Intelligent planning process with adaptive quick response system for low volume manufacturing

Author:

Dcoutho John1,Rahman Akhlaqur,Eisenbart Boris,Kulkarni Ambarish

Affiliation:

1. Swinburne University of Technology - Hawthorn Campus: Swinburne University of Technology

Abstract

Abstract The automotive manufacturing industry in recent years has seen a paradigm shift in production. Increased customer individualization demands and shorter product life cycles have become the norm in the market. Traditionally, production planning methods in this sector are based on high volumes; thus, production lines used to be relatively rigid. With the current demand for individualized low-volume production, the line must be altered frequently, leading to increased downtime and additional cost. This shift in automotive manufacturing requires production planning to cater to faster, cost-effective adoption to changing low-volume individualized demands. This research discusses a novel Intelligent Planning Process (IPP) to address low-volume individualized manufacturing. The IPP model harnesses transformative technologies such as extended reality (xR) to facilitate faster and more adaptive planning. Further, artificial intelligence is embedded through xR models using various response nodes (e.g., quick response) This provides a critical advantage in developing and evaluating multiple production layouts with considerably reduced efforts. A case studyon positioning preloaded planning data to the real world with quickresponse nodes resulted in one-fourth of the time required by manualinteractive positioning of physical assets. In addition, real-timecontrol and synchronous optimization were other intangible outcomes.

Publisher

Research Square Platform LLC

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