Skip to main content

Advances in Robotics in the Era of Industry 4.0

  • Chapter
  • First Online:
Industry 4.0: Managing The Digital Transformation

Part of the book series: Springer Series in Advanced Manufacturing ((SSAM))

Abstract

The industrial robots in factories have been recently designed and utilized to handle dangerous tasks for humans, to achieve faster and more accurate production processes, and to reduce the cost of the products. Since the competitiveness in today’s business environment increases, manufacturers require more intelligent systems making smarter decisions. In the light of Industry 4.0 revolution, the advances in information technology like artificial intelligence , cloud and Big Data change the use and design of robots in the industry. The potential industrial robotic applications and the next generation of robotics planned to be utilized in the Industry 4.0 factories are discussed.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 199.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  • Adamson G, Wanga L, Moore P (2017) Feature-based control and information framework for adaptive and distributed manufacturing in cyber physical systems. J Manufact Syst 43:305–315

    Article  Google Scholar 

  • Al-Jaroodi J, Mohamed N, Jawhar I, Sanja LM (2016) Software engineering issues for cyber-physical systems. In IEEE international conference on smart computing (SMARTCOMP), pp 17–23

    Google Scholar 

  • Augustsson S, Olsson J, Christiernin LG, Bolmsjö G (2014) How to transfer information between collaborating human operators and industrial robots in an assembly. NordiCHI 2014:286–294

    Google Scholar 

  • Bahrin MAK, Othman MF, Azli NHN, Talib MF (2016) Industry 40: a review on industrial automation and robotic. Jurnal Teknologi 137–143

    Google Scholar 

  • Berger U, Le D, Zou W, Lehmann C, Stdter J, Ampatzopoulos A (2015) Development of a mobile robot system for assembly task on continuous conveyor. In International conference on innovative technologies, pp 331–334

    Google Scholar 

  • Bicchi A, Peshkin MA, Colgate JE (2008) Safety for physical human robot interaction. In: Springer Handbook of Robotics Heidelberg, Germany, Springer, pp 1335–1348

    Google Scholar 

  • Bolmsjö G (2015) Supporting tools for operator in robot collaborative mode. In 6th international conference on applied human factors and ergonomics (AHFE 2015) and the affiliated conferences, AHFE 2015, pp 409–416

    Google Scholar 

  • Bolmsjö G, Bennulf M, Zhang X (2016) Safety system for industrial robots to support collaboration. Adv Ergonom Manufact: Manag Enter Fut 490:253–265

    Google Scholar 

  • BöckenkampFrank A, Stenzel W, Lünsch D (2016) Towards autonomously navigating and cooperating vehicles in cyber-physical production systems. In Machine learning for cyber physical systems, pp 111–121

    Google Scholar 

  • Brizzi P, Conzon D, Khaleel H, Tomasi R, Pramudianto F, Knechtel M, Cultrona P (2013) Bringing the internet of things along the manufacturing line: a case study in controlling industrial robot and monitoring energy consumption remotely. In Emerging technologies & factory automation (ETFA) pp 1–8

    Google Scholar 

  • Cherubini A, Passama R, Meline A, Crosnier A, Fraisse P, (2013) Multimodal control for human-robot cooperation. In 2013 IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 2202–2207

    Google Scholar 

  • Clint H, (2010) Human-robot interaction and future industrial robotics applications. In IEEE/RSJ international conference on intelligent robots and systems, pp 4749–4754

    Google Scholar 

  • Coninck ED, Bohez S, Leroux S, Verbelen T, Vankeirsbilck B, Dhoedt B, Simoens P, (2016) Middleware platform for distributed applications incorporating robots. In Sensors and the cloud, 5th IEEE international conference on cloud networking

    Google Scholar 

  • Corrales JA, García Gómez GJ, Torres F, Perdereau V (2012) Cooperative tasks between humans and robots in industrial environments. Int J Adv Rob Syst 9(94):1–10

    Google Scholar 

  • Erol S, Schumacher A, Sihn W (2016) Strategic guidance towards industry 40—a three-stage process model. In International conference on competitive manufacturing (COMA 2016), pp 495–500

    Google Scholar 

  • Huang S, Bergström N, Yamakawa Y, Senoo T, Ishikawa M (2016) Applying high-speed vision sensing to an industrial robot for high-performance position regulation under uncertainties. Sensors 16(8):1195

    Article  Google Scholar 

  • Jaber AA, Bicker R (2016) Fault diagnosis of industrial robot bearings based on discrete wavelet transform and artificial neural network. In-Non-Dest Test Cond Monit 7:179–186

    Google Scholar 

  • Kehoe B, Patil S, Abbeel P, Goldberg K (2015) A survey of research on cloud robotics and automation. IEEE Trans Autom Sci Eng 12(2):398–409

    Article  Google Scholar 

  • Khalid A, Kirisci P, Ghrairi Z, Pannek J, Thoben KD (2016) Safety requirements in collaborative human robot cyber physical system. In 5th international conference on dynamics in logistics (LDIC 2016), pp 39–48

    Google Scholar 

  • Khalid A, Kirisci P, Ghrairi Z, Thoben KD, Pannek J (2016) A methodology to develop collaborative robotic cyber physical systems for production environments. Log Res 9. doi: 10.1007/s12159-016-0151-x

  • Kolberg D, Zhlke D (2015) Lean automation enabled by industry 40 technologies. IFAC-PapersOnLine 48(3):1870–1875

    Article  Google Scholar 

  • Kwon D, Hodkiewicz MR, Fan J, Shibutani T, Pecht MG (2016) IoT-based prognostics and systems health management for industrial applications. IEEE Access 4:3659–3670

    Article  Google Scholar 

  • Lee J, Bagheri B, Kao HA (2015) A cyber-physical systems architecture for industry 40-based manufacturing systems. Manuf Lett 3:18–23

    Article  Google Scholar 

  • Lee J, Kao HA, Yang S (2014a) Service innovation and smart analytics for industry 4.0 and big data environment. Procedia CIRP 16:3–8

    Article  Google Scholar 

  • Lee J, Bagheri B, Kao HA (2014) Recent advances and trends of cyber-physical systems and big data analytics in industrial informatics. In Proceedings of International Conference on Industrial Informatics (INDIN), pp 217–229

    Google Scholar 

  • Lee J, Lapira E, Bagheri B, Kao HA (2013) Recent advances and trends in predictive manufacturing systems in big data environment. Manuf Lett 2013:38–41

    Article  Google Scholar 

  • Lenz C, Nair S, Rickert M, Knoll A, Gast J, Bannat A, Wallhoff F, (2008) Joint-action for humans and industrial robots for assembly tasks. In Proceedings of the 17th IEEE international symposium on robot and human interactive communication, pp 130–135

    Google Scholar 

  • Liu Q, Wan J, Zhou K (2014) Cloud manufacturing service system for industrial-cluster-oriented application. J Int Technol 28(1):373–380

    Google Scholar 

  • Maiolino P, Woolley R, Branson D, Benardos P, Popov A, Ratchev S (2017) Flexible robot sealant dispensing cell using RGB-D sensor and off-line programming. Robot Comput Int Manuf 48:188–195

    Article  Google Scholar 

  • Murar M, Brad S (2015) Monitoring and control of dual-arm industrial robot tasks using IoT application and services. Appl Mech Mater 762:255–260

    Article  Google Scholar 

  • Pedersen MR, Nalpantidis L, Andersen RS, Schou C, Bøgh S, Krüger V, Madsen O (2016) Robot skills for manufacturing: from concept to industrial deployment. Robot Comput-Int Manuf 37:282–291

    Article  Google Scholar 

  • Pérez L, Rodríguez Í, Rodríguez N, Usamentiaga R, García DF (2016) Robot guidance using machine vision techniques in industrial environments: a comparative review. Sensors 16(3):335

    Article  Google Scholar 

  • Pfeiffer S (2016) Robots, industry 40 and humans, or why assembly work is more than routine work. Societies 6(2):16

    Article  Google Scholar 

  • Ray PP (2017) Internet of Robotic Things: Concept, Technologies, and Challenges. IEEE Access 4:9489–9500

    Google Scholar 

  • Rozo LD, Calinon S, Caldwell D, Jimenez P, Torras C (2013) Learning collaborative impedance-based robot behaviors. In Proceedings of the twenty-seventh AAAI conference on artificial intelligence, pp 1422–1428

    Google Scholar 

  • Vagaš M, Semjon J, Baláž V, Varga J (2014) Methodology for the vibration measurement and evaluation on the industrial robot KUKA. In Proceedings of the RAAD 2014 23rd international conference on robotics in Alpe-Adria-Danube region

    Google Scholar 

  • Vichare NM, Pecht MG (2008) Prognostics and health management of electronics. Wiley, Hoboken

    Google Scholar 

  • Vick A, Vonasek V, Robert P, Kruger J (2015) Robot control as a service—towards cloud-based motion planning and control for industrial robots. In Proceedings of 10th ieee international workshop on robot motion and control (RoMoCo), pp 33–39

    Google Scholar 

  • Wagner M, Hess P, Reitelshoefer S, Franke J (2016) 3D scanning of workpieces with cooperative industrial robot arms. In Proceedings of ISR 2016: 47th international symposium on robotics

    Google Scholar 

  • Wan J, Yi M, Li D (2016) Mobile services for customization manufacturing systems: an example of industry 40. IEEE Access 4:8977–8986

    Article  Google Scholar 

  • Wang L, Gao R, Ragai I (2014) An integrated cyber-physical system for cloud manufacturing. In Proceedings of the ASME 2014 international manufacturing science and engineering conference, vol 1. pp 135–144

    Google Scholar 

  • Wang L, Törngren M, Onori M (2015) Current status and advancement of cyber-physical systems in manufacturing. J Manuf Syst 37(2):517–527

    Google Scholar 

  • Wang S, Wan J, Li D, Zhang C (2015b) Implementing smart factory of industrie 40: An outlook. Int J Distrib Sens Netw 2016:7–17

    Google Scholar 

  • Wang S, Wan J, Zhang D, Li D, Zhang C (2016) Towards smart factory for industry 40: A self-organized multi-agent system with big data based feedback and coordination. Comput Net 101:158–168

    Article  Google Scholar 

  • Wang XV, Wang L, Mohammed A, Givehchi M (2017) Ubiquitous manufacturing system based on cloud: a robotics application. Robot Comput-Int Manuf 45:116–125

    Article  Google Scholar 

  • Xu X (2012) From cloud computing to cloud manufacturing. Robot Comput-Int Manuf 28(1):75–86

    Article  Google Scholar 

  • Zhang Y, Qian C, Lv J, Liu Y (2017) Agent and cyber-physical system based self-organizing and self-adaptive intelligent shopfloor. IEEE Trans Indust Inf 13(2):737–744

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Barış Bayram .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Bayram, B., İnce, G. (2018). Advances in Robotics in the Era of Industry 4.0. In: Industry 4.0: Managing The Digital Transformation. Springer Series in Advanced Manufacturing. Springer, Cham. https://doi.org/10.1007/978-3-319-57870-5_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-57870-5_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-57869-9

  • Online ISBN: 978-3-319-57870-5

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics