scholarly journals A Modular Framework for the Life Cycle Based Evaluation of Aircraft Technologies, Maintenance Strategies, and Operational Decision Making Using Discrete Event Simulation

Aerospace ◽  
2021 ◽  
Vol 8 (7) ◽  
pp. 187
Author(s):  
Ahmad Ali Pohya ◽  
Jennifer Wehrspohn ◽  
Robert Meissner ◽  
Kai Wicke
Keyword(s):  
Decision Making ◽  
Life Cycle ◽  
Discrete Event Simulation ◽  
Product Life Cycle ◽  
Discrete Event ◽  
Estimation Methods ◽  
Maintenance Strategies ◽  
Event Simulation ◽  
Temporal Space ◽  
The Impact

Current practices for investment and technology decision making in aeronautics largely rely on regression-based cost estimation methods. Although quick to implement and easy to use, they suffer from a variety of limitations, both in temporal space and scope of applicability. While recent research and development in this area addresses these to a certain extent, aerospace engineering still lacks a flexible and customizable valuation framework. To this end, a generic environment for economic and operational assessment of aircraft and related products named LYFE is presented. This tool employs a discrete event simulation which models the product life cycle from its order through decades of operation and maintenance until disposal. This paper introduces its key characteristics and default methods alongside its modular program architecture. The capabilities are demonstrated with a case study of on-wing engine cleaning procedures which are triggered by a customized decision making module. Thereby, the impact on engine health, fuel efficiency and overall economic viability is quantified. On the whole, the framework introduced in this paper can be used to analyze not only physical products but also operational procedures and maintenance strategies as well as specified decision making algorithms in terms of their impact on an aircraft’s or system’s life cycle.

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.

A Multilayer Taxonomy of Cost Estimation Techniques, Looking at the Whole Product Lifecycle

2017 ◽  
Vol 140 (3) ◽  
Author(s):  
Stefania Altavilla ◽  
Francesca Montagna ◽  
Marco Cantamessa
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Life Cycle ◽  
Cost Estimation ◽  
Product Life Cycle ◽  
Recent Literature ◽  
Estimation Methods ◽  
Product Lifecycle ◽  
Conscious Decision ◽  
Decision Making Tool

Product cost estimation (PCE) still draws the attention of researchers and practitioners, even though it has been extensively discussed in the literature for more than 20 years. This is due to its central impact on the company's performance. Nowadays, the adoption of cost estimation methods seems to be limited, despite the multitude of examples and applications available. A possible reason is the multitude of approaches and techniques proposed in the literature, which, instead of representing a guide for enabling possible implementations, actually create confusion and ambiguity on their appropriateness for a particular application. Hence, this paper aims to provide a systematic review of the recent literature in the field of PCE, and intensively investigates the aspects that can enable a more conscious decision on the type of technique to be adopted. This results in the identification of five different perspectives, which can be taken simultaneously into account. By combining the different viewpoints, a new multilayer framework is derived, with a specific focus on the whole product life cycle. The proposed framework can be used as a decision-making tool by both researchers and practitioners. In fact, the former group can benefit from the new structure, as a way to identify new areas of possible research opportunities. The latter group is provided an operative guide for the application in industrial contexts.

Sign in / Sign up

Export Citation Format

Share Document