Lean process mining: adopting process mining in lean manufacturing for dynamic process mapping and avoiding waste occurrence in real time

Abstract

Purpose

This paper aims to recommend a method entitled “lean process mining (LPM)” for mapping, analyzing and improving the material/information flows in the value stream of manufacturing processes.

Design/methodology/approach

The method is developed based on literature review and in-depth explorative research in value stream mapping and process mining approaches. The proposed LPM framework consists of three phases including as-realized process state, improvement strategies and reengineered process state. Hence, firstly, extracts the as-realized model, measures the identified wastes and identifies the sources of wastes. Secondly, implements prediction-recommendation-prevention strategies. Thirdly, reengineers the process model and measures the improved wastes.

Findings

It presents the applicability of the proposed approach in (1) online observation of manufacturing process behavior and tracing the process deviations dynamically in real time to identify the sources of waste; (2) avoiding defective products occurring during the production and eliminating the relevant derived wastes including wasted material, wasted energy, waste of labor, excess inventory, increased production lead time and wasted operational costs.

Originality/value

The practical application of LPM is illustrated through implementing it in a real-life manufacturing case. The outcomes prove the remarkable applicability of this method in lean manufacturing to avoid waste occurrence in the value stream.

Citation

Khakpour, R., Ebrahimi, A. and Seyed-Hosseini, S.-M. (2024), "Lean process mining: adopting process mining in lean manufacturing for dynamic process mapping and avoiding waste occurrence in real time", International Journal of Lean Six Sigma, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/IJLSS-03-2024-0059