The application of a hybrid simulation modelling framework as a decision-making tool for TPM improvement

Abstract

Purpose

The purpose of this paper is to promote a system dynamics-discrete event simulation (SD-DES) hybrid modelling framework, one that is useful for investigating problems comprising multifaceted elements which interact and evolve over time, such as is found in TPM.

Design/methodology/approach

The hybrid modelling framework commences with system observation using field notes which culminate in model conceptualization to structure the problem. Thereafter, an SD-DEShybrid model is designed for the system, and simulated to proffer improvement programmes. The hybrid model emphasises the interactions between key constructs relating to the system, feedback structures and process flow concepts that are the hallmarks of many problems in production. The modelling framework is applied to the TPM operations of a bottling plant where sub-optimal TPM performance was affecting throughput performance.

Findings

Simulation results for the case study show that intangible human factors such as worker motivation do not significantly affect TPM performance. What is most critical is ensuring full compliance to routine and scheduled maintenance tasks and coordinating the latter to align with rate of machine defect creation.

Research limitations/implications

The framework was developed with completeness, generality and reuse in view. It remains to be applied to a wide variety of TPM and non-TPM-related problems.

Practical implications

The developed hybrid model is scalable and can fit into an existing discrete event simulation model of a production system. The case study findings indicate where TPM managers should focus their efforts.

Originality/value

The investigation of TPM using SD-DES hybrid modelling is a novelty.

Citation

Oleghe, O. and Salonitis, K. (2019), "The application of a hybrid simulation modelling framework as a decision-making tool for TPM improvement", Journal of Quality in Maintenance Engineering, Vol. 25 No. 3, pp. 476-498. https://doi.org/10.1108/JQME-06-2018-0056