Skip to main content

Part of the book series: Springer Theses ((Springer Theses))

Abstract

Concluding, the presented product state concept allows to identify relevant state drivers of complex manufacturing systems. The concept is able to utilize complex, diverse and high-dimensional data sets which often occur in manufacturing applications. This fits nicely with current initiatives like ‘Industrie 4.0’, ‘Cyber Physical Systems’ in Europe and the ‘Industrial Internet’ and ‘Advanced Manufacturing Partnership’ in the US as well as the growing area of Big Data research. It can be safely said that in the near future, the amount of data derived from manufacturing operations will increase due to these developments. This offers both opportunities and challenges for manufacturing companies and manufacturing research. With the developed concept, the increasing data streams can be analyzed efficiently and applicable results can be derived. The analysis results present a direct benefit in form of the most important process parameters and state characteristics, the state drivers, of the manufacturing system. These can be directly utilized in, e.g., quality monitoring and advanced process control.

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 84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 109.99
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

  • Guyon, I., Weston, J., Barnhill, S., & Vapnik, V. (2002). A gene selection method for cancer classification using support vector machines. Machine Learning, 46, 389–422. doi:10.1155/2012/586246.

    Article  MATH  Google Scholar 

  • Wuest, T., Hribernik, K., & Thoben, K. (2012). Can a product have a facebook? A new perspective on product avatars in product lifecycle management. In L. Rivest, A. Bouraz, & B. Louhichi (Eds.), Product Lifecycle Management: Towards Knowledge-Rich Enterprises. Proceedings of the 9th International Conference on Product Lifecycle Management. Montréal, Canada.

    Google Scholar 

  • Wuest, T., Hribernik, K., & Thoben, K. (2013). Digital representations of intelligent products: Product avatar 2.0. In M. Abramovici & R. Stark, M. Abramovici & R. Stark (Eds.), Smart Product Engineering, LNPE (pp. 675–684). Berlin, Heidelberg: Springer. doi:10.1007/978-3-642-30817-8.

  • Wuest, T., Hribernik, K. & Thoben, K.-D. (2014). Accessing servitization potential of PLM data by applying the product avatar concept. Production Planning and Control (accepted).

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Thorsten Wuest .

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer International Publishing Switzerland

About this chapter

Cite this chapter

Wuest, T. (2015). Recapitulation. In: Identifying Product and Process State Drivers in Manufacturing Systems Using Supervised Machine Learning. Springer Theses. Springer, Cham. https://doi.org/10.1007/978-3-319-17611-6_8

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-17611-6_8

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-17610-9

  • Online ISBN: 978-3-319-17611-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics