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Digital Supply Chain, Smart Operations and Industry 4.0

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Global Supply Chain and Operations Management

Part of the book series: Springer Texts in Business and Economics ((STBE))

Abstract

The supply chain is as good as the digital technology behind it. This chapter is devoted to the digitalization of supply chain and operations management (SCOM). The chapter starts with the concept of SCOM excellence and continues with fundamental definitions of digital supply chains and operations. Subsequently, digital technology classifications of SCOM are presented in terms of the SCOR model. Decision-making support improvements in the digital SCOM framework are discussed from qualitative and quantitative perspectives.

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Bibliography

  • Abele E, Meyer T, Näher U, Strube G, Sykes R (2008) Global production – a handbook for strategy and implementation. Springer, Berlin

    Google Scholar 

  • Addo-Tenkorang R, Helo PT (2016) Big data applications in operations/supply-chain management: a literature review. Comput Ind Eng 101:528–543

    Article  Google Scholar 

  • Alicke A, Rachor J, Seyfert A (2016) Supply Chain 4.0 – the next-generation digital supply chain, McKinsey & Company, Supply Chain Management, June 2016

    Google Scholar 

  • Asche S (2017) ThyssenKrupp druckt Metall und Kunststoff. VDI-Nachrichten 8:16

    Google Scholar 

  • Asche S Metalle drucken ohne Laser. VDI-Nachrichten 2018, 26:12–13

    Google Scholar 

  • Ballé M, Jones D, Chaize J, Fiume O (2017) The lean strategy – using lean to create competitive advantage, unleash innovation, and deliver sustainable growth. McGraw-Hill, New York

    Google Scholar 

  • Bauerhansel T, ten Hompel M, Vogel-Heuser B (2014) Industrie 4.0 in produktion, automatisierung und logistik. Springer Vieweg, Wiesbaden

    Book  Google Scholar 

  • Bearzotti LA, Salomone E, Chiotti OJ (2012) An autonomous multi-agent approach to supply chain event management. Int J Prod Econ 135(1):468–478

    Article  Google Scholar 

  • Ben-Daya M, Hassini E, Bahroun Z (2018) Internet of things and supply chain management: a literature review. Int J Prod Res. https://doi.org/10.1080/00207543.2017.1402140

  • BMBF (2013) Recommendations for implementing the strategic initiative INDUSTRIE 4.0 – final report of the Industrie 4.0 Working Group BMBF

    Google Scholar 

  • BMWi Bundesministerium für Wirtschaft und Energie (2016) Digitale Strategie 2025, Status March 2016

    Google Scholar 

  • Bozarth CC, Handfield RB (2013) Introduction to operations and supply chain management. Perason, Harlow

    Google Scholar 

  • Breunig M, Kelly R, Mathis R, Wee D (2016) Getting the most out of Industry 4.0. McKinsey & Company, Article April 2016

    Google Scholar 

  • Brynjolfsson E, McAfee A (2017) Von Managern und Maschinen. Harvard Business Manager, November 2017

    Google Scholar 

  • Brynjolfsson E, McAffe A (2015) The second machine age – Wie die nächste digitale Revolution unser aller Leben verändern wird. Plassen Verlag, Kulmbach

    Google Scholar 

  • Buer SV, Strandhagen JO, Chan FTS (2018) The link between Industry 4.0 and lean manufacturing: mapping current research and establishing a research agenda. Int J Prod Res. https://doi.org/10.1080/00207543.2018.1442945

    Article  Google Scholar 

  • Cheung WC, Simchi-Levi D, Wang H (2016) Dynamic pricing and demand learning with limited price experimentation. Oper Res. https://doi.org/10.1287/opre.2017.1629

    Article  Google Scholar 

  • Choi TM, Wallace SW, Wang Y (2018) Big data analytics in operations management. Prod Oper Manag. https://doi.org/10.1111/poms.12838

  • Chopra S, Meindl P (2013) Supply chain management – strategy, planning and operation. Pearson, Harlow

    Google Scholar 

  • Christopher M (2005) Logistics and supply chain management: creating value-adding networks. Financial Times. Prentice Hall, Dorchester

    Google Scholar 

  • D’Aveni R (2015) The 3-D printing revolution. Harvard Business Review, May 2015

    Google Scholar 

  • Decken T (2018) Warum Digitalisierung nicht mehr warten kann. The Source Magazine, 3rd edn, January 2018

    Google Scholar 

  • Deutsche Telekom AG (2013) Use case – the cow that texts the farmer. Deutsche Telekom Publications

    Google Scholar 

  • Deutsche Telekom AG (2015) Telemaintenance – remote delivery of first aid, Deutsche Telekom Publications

    Google Scholar 

  • Dolgui A, Ivanov D, Sokolov B (2018) Ripple effect in the supply chain: an analysis and recent literature. Int J Prod Res 56(1–2). https://doi.org/10.1080/00207543.2017.1387680

    Article  Google Scholar 

  • Duggan KJ (2012) Design for operational excellence – a breakthrough strategy for business growth. McGraw Hill, New York

    Google Scholar 

  • Erol S, Jäger A, Hold P, Ott K, Sihn W (2016) Tangible industry 4.0: a scenario-based approach to learning for the future of production. Proc CIRP 54:13–18

    Article  Google Scholar 

  • Fazili M, Venkatadri U, Cyrus P, Tajbakhsh M (2017) Physical Internet, conventional and hybrid logistic systems: a routing optimisation-based comparison using the Eastern Canada road network case study. Int J Prod Res 55(9):2703–2730

    Article  Google Scholar 

  • Feldmann K, Pumpe A (2017) A holistic decision framework for 3D printing investments in global supply chains. Trans Res Proc 25:677–694

    Google Scholar 

  • Feldmann R, Hammer M, Van Niel J, Somers K (2017) Find buried treasure with advanced analytics. McKinsey & Company

    Google Scholar 

  • Fritz H, Schulze G (1990) Fertigungstechnik. VDI Verlag Düsseldorf

    Google Scholar 

  • Gunasekaran A, Tiwari MK, Dubey R, Wamba SF (2016) Big data and predictive analytics applications in supply chain management. Comput Ind Eng 101:525–527

    Article  Google Scholar 

  • Gunasekaran A, Papadopoulos T, Dubey R, Wamba SF, Childe SJ, Hazen B, Akter S (2017) Big data and predictive analytics for supply chain and organizational performance. J Bus Res 70:308–317

    Article  Google Scholar 

  • Gunasekaran A, Yusuf YY, Adeleye EO, Papadopoulos T (2018) Agile manufacturing practices: the role of big data and business analytics with multiple case studies. Int J Prod Res. https://doi.org/10.1080/00207543.2017.1395488

    Article  Google Scholar 

  • Gupta AK, Arora SK (2013) Industrial automation and robotics, 2nd edn. University Science Press, New Delhi

    Google Scholar 

  • Hentrich C, Pachmajer M (2016) d.quarks – Der Weg zum digitalen Unternehmen. Pricewaterhouse Coopers Aktiengesellschaft, Frankfurt am Main

    Google Scholar 

  • Hofmann E, Rüsch M (2017) Industry 4.0 and the current status as well as future prospects on logistics. Comput Ind 89:23–34

    Article  Google Scholar 

  • Hofmann E, Strewe UM, Bosia N (2018) Supply chain finance and blockchain technology. Springer, Cham

    Book  Google Scholar 

  • Holmström J, Gutowski T (2017) Additive manufacturing in operations and supply chain management: no sustainability benefit or virtuous knock-on opportunities? J Ind Ecol 21(S1):S21–S24

    Article  Google Scholar 

  • Hossenfelder J (2010) Themendossier operational excellence – Nur das Beste ist gut genug. Lünendonk GmbH Publication in cooperation with Kienbaum Consultants

    Google Scholar 

  • Hozak K, Collier DA (2008) RFID as an enabler of improved manufacturing performance. Decis Sci 39:859–881

    Article  Google Scholar 

  • Ivanov D (2018) Structural dynamics and resilience in supply chain risk management. Springer, New York

    Book  Google Scholar 

  • Ivanov D, Sokolov B, Dolgui A, Werner F, Ivanova M (2016) A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory Industry 4.0. Int J Prod Res 54(2):386–402

    Article  Google Scholar 

  • Ivanov D, Dolgui A, Sokolov B (2018) The impact of digital technology and Industry 4.0 on the ripple effect and supply chain risk analytics. Int J Prod Res. https://doi.org/10.1080/00207543.2018.1488086

  • Johnson K, Lee ABH, Simchi-Levi D (2016) Analytics for an online retailer: demand forecasting and price optimization. Manuf Serv Oper Manag 18(1):69–85

    Article  Google Scholar 

  • Khajavi SH, Partanen J, Holmström J (2014) Additive manufacturing in the spare parts supply chain. Comput Ind 65(1):50–63

    Article  Google Scholar 

  • Kiehne B, Tsipoulanidis A (2016) Berufskompetenzen entwickeln durch Perspektivübernahme im Supply Chain und Operations Management. DUZ medienhaus

    Google Scholar 

  • Kinra A, Mukkamala RR, Vatrapu R (2017) Methodological demonstration of a text analytics approach to country logistics system assessments. In: Dynamics in logistics: proceedings of the 5th international conference LDIC, 2016. Bremen, Germany. Freitag M, Kotzab H; Pannek J (eds) Springer The 5th international conference on dynamics in logistics. LDIC 2016, Cham, pp 119–129

    Google Scholar 

  • Klünder T, Reder L, Steven M (2016) Assessing the industry 4.0-readiness of supply chain networks. 16th production research symposium, Istanbul, pp 790–800

    Google Scholar 

  • Koether R, Rau W (2012) Fertigungstechnik für Wirtschaftsingenieure. Carl Hanser Verlag, München

    Google Scholar 

  • Küpper D, Kuhlmann K, Kocher S, Dauner T, Burggräf P (2016) The factory of the future. https://www.bcg.com/publications/2016/leaning-manufacturing-operations-factory-of-future.aspx. Accessed 29 Oct 2017

  • Li J, Jia G, Cheng Y, Hu Y (2017) Additive manufacturing technology in spare parts supply chain: a comparative study. Int J Prod Res 55(5):1498–1515

    Article  Google Scholar 

  • Liao Y, Deschamps Y, de Freitas E, Loures R, Ramos LFP (2017) Past, present and future of Industry 4.0 – a systematic literature review and research agenda proposal. Int J Prod Res 55(12):3609–3629

    Article  Google Scholar 

  • Martin JW (2008) Operational excellence – using Lean Six Sigma to translate customer value through global supply chains. Auerbach Publications, New York

    Google Scholar 

  • Meyer GG, Buijs P, Szirbik NB, Wortmann JC(H) (2014) Intelligent products for enhancing the utilization of tracking technology in transportation. Int J Oper Prod Manag 34(4):422–446

    Article  Google Scholar 

  • Miller A (2014) Redefining operational excellence – new strategies for maximizing performance and profits across the organization. AMACOM American Management Association, New York

    Google Scholar 

  • Moghaddam M, Nof SY (2017) Collaborative service-component integration in cloud manufacturing. Int J Prod Res 56(1–2):677–691

    Google Scholar 

  • Mönch L, Fowler JW, Mason S (2012) Production planning and control for semiconductor wafer fabrication facilities: modeling, analysis, and systems. Springer, New York

    Google Scholar 

  • Müller B, Töppel T (2014) Technologiescreening Laserstrahlschmelzen und Rapid Prototyping – 3D Printing Studie, Fraunhofer-Institut für Werkzeugmaschinen und Umformtechnink IWU

    Google Scholar 

  • Nayak A, Levalle RR, Lee S, Nof SY (2016) Resource sharing in cyber-physical systems: modelling framework and case studies. Int J Prod Res 54(23):6969–6983

    Article  Google Scholar 

  • Nguyen T, Zhou L, Spiegler V, Ieromonachou P, Lin Y (2017) Big data analytics in supply chain management: a state-of-the-art literature review. Comput Oper Res

    Google Scholar 

  • Niesen C, Houy P, Fettke R, Loos P (2016) Towards an integrative big data analysis framework for data-driven risk management in industry 4.0. 49th Hawaii international conference on system sciences (HICSS), pp 5065–5074

    Google Scholar 

  • o. V. (2017) Roboterabsatz legt deutlich zu, VDI-Nachrichten Nr. 40, p. 3

    Google Scholar 

  • Oesterreich TD, Teuteberg F (2016) Understanding the implications of digitisation and automation in the context of Industry 4.0: a triangulation approach and elements of a research agenda for the construction industry. Comput Ind 83:121–139

    Article  Google Scholar 

  • Papadopoulos T, Gunasekaran A, Dubey R, Altay N, Childe SJ, Wamba SF (2017) The role of Big Data in explaining disaster resilience in supply chains for sustainability. J Clean Prod 142(2:1108–1118

    Article  Google Scholar 

  • Porter ME, Heppelmann JE (2014) How smart, connected products are transforming competition. Harv Bus Rev 92(11):64–88

    Google Scholar 

  • Porter ME, Heppelmann JE (2015) How smart, connected products are transforming companies. Harv Bus Rev 93(10):96–114

    Google Scholar 

  • Porter ME, Heppelmann JE (2018) Eine Brücke zwischen digitaler und physischer Welt. Harvard Business Manager, Februar 2018

    Google Scholar 

  • Richey RG, Morgan TR, Lindsey-Hall K, Adams FG (2016) A global exploration of big data in the supply chain. Int J Phys Distrib Logist Manag 46(8):710–739

    Article  Google Scholar 

  • Scheel O, Monahan S, Eitelwein O, Koelbli M (2015) Digital lean – the next stage in operations optimization. A.T. Kearney Publication

    Google Scholar 

  • Schlüter F, Hetterscheid E, Henke M (2017) A simulation-based evaluation approach for digitalization scenarios in smart supply chain risk management. J Ind Eng Manag Sci 1:179–206

    Google Scholar 

  • Schmitt R, Pfeifer T (2010) Qualitätsmanagement: Strategien – Methoden – Techniken. Carl Hanser Verlag, München

    Book  Google Scholar 

  • Schneider M (2017) Lean trifft auf “Industrie 4.0”, Logistik für Unternehmen, 07/08-2017, pp. 36–38, Springer VDI Verlag

    Google Scholar 

  • Schrauf S, Berttram F (2016) Industry 4.0: how digitization makes the supply chain more efficient, agile, and customer-focused. https://www.strategyand.pwc.com/reports/industry4.0. Accessed 29 Oct 2017

  • Schröder MI, Kersten W (2014) Industry 4.0 and its impact on supply chain risk management. Proceedings of the conference reliability and statistics in transport and communication (RelStat), pp 15–18

    Google Scholar 

  • Shafiq SI, Sanin C, Szczerbicki E, Toro C (2015) Virtual engineering object/virtual engineering process: a specialized form of cyber physical system for industrie 4.0. Procedia Comput Sci 60:1146–1155

    Article  Google Scholar 

  • Simchi-Levi D, Schmidt W, Wei Y (2014) From superstorms to factory fires: managing unpredictable supply-chain disruptions. Harv Bus Rev (January–February)

    Google Scholar 

  • Simchi-Levi D, Wu MX (2018) Powering retailers’ digitization through analytics and automation. Int J Prod Res 56(1–2):809–816

    Article  Google Scholar 

  • Statista (2017) https://www.statista.com/topics/1476/industrial-robots/. Accessed 7th Feb 2017 and 12th Jan 2018

  • Strozzi F, Colicchia C, Creazza A, Noè C (2017) Literature review on the ‘Smart Factory’ concept using bibliometric tools. Int J Prod Res. https://doi.org/10.1080/00207543.2017.1326643

    Article  Google Scholar 

  • Sun YI (2017) Die nächste Werkbank der Welt. Harvard Business Manager, December 2017

    Google Scholar 

  • Theorin A, Bengtsson K, Provost J, Lieder M, Johnsson C, Lundholm T, Lennartson B (2017) An event-driven manufacturing information system architecture for Industry 4.0. Int J Prod Res 55(5):1297–1311

    Article  Google Scholar 

  • Tran-Dang H, Krommenacker N, Charpentier P (2017) Containers monitoring through the Physical Internet: a spatial 3D model based on wireless sensor networks. Int J Prod Res 55(9):2650–2663

    Article  Google Scholar 

  • Tsipoulanidis A (2015) Von lean thinking zu supply chain & operational excellence durch die digitale transformation. Der Tagesspiegel, 2.11.2015

    Google Scholar 

  • Tsipoulanidis A (2017a) Leandustry 4.0 – the efficient way from company to customer at times of the digital transformation – how lean thinking is leading to smart supply chain management and operational excellence. ICCMI conference 2017, Thessaloniki, Greece

    Google Scholar 

  • Tsipoulanidis A (2017b) With lean thinking and industry 4.0 to operational excellence. Supply Chain Manag 3:13–19

    Google Scholar 

  • VDI Verein Deutscher Ingenieure e.V. (2013) Cyber-physical systems: Chancen und Nutzen aus Sicht der Automation. Thesen und Handlungsfelder, April 2013

    Google Scholar 

  • Wamba SF, Akter S, Edwards A, Chopin G, Gnanzou D (2015) How ‘big data’ can make big impact: findings from a systematic review and a longitudinal case study, Int J Prod Econ, Elsevier, 165, 234–246.

    Google Scholar 

  • Wamba SF, Ngai EWT, Riggins F, Akter S (2017) Transforming operations and production management using big data and business analytics: future research directions. Int J Oper Prod Manag 37(1):2–9

    Article  Google Scholar 

  • Wang G, Gunasekaran A, Ngai EWT, Papadopoulos T (2016) Big data analytics in logistics and supply chain management: Certain investigations for research and applications. Int J Prod Econ 176:98–110

    Article  Google Scholar 

  • Wannenwetsch HH, Nicolai S (2004) E-Supply-Chain-Management Grundlagen, Strategien, Praxisanwendungen, Gabler Wiesbaden

    Google Scholar 

  • Westerman G, Bonnet D, McAfee A (2014) Leading digital – turning technology into business transformation. Harvard Business Review Press, New York, NY

    Google Scholar 

  • Wildemann H (2016) Die Digitale Chance. Harvard Business Manager, November 2016, pp 87–92

    Google Scholar 

  • Yang Y, Pan S, Ballot E (2017) Innovative vendor-managed inventory strategy exploiting interconnected logistics services in the Physical Internet. Int J Prod Res 55(9):2685–2702

    Article  Google Scholar 

  • Zhong RY, Xu C, Chen C, Huang GQ (2017) Big data analytics for physical internet-based intelligent manufacturing shop floors. Int J Prod Res 55(9):2610–2621

    Article  Google Scholar 

  • Zhuge H (2011) Semantic linking through spaces for cyber-physical-socio intelligence: a methodology. Artif Intell 175(5–6):988–1019

    Article  Google Scholar 

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Acknowledgement

The case-study “Smart usage of Big Data along the Supply Chain” is written by Mr. Arvid Holzwarth (MBA) based on the materials of SupplyOn.

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Authors and Affiliations

  1. Department of Business Administration, Berlin School of Economics and Law, Berlin, Germany

    Dmitry Ivanov & Alexander Tsipoulanidis

  2. Faculty of Transportation and Traffic Science “Friedrich List”, Technical University of Dresden, Dresden, Germany

    Jörn Schönberger

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  1. Dmitry Ivanov
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  2. Alexander Tsipoulanidis
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  3. Jörn Schönberger
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Ivanov, D., Tsipoulanidis, A., Schönberger, J. (2019). Digital Supply Chain, Smart Operations and Industry 4.0. In: Global Supply Chain and Operations Management. Springer Texts in Business and Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-94313-8_16

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