 2019. “Using Labeled Autoencoder to Supervise Neural Network Combined with k-Nearest Neighbor for Visual Industrial Process Monitoring.” Industrial & Engineering Chemistry Research 58 (23): 9952–9958.
  • Yang, Hanna, Minjeong Park, Minsu Cho, Minseok Song, and Seongjoo Kim. 2014. “A System Architecture for Manufacturing Process Analysis Based on Big Data and Process Mining Techniques.” In 2014 IEEE International Conference on Big Data (Big Data), 1024–1029. IEEE.
  • Yao, Le, and Zhiqiang Ge. 2018. “Big Data Quality Prediction in the Process Industry: A Distributed Parallel Modeling Framework.” Journal of Process Control 68: 1–13.
  • Zhong, R. Y., C. Xu, C. Chen, and G. Q. Huang. 2017. “Big Data Analytics for Physical Internet-Based Intelligent Manufacturing Shop Floors.” International Journal of Production Research 55 (9): 2610–2621.
  • Zhu, Jinlin, Zhiqiang Ge, Zhihuan Song, and Furong Gao. 2018. “Review and Big Data Perspectives on Robust Data Mining Approaches for Industrial Process Modeling with Outliers and Missing Data.” Annual Reviews in Control 46: 107–133.
  • Zhuang, C., J. Liu, and H. Xiong. 2018. “Digital Twin-Based Smart Production Management and Control Framework for the Complex Product Assembly Shop-Floor.” The International Journal of Advanced Manufacturing Technology 96 (1–4): 1149–1163.
  • Zwetsloot, I. M., A. Kuiper, T. S. Akkerhuis, and H. de Koning. 2018. “Lean Six Sigma Meets Data Science: Integrating two Approaches Based on Three Case Studies.” Quality Engineering 30 (3): 419–431.

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