A System Dynamics Model to Evaluate the Impact of Production Process Disruption on Order Shipping

Cuauhtémoc Sánchez-Ramírez,José Roberto Mendoza Fong,Rocío Ramos-Hernández,Jorge Luis García-Alcaraz,Giner Alor-Hernández

doi:10.3390/app10010208

Abstract

Multiple studies have analyzed the importance of preventive maintenance. Similarly, they have developed and/or evaluated various spare part inventory management policies that help companies reduce the duration of production disruptions resulting from sudden mechanical failures. All of these studies assess the impact of mechanical failures on local aspects, such as idle times or management policies. However, they do not holistically evaluate how machine failures affect key performance indicators. To address this gap, we proposed a System Dynamics (SD) model to systemically analyze the impact of machine part failures on order shipping, a key performance indicator. Similarly, we assessed the impact of machine part failures on the levels of the company’s finished goods inventory. The research was conducted in a glass bottle manufacturing company. To increase order shipping as a performance indicator, we identified the key variables of the production process and conducted a sensitivity analysis of the variables. Our results indicate that it is possible to reach the company’s 98–100% complete delivery policy.

Highlights

IntroductionRandom disruptions in key supply chain processes (i.e., procurement, production, and distribution) are neither controllable nor predictable [1,2,3]
Random disruptions in key supply chain processes are neither controllable nor predictable [1,2,3]
To evaluate the hypothesis on the importance of spare part inventory during mechanical failures, we propose a System Dynamics (SD) model to both analyze the probability of failure of machine parts and determine the impact of lacking spare parts inventory on product deliveries

Summary

Introduction

Random disruptions in key supply chain processes (i.e., procurement, production, and distribution) are neither controllable nor predictable [1,2,3]. This motivates decision makers to implement specific strategies to both ensure continuous production and timely fulfill orders. Overall, most of these strategies seek to increase inventory of raw materials, equipment, and machine parts [4]. BPE manages a general inventory of those parts that often wear out naturally

Methods

Results

Conclusion