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Identify product families using cluster analysis: Case study in Passenger Car Radial (PCR) tire product

Research output: Contribution to journalConference articlepeer-review

4 Citations (Scopus)

Abstract

Manufacturing companies, such as tire manufactures are facing great challenges to cope with increased product variety which induced by customer demand. This variety lead to higher internal complexity in term of design and production. Thus, variety has to be well-managed in order to guarantee the positive outcome for company. One of the solution is to have a well-structured product family. In this research, products data are partitioned into clusters by applying cluster analysis for mixed-type data based on their general characteristic and component specification. Variants within cluster have similarities in term of characteristics and main product component used in production. By applying k-prototypes algorithm to handle these mixed type data, the data set is clustered and interpreted into eight different clusters using selected variables.

Original languageEnglish
Article number012057
JournalIOP Conference Series: Materials Science and Engineering
Volume909
Issue number1
DOIs
Publication statusPublished - 21 Dec 2020
Event2020 International Conference on Advanced Mechanical and Industrial Engineering, ICAMIE 2020 - Cilegon City, Banten, Indonesia
Duration: 8 Jul 20208 Jul 2020

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure

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