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.

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 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.

Investigating the impact of inventory inaccuracy on the bullwhip effect in RFID-enabled supply chains using colored petri nets

2019 ◽  
Vol 14 (2) ◽  
pp. 360-384 ◽  
Author(s):  
Maria Drakaki ◽  
Panagiotis Tzionas
Keyword(s):  
Supply Chain ◽  
Supply Chains ◽  
Petri Nets ◽  
Information Sharing ◽  
Bullwhip Effect ◽  
Colored Petri Nets ◽  
Content Type ◽  
Multi Stage ◽  
The Impact ◽  
Serial Supply Chains

PurposeInformation distortion results in demand variance amplification in upstream supply chain members, known as the bullwhip effect, and inventory inaccuracy in the inventory records. As inventory inaccuracy contributes to the bullwhip effect, the purpose of this paper is to investigate the impact of inventory inaccuracy on the bullwhip effect in radio-frequency identification (RFID)-enabled supply chains and, in this context, to evaluate supply chain performance because of the RFID technology.Design/methodology/approachA simulation modeling method based on hierarchical timed colored petri nets is presented to model inventory management in multi-stage serial supply chains subject to inventory inaccuracy for various traditional and information sharing configurations in the presence and absence of RFID. Validation of the method is done by comparing results obtained for the bullwhip effect with published literature results.FindingsThe bullwhip effect is increased in RFID-enabled multi-stage serial supply chains subject to inventory inaccuracy. The information sharing supply chain is more sensitive to the impact of inventory inaccuracy.Research limitations/implicationsInformation sharing involves collaboration in market demand and inventory inaccuracy, whereas RFID is implemented by all echelons. To obtain the full benefits of RFID adoption and collaboration, different collaboration strategies should be investigated.Originality/valueColored petri nets simulation modeling of the inventory management process is a novel approach to study supply chain dynamics. In the context of inventory errors, information on RFID impact on the dynamic behavior of multi-stage serial supply chains is provided.

Use of Predictive and Simulation Models to Develop Strategies for Better Access Specialists Care

2020 ◽  
pp. 109-136
Author(s):  
Siang Li Chua ◽  
Wai Leng Chow
Keyword(s):  
Lead Time ◽  
Discrete Event ◽  
Simulation Models ◽  
Multiple Logistic Regression ◽  
Specialist Care ◽  
Event Simulation ◽  
Patients At Risk ◽  
The Impact ◽  
Specialist Outpatient Clinic ◽  
Des Model

No-shows are patients who miss scheduled Specialist Outpatient Clinic (SOC) appointments. No-shows can impact patients' access to care and appointment lead time. This chapter describes a data-driven strategy of improving access to specialist care through first developing a stratified predictive scoring model to identify patients at risk of no-shows; second, studying the impact of a dynamic overbooking strategy that incorporates the use of the no-show prediction model using discrete event simulation (DES) on lead time. Seventeen variables related to new SOC appointments for subsidized patients in 2016 were analyzed. Multiple logistic regression (MLR) found eight variables independently associated with no-shows with area under receiver operation curve (AUC) 70%. The model was tested and validated. DES model simulated the appointment overbooking strategy as applied to the top highest volume specialties and concluded that lead time of Specialty 1 and 2 can be shortened by 27.5 days (49% improvement) and 21.3 (33%) respectively.

scholarly journals CONWIP versus POLCA: A comparative analysis in a high-mix, low-volume (HMLV) manufacturing environment

2016 ◽  
Vol 9 (2) ◽  
pp. 432 ◽  
Author(s):  
Todd Frazee ◽  
Charles Standridge
Keyword(s):  
Discrete Event Simulation ◽  
Lead Time ◽  
Manufacturing Systems ◽  
Discrete Event ◽  
Model Verification ◽  
Manufacturing Environment ◽  
Event Simulation ◽  
Work In Process ◽  
Low Volume ◽  
Average Lead

Purpose: Few studies comparing manufacturing control systems as they relate to high-mix, low-volume applications have been reported. This paper compares two strategies, constant work in process (CONWIP) and Paired-cell Overlapping Loops of Cards with Authorization (POLCA), for controlling work in process (WIP) in such a manufacturing environment. Characteristics of each control method are explained in regards to lead time impact and thus, why one may be advantageous over the other.Design/methodology/approach: An industrial system in the Photonics industry is studied. Discrete event simulation is used as the primary tool to compare performance of CONWIP and POLCA controls for the same WIP level with respect to lead time. Model verification and validation are accomplished by comparing historic data to simulation generated data including utilizations. Both deterministic and Poisson distributed order arrivals are considered. Findings: For the system considered in this case study, including order arrival patterns, a POLCA control can outperform a CONWIP parameter in terms of average lead time for a given level of WIP. At higher levels of WIP, the performance of POLCA and CONWIP is equivalent. Practical Implications: The POLCA control helps limit WIP in specific áreas of the system where the CONWIP control only limits the overall WIP in the system. Thus, POLCA can generate acceptably low lead times at lower levels of WIP for conditions equivalent to the HMLV manufacturing systems studied.Originality/value: The study compliments and extends previous studies of  CONWIP and POLCA performance to a HMLV manufacturing environment. It demonstrates the utility of discrete event simulation in that regard. It shows that proper inventory controls in bottleneck áreas of a system can reduce average lead time.

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