A Model-based Method for System Reconfiguration

2021 ◽  
pp. 1-67
Author(s):  
Lara Qasim ◽  
Andreas Hein ◽  
Sorin Olaru ◽  
Jean-Luc Garnier ◽  
Marija Jankovic
Keyword(s):  
Complex Systems ◽  
Historical Data ◽  
Level Of Functioning ◽  
System Reconfiguration ◽  
Configuration Generation ◽  
Effectiveness And Efficiency ◽  
System Configurations ◽  
Whole Life Cycle ◽  
System Effectiveness

Abstract System Reconfiguration is essential in complex systems management, as it is an enabler of system adaptability with regard to system evolutions. System evolutions have to be managed to ensure system effectiveness and efficiency through its whole life cycle, particularly when it comes to complex systems that take years of development and dozens of years of usage. In this context, system reconfiguration ensures system operation and maintains system “ilities” (e.g., reliability, availability, maintainability, testability, and safety). This research has been conducted in the context of a large international aerospace, space, ground transportation, defense, and security company. This research aims at supporting system reconfiguration during operations. Within current industrial practices, the development of reconfiguration support is challenging as it requires integrating data related to observations (from operations) and system design (from engineering). More specifically, there is a need to integrate and link relevant reconfiguration data concerning the system objectives, operational context, and level of functioning. This paper proposes integrating and linking this fundamental data within a reconfiguration method. MBSysRec is a multidisciplinary method that involves configuration generation and a multi-criteria decision-making method for configuration evaluation and selection to support system reconfiguration during operations. The method has been implemented on two projects based on historical data. Resulting configurations have been discussed and assessed by system reconfiguration experts. A SAR case study is used to demonstrate the method. The method is proven effective for finding relevant system configurations for reconfiguring the already deployed system to achieve search and rescue missions.

Teaching Computer Based Historical Data Analysis

1994 ◽  
Vol 6 (1) ◽  
pp. 52-58 ◽  
Author(s):  
Charles Anderson ◽  
Robert J. Morris
Keyword(s):  
Data Analysis ◽  
Social History ◽  
Historical Data ◽  
Good Practice ◽  
Computer Assisted ◽  
Historical Data Analysis ◽  
University Of Edinburgh ◽  
Computer Based ◽  
The University

A case study ofa third year course in the Department of Economic and Social History in the University of Edinburgh isusedto considerandhighlightaspects of good practice in the teaching of computer-assisted historical data analysis.

A Case Study on the Un-Used Capacity Assessment Using Time Driven Activity Based Costing for Magnetic Components

2020 ◽  
Vol 6 (1) ◽  
pp. 18-39
Author(s):  
Areena Zaini ◽  
Haryantie Kamil ◽  
Mohd Yazid Abu
Keyword(s):  
Historical Data ◽  
Manufacturing Sector ◽  
Type I ◽  
Activity Based Costing ◽  
Cost Rate ◽  
Continuous Innovation ◽  
Magnetic Components ◽  
Alignment Process ◽  
Capacity Cost

The Electrical & Electronic (E&E) company is one of Malaysia’s leading industries that has 24.5% in manufacturing sector production. With a continuous innovation of E&E company, the current costing being used is hardly to access the complete activities with variations required for each workstation to measure the un-used capacity in term of resources and cost. The objective of this work is to develop a new costing structure using time-driven activity-based costing (TDABC) at . This data collection was obtained at E&E company located at Kuantan, Pahang that focusing on magnetic component. The historical data was considered in 2018. TDABC is used to measure the un-used capacity by constructing the time equation and capacity cost rate. This work found three conditions of un-used capacity. Type I is pessimistic situation whereby according to winding toroid core, the un-used capacity of time and cost are -14820 hours and -MYR2.60 respectively. It means the system must sacrifice the time and cost more than actual apportionment. Type II is most likely situation whereby according to assembly process, the un-used capacity of time and cost are 7400 hours and MYR201575.45 respectively. It means the system minimize the time and cost which close to fully utilize from the actual apportionment. Type III is optimistic situation whereby according to alignment process, the un-used capacity of time and cost are 4120 hours and MYR289217.15 respectively. It means the system used small amount of cost and time from the actual apportionment.

scholarly journals Modeling of Emergency Supply Scheduling Problem Based on Reliability and Its Solution Algorithm under Variable Road Network after Sudden-Onset Disasters

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-15 ◽  
Author(s):  
Tinggui Chen ◽  
Shiwen Wu ◽  
Jianjun Yang ◽  
Guodong Cong ◽  
Gongfa Li
Keyword(s):  
Road Network ◽  
Road Networks ◽  
Sudden Onset ◽  
The Road ◽  
Bee Colony ◽  
Proposed Model ◽  
Effectiveness And Efficiency ◽  
In Transit ◽  
Emergency Supply

It is common that many roads in disaster areas are damaged and obstructed after sudden-onset disasters. The phenomenon often comes with escalated traffic deterioration that raises the time and cost of emergency supply scheduling. Fortunately, repairing road network will shorten the time of in-transit distribution. In this paper, according to the characteristics of emergency supplies distribution, an emergency supply scheduling model based on multiple warehouses and stricken locations is constructed to deal with the failure of part of road networks in the early postdisaster phase. The detailed process is as follows. When part of the road networks fail, we firstly determine whether to repair the damaged road networks, and then a model of reliable emergency supply scheduling based on bi-level programming is proposed. Subsequently, an improved artificial bee colony algorithm is presented to solve the problem mentioned above. Finally, through a case study, the effectiveness and efficiency of the proposed model and algorithm are verified.

scholarly journals A Personalized Machine-Learning-Enabled Method for Efficient Research in Ethnopharmacology. The Case of the Southern Balkans and the Coastal Zone of Asia Minor

2021 ◽  
Vol 11 (13) ◽  
pp. 5826
Author(s):  
Evangelos Axiotis ◽  
Andreas Kontogiannis ◽  
Eleftherios Kalpoutzakis ◽  
George Giannakopoulos
Keyword(s):  
Machine Learning ◽  
Coastal Zone ◽  
Extraction Process ◽  
Asia Minor ◽  
Efficiency And Effectiveness ◽  
Effectiveness And Efficiency ◽  
Intelligent Tools ◽  
Southern Balkans

Ethnopharmacology experts face several challenges when identifying and retrieving documents and resources related to their scientific focus. The volume of sources that need to be monitored, the variety of formats utilized, and the different quality of language use across sources present some of what we call “big data” challenges in the analysis of this data. This study aims to understand if and how experts can be supported effectively through intelligent tools in the task of ethnopharmacological literature research. To this end, we utilize a real case study of ethnopharmacology research aimed at the southern Balkans and the coastal zone of Asia Minor. Thus, we propose a methodology for more efficient research in ethnopharmacology. Our work follows an “expert–apprentice” paradigm in an automatic URL extraction process, through crawling, where the apprentice is a machine learning (ML) algorithm, utilizing a combination of active learning (AL) and reinforcement learning (RL), and the expert is the human researcher. ML-powered research improved the effectiveness and efficiency of the domain expert by 3.1 and 5.14 times, respectively, fetching a total number of 420 relevant ethnopharmacological documents in only 7 h versus an estimated 36 h of human-expert effort. Therefore, utilizing artificial intelligence (AI) tools to support the researcher can boost the efficiency and effectiveness of the identification and retrieval of appropriate documents.

Reliability-based covariate analysis for complex systems in heterogeneous environment: Case study of mining equipment

2018 ◽  
Vol 233 (4) ◽  
pp. 593-604
Author(s):  
Amin Moniri-Morad ◽  
Mohammad Pourgol-Mohammad ◽  
Hamid Aghababaei ◽  
Javad Sattarvand
Keyword(s):  
Complex Systems ◽  
Cox Regression ◽  
Reliability Evaluation ◽  
Distribution Functions ◽  
Heterogeneous Environment ◽  
Mining Equipment ◽  
Data Set ◽  
Explanatory Variables ◽  
The Impact

Operational heterogeneity and harsh environment lead to major variations in production system performance and safety. Traditional probabilistic model is dealt with time-to-event data analysis, which does not have the capability of quantifying and simulation of these types of complexities. This research proposes an integrated methodology for analyzing the impact of dominant explanatory variables on the complex system reliability. A flexible parametric proportional hazards model is developed by focusing on standard parametric Cox regression model for reliability evaluation in complex systems. To achieve this, natural cubic splines are utilized to create a smooth and flexible baseline hazards function where the standard parametric distribution functions do not fit into the failure data set. A real case study is considered to evaluate the reliability for multi-component mechanical systems such as mining equipment. Different operational and environmental explanatory variables are chosen for the analysis process. Research findings revealed that precise estimation of the baseline hazards function is a major part of the reliability evaluation in heterogeneous environment. It is concluded that an appropriate maintenance strategy potentially mitigate the equipment failure intensity.

scholarly journals The interconnection exchange and complex systems properties in power grid network

2021 ◽  
Vol 336 ◽  
pp. 05020
Author(s):  
Piotr Hadaj ◽  
Marek Nowak ◽  
Dominik Strzałka
Keyword(s):  
Complex Systems ◽  
Complex Networks ◽  
Real Data ◽  
Electrical Energy ◽  
Significant Drop ◽  
Average Efficiency ◽  
Grid Network ◽  
System Operator ◽  
Energy Network

A case study based on the real data obtained from the Polish PSE System Operator of the highest voltages electrical energy network is shown. The data about the interconnection exchange and some complex networks (graphs) parameters were examined, after the removal of selected nodes. This allowed to test selected network parameters and to show that the breakdown of only three nodes in this network can cause significant drop of its average efficiency.

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