Variability and Component Criticality in Component Reuse and Remanufacturing Systems

2007 ◽  
Author(s):  
Vijitashwa Pandey ◽  
Deborah Thurston
Keyword(s):  
Design Solution ◽  
Complex Nature ◽  
Design Decision ◽  
Component Reuse ◽  
Contributing Factors ◽  
System A ◽  
Take Back ◽  
Two Measures ◽  
High Degree

Product take-back and remanufacturing systems are difficult to implement cost-effectively. Two contributing factors to this problem are the complex nature of the interrelationships among components, and their high degree of variability. Legislated take-back mandates have made it imperative for manufacturers to realize when there is value to be recovered in components and when there is not. This paper proposes a component criticality method to help ascertain this remaining value. We also develop a metric that measures the randomness or variability that a reuse alternative imposes on the remanufacturing system. A case study on washing machines illustrates how the two measures can be incorporated into a design decision model, can help reduce the complexity of reuse operations, and result in a superior design solution.

Variability and Component Criticality in Component Reuse and Remanufacturing Systems

2010 ◽  
Vol 10 (4) ◽  
Author(s):  
Vijitashwa Pandey ◽  
Deborah Thurston
Keyword(s):  
Design Decision ◽  
Component Reuse ◽  
Component Level ◽  
Customer Perception ◽  
Effective Age ◽  
Take Back ◽  
Information Set ◽  
System Variability ◽  
Two Measures ◽  
High System

Different operations, such as take-back, cleaning, and repair, lead to high system variability rendering remanufacturing systems difficult to manage. Even when a product is successfully remanufactured, there remains the problem of customer perception of remanufactured products being not able to perform as well as new ones. The possibility of several different options (reusing, remanufacturing, and recycling) further compound the complexity of the information set that should be considered for effective remanufacturing. This paper develops a method that can be employed for making component level decisions that accounts for aforesaid issues. A metric is proposed that measures the randomness or variability imposed by a reuse alternative. A measure of effective age is also proposed, extending the lines of previous research. A washing machine example illustrates the method and how the two measures can be incorporated into a design decision model.

More Reliable Lifetime Distribution of System: A New Statistical Heuristic Model with Numeric Case Study

2011 ◽  
Vol 110-116 ◽  
pp. 2872-2878
Author(s):  
Mojtaba Mahdavi ◽  
Mohamad Mahdavi
Keyword(s):  
Distribution Function ◽  
Operating Systems ◽  
Extreme Value Distribution ◽  
Reliability Function ◽  
Lifetime Distribution ◽  
Value Distribution ◽  
Heuristic Model ◽  
System A ◽  
High Degree

—This paper explores a new method to find most reliable lifetime distribution function of systems, via an applied heuristic model. In most operating systems which complicity of system obligates high degree of reliability, this model will be use to propose a more appropriate reliability function between lifetime distribution based and another that is based on relevant Extreme Value distribution. A numeric study will be reviewed to clear the concepts of this paper.

scholarly journals The quest for better machine learning models to forecast COVID-19-related infections: A case study in the state of Pará-Brazil

2020 ◽  
Author(s):  
Renato Hidaka Torres ◽  
Wilson Rogério Soares ◽  
Orlando Shigueo Ohashi ◽  
Gustavo Pessin
Keyword(s):  
Machine Learning ◽  
Geographic Region ◽  
Complex Nature ◽  
Learning Models ◽  
Health Crisis ◽  
The Public ◽  
Linear Svm ◽  
High Degree ◽  
Machine Learning Models

Abstract COVID-19 disease has become an unprecedented public health crisis. Although a relatively small percentage of people require intensive care, due to the high degree of contagion of the disease, the public system quickly collapses. Due to the highly complex nature of this disease and variation in its behavior depending on the characteristics of each geographic region, in this work, we analyze data from the Amazon region in Brazil (Pará). We applied several machine learning models to forecast the contagious curve to up 10 days. The Linear SVM and Multilayer Perceptron presented the best overall performances. Until the discovery of a vaccine, every effort is needed to understand and anticipate this disease.

Technology and Hospital Information System: A Case of Implementation of Electronic Clinical Records in Hospital Maternity Irene Neto in Lubango, Angola

2019 ◽  
Vol 10 (11) ◽  
pp. 1131-1135
Author(s):  
Tomas Hambili Paulo Sanjuluca ◽  
◽  
Ricardo Correia ◽  
Anabela Antunes de Almeida ◽  
Ana Gloria Diaz Martinez ◽  
...  
Keyword(s):  
Maternity Hospital ◽  
Management Support ◽  
Retrospective Case ◽  
System A ◽  
Clinical Records ◽  
Retrospective Case Study ◽  
The Impact ◽  
And Child Health

Introduction: In order to have a good assessment of the quality of maternal and child health care, it is essential that there is up-to-date and reliable information. Objective: To evaluate the impact of the implementation of a computerized database of clinical processes in the admission, archive and medical statistics section, of Maternity hospital Irene Neto/Lubango-Angola. Methodology: A descriptive study with a quantitative and qualitative approach to carry out a retrospective case study deliveries and newborns, records from 2014 to 2017. Final considerations: The implementation of this project may contribute to the improvement of clinical management support management of the hospital as well as facilitating access to information for research and scientific production.

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