Predicting the development time of platform for multiple-generation product using artificial neural network

Amalia Suzianti, Nauli Dwi Fileinti, Nabila Priscandy Poetri

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The rapid growth of technology in the automotive industry has forced the manufacturers to continuously develop new technology and innovate. Nowadays, innovation in the automotive industry does not only refer to product innovation, but also refers to process innovation as well, namely by implementing the product platform strategy. This research aims to predict the development time of new platform for automotive product as one of the multiple-generation product line, using artificial neural network. Artificial neural network was used in this study simply because it adopts the human brain's ability to give stimuli, process it, and give output. Thus, its capability to map the pattern of input into a new pattern of output and predict possible patterns. This research was focused on the platform innovation of Toyota Kijang. The prediction from this research shows that Toyota Kijang new platform should be introduced in 32-33 quarters. This result appears to be corresponding with the ideal condition of platform innovation which is in 8-10 years. Moreover, the result shows that most of the time, company decides to introduce the nextgeneration platform when the older generation is still in the maturity stage of its life cycle. The research also successfully identifies the factors influencing company to introduce the next-generation platform.

Original languageEnglish
Title of host publication6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
PublisherIEOM Society
Number of pages1
ISBN (Print)9780985549749
Publication statusPublished - 1 Jan 2016
Event6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016 - Kuala Lumpur, Malaysia
Duration: 8 Mar 201610 Mar 2016

Publication series

NameProceedings of the International Conference on Industrial Engineering and Operations Management
Volume8-10 March 2016
ISSN (Electronic)2169-8767

Conference

Conference6th International Conference on Industrial Engineering and Operations Management in Kuala Lumpur, IEOM 2016
Country/TerritoryMalaysia
CityKuala Lumpur
Period8/03/1610/03/16

Keywords

  • Artificial neural network
  • Automotive
  • Innovation
  • Multiple-generation product
  • Product platform

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