Data-Driven Product Family Modeling with Feedback

Thomas Ditlev Brunoe () and Kjeld Nielsen ()
Additional contact information
Thomas Ditlev Brunoe: Department of Materials and Production, Aalborg University
Kjeld Nielsen: Department of Materials and Production, Aalborg University

A chapter in Customization 4.0, 2018, pp 469-478 from Springer

Abstract: Abstract In order to become a successful mass customizer, companies must be in control of their product variety. This is to ensure that the product variety is sufficient in order to satisfy the range of customer demands but also to ensure that there is no excess variety, which compromises efficiency in business processes and manufacturing processes. This is often addressed by establishing product family models which represent the variety in a specific product family and any constraints there may be. In this paper, we first present a literature review of the currently existing product family modeling methods, in which it is concluded that most current methods are stand-alone, document-based methods, which largely do not consider integration with other product data systems or feedback from production and products. We then propose a number of new approaches to product family modeling, which utilizes data from other systems such as ERP and PDM, which enables a more fact-based modeling process. Furthermore, the proposed approach enables feedback loops into the product family model, which is possible due to advances in connectivity (IOT applications). The new approach will enable better qualification of decisions regarding product variety management once implemented.

Keywords: Mass customization; Product modeling; Product family modeling; Solution space development; Product variety (search for similar items in EconPapers)
Date: 2018
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-319-77556-2_29

Ordering information: This item can be ordered from
http://www.springer.com/9783319775562

DOI: 10.1007/978-3-319-77556-2_29

Access Statistics for this chapter

More chapters in Springer Proceedings in Business and Economics from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().