A Systematic Disturbance Analysis Method for Resilience Evaluation: A Case Study in Material Handling Systems

Ruiying Li,Xiaoyu Tian,Rui Kang,Li Yu

doi:10.3390/su11051447

Abstract

With the development of intelligent manufacturing technology, the material handling system (MHS) faces larger resilience challenges that threaten the sustainability of the system. To evaluate system resilience, the disturbance that the system may experience and the system response need to be identified in advance. This paper proposes a systematic and innovative approach to performing resilience-related disturbance analysis, i.e., disturbance mode and effects analysis (DMEA). Using this method, the possible disturbance modes, their occurrence probabilities, and the quantitative effects on system performance can be collected in a bottom-up process, and the information can be applied to further resilience quantification. Moreover, a quantitative system resilience evaluation framework for the MHS based on DMEA and the Monte Carlo method is presented. Production is defined as the key performance index of the system and is monitored to reflect the resilience behavior of the system after the disturbance occurs. The resilience of a tire tread handing system is quantified in our case study, and the results show the effectiveness of our DMEA-based resilience evaluation method. We also find that a reasonable system configuration and maintenance strategy can effectively improve system resilience, and a trade-off can be made between resilience and cost.

Highlights

Manufacturing provides a solid foundation for economic and societal developments, and it is the mainstay industry of the country
Using the disturbance mode and effects analysis (DMEA) and Monte Carlo-based simulation method detailed in Section 4, we evaluated the resilience of the tire tread handling system, and Figure 6 shows an example of the system’s resilience behavior after a certain disturbance
Using the 86 disturbance modes and the corresponding performance degradation and recovery data identified through DMEA, the expectation of the resilience for the tire tread handling system subjected to random disturbances is calculated to be RA = 0.9565 on the basis of 1000 simulation runs

Summary

Introduction

Manufacturing provides a solid foundation for economic and societal developments, and it is the mainstay industry of the country. The manufacturing process consumes a lot of the world’s resources, such as water and energy, and part of the consumption becomes a type of waste. Sustainable manufacturing presents a new manufacturing system paradigm from the perspective of sustainability. Sustainable manufacturing can be considered as an integrated strategy to reduce the environmental impacts caused by manufacturing [1], with the aim of coping with environmental challenges by minimizing natural resource consumption and improving manufacturing quality. Today’s sustainable manufacturing faces challenges related to maintaining manufacturing continuity because of potential disturbances. Resilience is an effective way to combat these unpredictable disturbances, and it helps to improve performance sustainability [2]

Objectives

Results

Conclusion