Optimization of Complex Engineered Systems Under Risk and Uncertainty

2007 ◽  
Author(s):  
Seung-Kyum Choi ◽  
Mervyn Fathianathan ◽  
Dirk Schaefer
Keyword(s):  
Large Scale ◽  
Optimization Procedure ◽  
Decision Support Tool ◽  
Primary Objective ◽  
Risk And Uncertainty ◽  
Support Tool ◽  
Structural Problems ◽  
Complex Engineered Systems ◽  
Engineered Systems ◽  
Karhunen Loeve Transform

The advances in information technology significantly impact the engineering design process. The primary objective of this research is to develop a novel probabilistic decision support tool to assist management of structural systems under risk and uncertainty by utilizing a stochastic optimization procedure and IT tools. The proposed mathematical and computational framework will overcome the drawbacks of the traditional methods and will be critically demonstrated through large-scale structural problems. The efficiency of the proposed procedure is achieved by the combination of the Karhunen-Loeve transform with the stochastic analysis of polynomial chaos expansion to common optimization procedures. The proposed technology, comprising new and adapted current capabilities, will provide robust and physically reasonable solutions for practical engineering problems.

Neural Network Ensemble Approach to Pushed Convoys Dispatching Problems

2020 ◽  
Vol 27 (1) ◽  
pp. 70-82 ◽  
Author(s):  
Aleksandar Radonjić ◽  
Danijela Pjevčević ◽  
Vladislav Maraš
Keyword(s):  
Neural Network ◽  
Decision Support Tool ◽  
Primary Objective ◽  
Danube River ◽  
Decision Making Process ◽  
Neural Network Ensemble ◽  
Support Tool ◽  
Shipping Company ◽  
The Republic ◽  
Power Measurements

AbstractThis paper investigates the use of neural networks (NNs) for the problem of assigning push boats to barge convoys in inland waterway transportation (IWT). Push boat–barge convoy assignmentsare part of the daily decision-making process done by dispatchers in IWT companiesforwhich a decision support tool does not exist. The aim of this paper is to develop a Neural Network Ensemble (NNE) model that will be able to assist in push boat–barge convoy assignments based on the push boat power.The primary objective of this paper is to derive an NNE model for calculation of push boat Shaft Powers (SHPs) by using less than 100% of the experimental data available. The NNE model is applied to a real-world case of more than one shipping company from the Republic of Serbia, which is encountered on the Danube River. The solution obtained from the NNE model is compared toreal-world full-scale speed/power measurements carried out on Serbian push boats, as well as with the results obtained from the previous NNE model. It is found that the model is highly accurate, with scope for further improvements.

scholarly journals LO21: Consistency of CTAS scores by presenting complaint pre and post eCTAS implementation in 35 emergency departments across Ontario

CJEM ◽  
2020 ◽  
Vol 22 (S1) ◽  
pp. S14-S15
Author(s):  
S. McLeod ◽  
C. Thompson ◽  
B. Borgundvaag ◽  
L. Thabane ◽  
H. Ovens ◽  
...  
Keyword(s):  
Emergency Departments ◽  
Improve Patient Safety ◽  
Vital Signs ◽  
Decision Support Tool ◽  
High Volume ◽  
Population Based ◽  
Primary Objective ◽  
Absolute Difference ◽  
Altered Level ◽  
Support Tool

Introduction: eCTAS is a real time electronic triage decision-support tool designed to improve patient safety and quality of care by standardizing the application of the Canadian Triage and Acuity Scale (CTAS). The tool dynamically calculates a recommended CTAS score based on the presenting complaint, vital signs and selected clinical modifiers. The primary objective was to assess consistency of CTAS score distributions across 35 emergency departments (EDs) by 16 presenting complaints pre and post eCTAS implementation. Methods: This retrospective cohort study used population-based administrative data from January 2016 to December 2018 from all hospital EDs in Ontario that had implemented eCTAS with at least 9 months of data. Following a 3-month stabilization period, we compared data for 6 months post-eCTAS implementation to the same 6-month period the previous year (pre-implementation) to account for potential seasonal variation, patient volume and case-mix. We included triage encounters of adult (≥18 years) patients if they had one of 16 pre-specified high-volume, presenting complaints. A paired-samples t-test was used to determine consistency by estimating the absolute difference in CTAS distribution for each presenting complaint, by each hospital, pre and post eCTAS implementation, compared to the overall average of the 35 EDs. Results: There were 183,231 triage encounters in the pre-eCTAS cohort and 179,983 in the post-eCTAS cohort from 35 EDs across the province. Triage scores were more consistent with the overall average after eCTAS implementation in 6 (37.5%) presenting complaints: chest pain (cardiac features) (p < 0.001), extremity weakness/symptoms of cerebrovascular accident (p < 0.001), fever (p < 0.001), shortness of breath (p < 0.001), syncope (p = 0.02), and hyperglycemia (p = 0.03). Triage consistency was similar pre and post eCTAS implementation for the presenting complaints of altered level of consciousness, anxiety/situational crisis, confusion, depression/suicidal/deliberate self-harm, general weakness, head injury, palpitations, seizure, substance misuse/intoxication or vertigo. Conclusion: A standardized, electronic approach to performing triage assessments increased consistency in CTAS scores across many, but not all, high-volume CEDIS complaints. This does not reflect triage accuracy, as there are no known benchmarks for triage accuracy. Improvements in consistency were greatest for sentinel presenting complaints with a minimum allowable CTAS score.

On the Design of a Sustainable Production Line: The MetaCAM Tool

2015 ◽  
Author(s):  
Apostolos Fysikopoulos ◽  
Theocharis Alexopoulos ◽  
George Pastras ◽  
Panos Stavropoulos ◽  
Georgios Chryssolouris
Keyword(s):  
Energy Efficiency ◽  
Decision Support ◽  
Value Chain ◽  
Production Line ◽  
Optimization Procedure ◽  
Decision Support Tool ◽  
Life Cycles ◽  
Support Tool ◽  
Industrial Sectors

Nowadays, manufacturing enterprises face enormous environmental challenges, due to complex and diverse economic trends, including shorter product life cycles, rapid advances in science and technology, increased diversity in customer demands and globalization of production activities. Consequently, the cost is highly affected by environmentally related factors. Energy efficiency is one of the main factors, which together with waste management, affect manufacturing decisions. The complexity and diversity of the factors that determine energy efficiency require intelligent systems for their optimization at each “manufacturing level”. Manufacturing decisions should be taken as fast as possible and with the highest possible accuracy. Artificial intelligence/machine learning tools have made significant progress during the last decade and are suitable for such applications. The main objective of the current study is that an architecture for the development of a networked, online, decision support tool, be provided towards achieving sustainable value chain management. The main idea behind the proposed design is that stakeholders be assisted in taking decisions towards improving the energy and eco-efficiency of the entire value chain or parts of it. This is suggested within the context of a multi-objective optimization procedure, taking into account other important decision making attributes, such as flexibility, quality and time for the final reduction in the overall cost. This architecture incorporates real time information modules that interact with online monitoring systems, using any available information within the value chain and the existing IT tools. A partial realization of the proposed idea is implemented in the form of a user friendly software tool (the MetaCAM tool). This based, decision support tool aiming to optimize a current production line or to propose alternatives for the manufacturing of a product. The tool performs optimization based on a set of predefined criteria, namely energy, waste, cost and time. For each of these criteria, the end-user selects the desired weight factor in order to drive the optimization procedure accordingly. The tool presents the characteristics of the setup of the proposed optimized line and maintains all used data and calculations in order to be reused when necessary. For the tool’s validation, three real case studies from different industrial sectors have been used. The first case study comes from the domestic appliances sector (refrigerator door panel), the second one from the automotive sector (a two seat bench for light commercial vehicles) and finally, the third case study derives from the aeronautics sector and deals with the production of the loading ramp hinge of a military aircraft.

scholarly journals Primary Care Clinicians Attitudes and Knowledge of Pharmacogenetics in a Large, Multi-state, Healthcare System

2018 ◽  
Vol 9 (2) ◽  
pp. 6
Author(s):  
Megan Olander ◽  
Stephen Waring ◽  
David D Stenehjem ◽  
Allise Taran ◽  
Paul L Raneli ◽  
...  
Keyword(s):  
Primary Care ◽  
Conflicts Of Interest ◽  
Human Subjects ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Primary Objective ◽  
Pharmacogenetic Testing ◽  
Support Tool ◽  
Medication Therapy ◽  
Primary Care Clinicians

  Background: Considerable progress has been made in the way of pharmacogenetic research and the development of clinical recommendations; however, its implementation into clinical practice has been slower than anticipated. We sought to better understand its lack of clinical uptake within primary care. Aim: The primary objective of this survey was to ascertain primary care clinicians’ perceptions of pharmacogenetic use and implementation in an integrated health system of metropolitan and rural settings across several states. Methods: Primary care clinicians (including MDs, DOs, NPs, and PAs) were invited to participate in a survey via email. Questions about pharmacogenetics knowledge and perceptions were presented to assess current understanding and usage of pharmacogenetics in practice. Results: The rate of response for the survey was 17%. Of the 90 respondents, 58% were female, 69% were MDs/DOs, 20% were NPs, and 11% were PAs. Fifty-eight percent of respondents received their clinical degree in or after 2000. Ninety percent of respondents noted that they were uncomfortable ordering a pharmacogenetics test, with 76% stating they were uncomfortable applying the results of a pharmacogenetic test. Notably, 78% of respondents were interested in having pharmacogenetic testing available through Medication Therapy Management (MTM) services, although PAs were significantly less interested as compared to NPs and MD/DOs. Ninety-five percent of respondents were interested in a clinical decision support tool relevant to pharmacogenetic results. Conclusions: As a whole, prescribing clinicians in primary care clinics are uncomfortable in the ordering, interpreting, and applying pharmacogenetic results to individual patients. However, favorable attitudes towards providing pharmacogenetic testing through existing MTM clinics provides the opportunity for pharmacists to advance existing practices. Conflict of Interest: We declare no conflicts of interest or financial interests that the authors or members of their immediate families have in any product or service discussed in the manuscript, including grants (pending or received), employment, gifts, stock holdings or options, honoraria, consultancies, expert testimony, patents and royalties Treatment of Human Subjects: IRB determined project was non-HSR   Type: Student Project

Estimate Uncertainty: Miscommunication About Definitions of Engineering Terminology

2019 ◽  
Vol 142 (7) ◽  
Author(s):  
John Meluso ◽  
Jesse Austin-Breneman ◽  
Jose Uribe
Keyword(s):  
System Performance ◽  
Large Scale ◽  
Phase 1 ◽  
Parameter Estimate ◽  
Fortune 500 ◽  
System Level ◽  
Future Design ◽  
Complex Engineered Systems ◽  
Current Design ◽  
Engineered Systems

Abstract Communication has been shown to affect the design of large-scale complex engineered systems. Drawing from engineering design, communication, and management literature, this work defines miscommunication as when communication results in a “deficiency” or “problem” that hinders parties from fulfilling their values. This article details a consequential example of miscommunication at a Fortune 500 engineering firm with the potential to affect system performance. In phase 1, interviews with engineering practitioners (n = 82) identified disagreement about what constitutes a parameter “estimate” in the design process. Phase 2 surveyed engineering practitioners (n = 128) about whether estimates communicated for system-level tracking approximate “current” design statuses or “future” design projections. The survey found that both definitions existed throughout the organization and did not correlate with subsystem, position, or design phase. Engineers inadvertently aggregated both current and future estimates into single system-level parameters that informed decision-making, thereby constituting widespread or systemic miscommunication. Thus, even technical concepts may be susceptible to miscommunication and could affect system performance.

Decision-support tool for coordination of volunteers in large-scale lockdowns

2021 ◽  
pp. 102420
Author(s):  
Aleksandra Krstikj ◽  
Moisés Gerardo Contreras Ruiz Esparza ◽  
Jaime Mora Vargas ◽  
Laura Hervert Escobar ◽  
Cecilia López de la Rosa ◽  
...  
Keyword(s):  
Decision Support ◽  
Large Scale ◽  
Decision Support Tool ◽  
Support Tool

scholarly journals Planning and Suitability Assessment of Large-scale Nature-based Solutions for Flood-risk Reduction

2021 ◽  
Author(s):  
Adam Mubeen ◽  
Laddaporn Ruangpan ◽  
Zoran Vojinovic ◽  
Arlex Sanchez Torrez ◽  
Jasna Plavšić
Keyword(s):  
Flood Risk ◽  
Large Scale ◽  
Decision Support Tool ◽  
Careful Consideration ◽  
Climate Projections ◽  
Suitable Alternative ◽  
Support Tool ◽  
Suitability Assessment ◽  
Suitability Maps

AbstractAdverse effects of climate change are increasing around the world and the floods are posing significant challenges for water managers. With climate projections showing increased risks of storms and extreme precipitation, the use of traditional measures alone is no longer an option. Nature-Based Solutions (NBS) offer a suitable alternative to reduce the risk of flooding and provide multiple benefits. However, planning such interventions requires careful consideration of various factors and local contexts. The present paper provides contribution in this direction and it proposes a methodology for allocation of large-scale NBS using suitability mapping. The methodology was implemented within the toolboxes of ESRI ArcMap software in order to map suitability for four types of NBS interventions: floodplain restoration, detention basins, retention ponds, and river widening. The toolboxes developed were applied to the case study area in Serbia, i.e., the Tamnava River basin. Flood maps were used to determine the volume of floodwater that needs to be stored for reducing flood risk in the basin and subsequent downstream areas. The suitability maps produced indicate the potential of the new methodology and its application as a decision-support tool for selection and allocation of large-scale NBS.

scholarly journals A Hierarchical Route Guidance Framework for Off-Road Connected Vehicles

2018 ◽  
Vol 140 (7) ◽  
Author(s):  
Judhajit Roy ◽  
Nianfeng Wan ◽  
Angshuman Goswami ◽  
Ardalan Vahidi ◽  
Paramsothy Jayakumar ◽  
...  
Keyword(s):  
High Resolution ◽  
Large Scale ◽  
Optimal Path ◽  
Computational Cost ◽  
Grid Cell ◽  
Decision Support Tool ◽  
Route Guidance ◽  
Low Resolution ◽  
Support Tool ◽  
Optimal Cost

A new framework for route guidance, as part of a path decision support tool, for off-road driving scenarios is presented in this paper. The algorithm accesses information gathered prior to and during a mission which are stored as layers of a central map. The algorithm incorporates a priori knowledge of the low resolution soil and elevation information and real-time high-resolution information from on-board sensors. The challenge of high computational cost to find the optimal path over a large-scale high-resolution map is mitigated by the proposed hierarchical path planning algorithm. A dynamic programming (DP) method generates the globally optimal path approximation based on low-resolution information. The optimal cost-to-go from each grid cell to the destination is calculated by back-stepping from the target and stored. A model predictive control algorithm (MPC) operates locally on the vehicle to find the optimal path over a moving radial horizon. The MPC algorithm uses the stored global optimal cost-to-go map in addition to high resolution and locally available information. Efficacy of the developed algorithm is demonstrated in scenarios simulating static and moving obstacles avoidance, path finding in condition-time-variant environments, eluding adversarial line of sight detection, and connected fleet cooperation.

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