Modeling and quantifying uncertainty in the product design phase for effects of user preference changes

Abstract

Purpose

The purpose of this paper is to quantify external and internal uncertainties in product design process. The research addresses the measure of product future changes.

Design/methodology/approach

Two methods are proposed to model and quantify uncertainty in the product life cycle. Changes of user preferences are considered as the external uncertainty. Changes stemming from dependencies between components are addressed as the internal uncertainty. Both methods use developed mechanisms to capture and treat changes of user preferences. An agent-based model is developed to simulate sociotechnical events in the product life cycle for the external uncertainty. An innovative application of Big Data Analytics (BDA) is proposed to evaluate the external and internal uncertainties in product design. The methods can identify the most affected product components under uncertainty.

Findings

The results show that the proposed method could identify product changes during its life cycle, particularly using the proposed BDA method.

Practical implications

It is essential for manufacturers in the competitive market to know their product changes under uncertainty. Proposed methods have potential to optimize design parameters in complex environments.

Originality/value

This research bridges the gap of literature in the accurate estimation of uncertainty. The research integrates the change prediction and change transferring, applies data management methods innovatively, and utilizes the proposed methods practically.

Citation

Afshari, H. and Peng, Q. (2015), "Modeling and quantifying uncertainty in the product design phase for effects of user preference changes", Industrial Management & Data Systems, Vol. 115 No. 9, pp. 1637-1665. https://doi.org/10.1108/IMDS-04-2015-0163