scholarly journals An integrated simulation modelling approach for a warehouse 4.0

2021 ◽  
Author(s):  
Andrea Ferrari ◽  
Giovanni Zenezini ◽  
Antonio Carlin ◽  
Carlo Rafele
Keyword(s):  
Supply Chain ◽  
Discrete Event ◽  
Simulation Modelling ◽  
Business Environment ◽  
Industrial Robots ◽  
Agent Based ◽  
Integrated Simulation ◽  
Event Simulation ◽  
The Impact ◽  
And Storage

Abstract In a progressively unstable business environment characterized by customers' demand challenging to predict, innovative solutions must be developed to respond to the growing need for flexibility in supply chain operations. In this scenario, the innovations of Industry 4.0 allow exploiting new methods for the development, management, and improvement of processes. Supply chain operations can significantly benefit from implementing one of these innovations, namely Warehouse automation, which is composed of automated retrieval and storage systems (AS/RS) and mobile robots (MR). This article contributes provides a hybrid virtual model based on Agent-Based Modeling and Simulation (ABMS) and Discrete Event Simulation (DES) paradigms of an integrated warehouse system, aiming to an ex-ante evaluation of the level of performance of the various logistic flows and the impact of operating parameters. The system into analysis consists of an automated warehouse with a maxi-shuttle-type translator, enslaved by mobile industrial robots and interfaced with a laboratory factory system equipped with an assembly station. Four experiments are carried out to analyze the warehousing system's performance by varying different parameters and design configurations. Results show that the model can determine the best design trade-off in terms of performance and is able to identify the bottlenecks of the system.

scholarly journals Exiting the COVID-19 pandemic: after-shock risks and avoidance of disruption tails in supply chains

2021 ◽  
Author(s):  
Dmitry Ivanov
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Inventory Management ◽  
Supply Chain Coordination ◽  
Discrete Event ◽  
Inventory Costs ◽  
Event Simulation ◽  
Inventory Dynamics ◽  
Disruption Recovery ◽  
The Impact

AbstractEntering the COVID-19 pandemic wreaked havoc on supply chains. Reacting to the pandemic and adaptation in the “new normal” have been challenging tasks. Exiting the pandemic can lead to some after-shock effects such as “disruption tails.” While the research community has undertaken considerable efforts to predict the pandemic’s impacts and examine supply chain adaptive behaviors during the pandemic, little is known about supply chain management in the course of pandemic elimination and post-disruption recovery. If capacity and inventory management are unaware of the after-shock risks, this can result in highly destabilized production–inventory dynamics and decreased performance in the post-disruption period causing product deficits in the markets and high inventory costs in the supply chains. In this paper, we use a discrete-event simulation model to investigate some exit strategies for a supply chain in the context of the COVID-19 pandemic. Our model can inform managers about the existence and risk of disruption tails in their supply chains and guide the selection of post-pandemic recovery strategies. Our results show that supply chains with postponed demand and shutdown capacity during the COVID-19 pandemic are particularly prone to disruption tails. We then developed and examined two strategies to avoid these disruption tails. First, we observed a conjunction of recovery and supply chain coordination which mitigates the impact of disruption tails by demand smoothing over time in the post-disruption period. Second, we found a gradual capacity ramp-up prior to expected peaks of postponed demand to be an effective strategy for disruption tail control.

Discrete event simulation modelling to evaluate the impact of a quality improvement initiative on patient flow in a paediatric emergency department

2020 ◽  
Vol 37 (4) ◽  
pp. 193-199 ◽  
Author(s):  
Kenneth W McKinley ◽  
John Babineau ◽  
Cindy G Roskind ◽  
Meridith Sonnett ◽  
Quynh Doan
Keyword(s):  
Quality Improvement ◽  
Discrete Event Simulation ◽  
Patient Flow ◽  
Discrete Event ◽  
Simulation Modelling ◽  
Quality Improvement Initiative ◽  
Event Simulation ◽  
Specific Protocol ◽  
Time Specific ◽  
The Impact

ObjectiveWe developed a discrete event simulation model to evaluate the impact on system flow of a quality improvement (QI) initiative that included a time-specific protocol to decrease the time to antibiotic delivery for children with cancer and central venous catheters who present to a paediatric ED with fever.MethodsThe model was based on prospective observations and retrospective review of ED processes during the maintenance phase of the QI initiative between January 2016 and June 2017 in a large, urban, academic children’s hospital in New York City, USA. We compared waiting time for full evaluation (WT) and length of stay (LOS) between a model with and a model without the protocol. We then gradually increased the proportion of patients receiving the protocol in the model and recorded changes in WT and LOS.ResultsWe validated model outputs against administrative data from 2016, with no statistically significant differences in average WT or LOS for any emergency severity index (ESI). There were no statistically significant differences in these flow metrics between the model with and the model without the protocol. By increasing the proportion of total patients receiving this protocol, from 0.2% to 1.3%, the WT increased by 2.8 min (95% CI: 0.6 to 5.0) and 7.6 min (95% CI: 2.0 to 13.2) for ESI 2 and ESI 3 patients, respectively. This represents a 14.0% increase in WT for ESI 3 patients.ConclusionsSimulation modelling facilitated the testing of system effects for a time-specific protocol implemented in a large, urban, academic paediatric ED, showing no significant impact on patient flow. The model suggests system resilience, demonstrating no detrimental effect on WT until there is a 7-fold increase in the proportion of patients receiving the protocol.

Simulation and Analysis of Mission Capability Degrades Due to Supply for the B-1 Bomber

2011 ◽  
Vol 9 (3) ◽  
pp. 279-290
Author(s):  
Carl R Parson ◽  
John O Miller ◽  
Jeffery D Weir
Keyword(s):  
Supply Chain ◽  
Experimental Design ◽  
Discrete Event Simulation ◽  
Air Force ◽  
Discrete Event ◽  
Weapon System ◽  
Weapon Systems ◽  
Event Simulation ◽  
High Level ◽  
The Impact

This research develops a discrete event simulation to investigate factors that affect key Air Force (AF) metrics for gauging the health of the AF spares supply chain and the impact on maintaining the mission capability of individual weapon systems. We focus on the unscheduled maintenance actions at a single air base for a single weapon system – the B-1 Bomber. A notional fleet of 16 aircraft at a single air base is modeled based on historical supply and maintenance data. To identify and quantify the effects of various factors, an experimental design is used for analyzing the output of our high-level discrete event simulation. This exploration shows we successfully capture several factors that significantly impact the key metrics used for the B-1 and have the potential to significantly increase mission capability for this weapon system.

scholarly journals A Discrete Event Simulation Analysis of the Bullwhip Effect in a Multi-Product and Multi-Echelon Supply Chain of Fast Moving Consumer Goods

2020 ◽  
pp. 561-576
Author(s):  
Ramsha Ali ◽  
Ruzelan Khalid ◽  
Shahzad Qaiser
Keyword(s):  
Supply Chain ◽  
Information Sharing ◽  
Discrete Event Simulation ◽  
Fast Moving ◽  
Lead Time ◽  
Discrete Event ◽  
Bullwhip Effect ◽  
Event Simulation ◽  
Stochastic Lead Time ◽  
The Impact

Timely delivery is the major issue in Fast Moving Consumer Good (FMCG) since it depends on the lead time which is stochastic and long due to several reasons; e.g., delay in processing orders and transportation. Stochastic lead time can cause inventory inaccuracy where echelons have to keep high product stocks. Such performance inefficiency reflects the existence of the bullwhip effect (BWE), which is a common challenge in supply chain networks. Thus, this paper studies the impact of stochastic lead time on the BWE in a multi-product and multi-echelon supply chain of FMCG industries under two information-sharing strategies; i.e., decentralized and centralized. The impact was measured using a discrete event simulation approach, where a simulation model of a four-tier supply chain whose echelons adopt the same lead time distribution and continuous review inventory policy was developed and simulated. Different lead time cases under the information-sharing strategies were experimented and the BWE was measured using the standard deviation of demand ratios between echelons. The results show that the BWE cannot be eliminated but can be reduced under centralized information sharing. All the research analyses help the practitioners in FMCG industries get insight into the impact of sharing demand information on the performance of a supply chain when lead time is stochastic.

scholarly journals Balancing scarce hospital resources during the COVID-19 pandemic using discrete-event simulation

2021 ◽  
Author(s):  
G.J. Melman ◽  
A.K. Parlikad ◽  
E.A.B. Cameron
Keyword(s):  
Resource Allocation ◽  
Discrete Event Simulation ◽  
Elective Surgery ◽  
Discrete Event ◽  
Specific Patient ◽  
Event Simulation ◽  
The Impact ◽  
Allocation Decisions ◽  
Allocation Strategies ◽  
Resource Allocation Decisions

AbstractCOVID-19 has disrupted healthcare operations and resulted in large-scale cancellations of elective surgery. Hospitals throughout the world made life-altering resource allocation decisions and prioritised the care of COVID-19 patients. Without effective models to evaluate resource allocation strategies encompassing COVID-19 and non-COVID-19 care, hospitals face the risk of making sub-optimal local resource allocation decisions. A discrete-event-simulation model is proposed in this paper to describe COVID-19, elective surgery, and emergency surgery patient flows. COVID-19-specific patient flows and a surgical patient flow network were constructed based on data of 475 COVID-19 patients and 28,831 non-COVID-19 patients in Addenbrooke’s hospital in the UK. The model enabled the evaluation of three resource allocation strategies, for two COVID-19 wave scenarios: proactive cancellation of elective surgery, reactive cancellation of elective surgery, and ring-fencing operating theatre capacity. The results suggest that a ring-fencing strategy outperforms the other strategies, regardless of the COVID-19 scenario, in terms of total direct deaths and the number of surgeries performed. However, this does come at the cost of 50% more critical care rejections. In terms of aggregate hospital performance, a reactive cancellation strategy prioritising COVID-19 is no longer favourable if more than 7.3% of elective surgeries can be considered life-saving. Additionally, the model demonstrates the impact of timely hospital preparation and staff availability, on the ability to treat patients during a pandemic. The model can aid hospitals worldwide during pandemics and disasters, to evaluate their resource allocation strategies and identify the effect of redefining the prioritisation of patients.

scholarly journals Assessing asset monitoring levels for maintenance operations

2015 ◽  
Vol 26 (5) ◽  
pp. 632-659 ◽  
Author(s):  
Abdullah A Alabdulkarim ◽  
Peter Ball ◽  
Ashutosh Tiwari
Keyword(s):  
Asset Management ◽  
Business Models ◽  
Discrete Event ◽  
Dynamic Modelling ◽  
Simulation Models ◽  
Content Type ◽  
Event Simulation ◽  
Product Service ◽  
Asset Monitoring ◽  
The Impact

Purpose – Asset management has recently gained significance due to emerging business models such as Product Service Systems where the sale of asset use, rather than the sale of the asset itself, is applied. This leaves the responsibility of the maintenance tasks to fall on the shoulders of the manufacturer/supplier to provide high asset availability. The use of asset monitoring assists in providing high availability but the level of monitoring and maintenance needs to be assessed for cost effectiveness. There is a lack of available tools and understanding of their value in assessing monitoring levels. The paper aims to discuss these issues. Design/methodology/approach – This research aims to develop a dynamic modelling approach using Discrete Event Simulation (DES) to assess such maintenance systems in order to provide a better understanding of the behaviour of complex maintenance operations. Interviews were conducted and literature was analysed to gather modelling requirements. Generic models were created, followed by simulation models, to examine how maintenance operation systems behave regarding different levels of asset monitoring. Findings – This research indicates that DES discerns varying levels of complexity of maintenance operations but that more sophisticated asset monitoring levels will not necessarily result in a higher asset performance. The paper shows that it is possible to assess the impact of monitoring levels as well as make other changes to system operation that may be more or less effective. Practical implications – The proposed tool supports the maintenance operations decision makers to select the appropriate asset monitoring level that suits their operational needs. Originality/value – A novel DES approach was developed to assess asset monitoring levels for maintenance operations. In applying this quantitative approach, it was demonstrated that higher asset monitoring levels do not necessarily result in higher asset availability. The work provides a means of evaluating the constraints in the system that an asset is part of rather than focusing on the asset in isolation.

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