Redesign of the production system: A hard decision-making process

2015 ◽  
Author(s):  
A. C. Alves ◽  
R. M. Sousa ◽  
J. Dinis-Carvalho
Keyword(s):  
Decision Making ◽  
Production System ◽  
Decision Making Process ◽  
System A ◽  
Hard Decision

Definition of an Offshore Petroleum Production System by Using Fuzzy Sets and Utility Functions

2005 ◽  
Vol 9 (6) ◽  
pp. 684-692 ◽  
Author(s):  
Tiago C. da Fonseca ◽  
◽  
José R. P. Mendes ◽  
Celso K. Morooka ◽  
Ivan R. Guilherme ◽  
...  
Keyword(s):  
Decision Making ◽  
Fuzzy Sets ◽  
Production System ◽  
Petroleum Industry ◽  
Utility Functions ◽  
Oil Field ◽  
Petroleum Engineering ◽  
Decision Making Process ◽  
Field Development ◽  
Definition Of

Field development is a very important task in the petroleum industry. Decisions in this area may lead either to profitable success or to expensive failures, and usually involve several distinct areas in the scope of Petroleum Engineering and Science, such as Geology, Petreoleum Engineering, Offshore Engineering and Economics. Therefore, these subjects must be well understood by teams supporting the decision-making process. This work proposes a methodology to support managers in one stage of field development: the definition of the field production system. In order to determinate the production system to be installed in an oil field, attributes such as investment, profitability, safety, environmental preservation and technological experience must be considered. A decision-making team or agent must weight these attributes in order to achieve solutions accordingly to the company strategies and objectives. Combining a few mathematical tools to represent the process, the methodology proposed herein is an approach that considers not only the financial variables involved in a field decision process, but might include other aspects, or attributes, also important to guide a decision. To this end, the application of Multi-Attribute Analysis concepts is suggested. Also, to support the decision-making agent, the approach follows Utility Functions concepts in order to numerically represent the agent trend or inclination to each option. Considering that subjectivity and imprecision are naturally involved in the decision-making process, the approach incorporates Fuzzy Sets Theory concepts as a means of formalizing the computation of this uncertainty.

Indigenous Mothers' Aspirations for Their Children in Perth, Western Australia: The Value of Education and Schooling

2009 ◽  
Vol 38 (1) ◽  
pp. 65-73 ◽  
Author(s):  
Helen Lette ◽  
Edouard Tursan d'Espaignet ◽  
Linda Slack-Smith ◽  
Kerry Hunt ◽  
Janine Nannup
Keyword(s):  
Decision Making ◽  
Western Australia ◽  
School System ◽  
Decision Making Process ◽  
Major Theme ◽  
Positive Education ◽  
Structured Interviews ◽  
Education Experience ◽  
System A ◽  
Indigenous Children

AbstractThis project involved the collection of stories about the aspirations, goals and strategies from a sample of mothers of Indigenous children living in Perth, Western Australia. Analysis of the semi-structured interviews indicated that the education of their children was important for many of the mothers. Whilst some of the mothers preferred their children to learn about their Indigenous history, culture and identity, others valued the type of education that emanates from a mainstream-style school system. A major theme was a need for schools to partner with Indigenous parents in the decision-making process to engage the families in a positive education experience.

Prioritization of congenital cardiac surgical patients using fuzzy reasoning – a solution to the problem of the waiting list?

2006 ◽  
Vol 16 (3) ◽  
pp. 289-299 ◽  
Author(s):  
Ralf Holzer ◽  
Ed Ladusans ◽  
Denise Kitchiner ◽  
Ian Peart ◽  
Gordon Gladman ◽  
...  
Keyword(s):  
Decision Making ◽  
Expert System ◽  
Production System ◽  
Medical Decision Making ◽  
Waiting List ◽  
Surgical Patients ◽  
Medical Decision ◽  
Impact Factors ◽  
Decision Making Process ◽  
Rule Based

Surgical waiting lists are of high importance in countries, where the national health system is unable to deliver surgical services at a rate that would allow patients to avoid unnecessary periods of waiting. Prioritization of these lists, however, is frequently arbitrary and inconsistent.The objective of our research was to analyze the medical decision-making process when prioritizing patients with congenital cardiac malformations for cardiac surgical procedures, identifying an appropriate representation of knowledge, and transferring this knowledge onto the design and implementation of an expert system (“PrioHeart”).The medical decision-making process was stratified into three stages. The first was to analyze the details of the procedure and patient to define important impact factors on clinical priority, such as the risk of adverse events. The second step was to evaluate these impact factors to define an appropriate “timing category” within which a procedure should be performed. The third, and final, step was to re-evaluate the characteristics of individual patients to differentiate between those in the same timing category.We implemented this decision-making process using a rule-based production system with support for fuzzy sets, using the FuzzyCLIPS inference engine and expert system shell as a suitable development environment for the knowledge base.The “PrioHeart” expert system was developed to give paediatric cardiologists a tool to allow and facilitate the prioritization of patients on the cardiosurgical waiting list. Evaluation of “PrioHeart” on limited sets of patients documented appropriate results of prioritization, with a significant correlation between the prioritization made using “PrioHeart” and those results obtained by the individual consultant specialist.We conclude that our study has demonstrated the feasibility of using an expert system approach with a fuzzy, rule-based production system to implement the prioritization of cardiac surgical patients. The approach may potentially be transferable to other medical subspecialities.

scholarly journals Industry 4.0 and Decision Making

2021 ◽  
pp. 400-405
Author(s):  
Frédéric Rosin ◽  
Pascal Forget ◽  
Samir Lamouri ◽  
Robert Pellerin
Keyword(s):  
Decision Making ◽  
Production System ◽  
Industry 4.0 ◽  
Production Systems ◽  
Lean Production ◽  
Management Training ◽  
Decision Making Process ◽  
Use Case ◽  
Lean Management ◽  
Different Types

AbstractIndustry 4.0 is an ubiquitous term that suggests significant impacts on the productivity and flexibility of production systems. But to what extent do the various technologies associated with Industry 4.0 contribute to enhance autonomy of operational teams by helping them make better and faster decisions, particularly in the context of Lean production system? This paper proposes a model of different types of autonomy in the decision-making process, depending on whether or not the steps in the decision-making process are enhanced by technologies. This model will be tested afterwards in a use case implemented in a learning factory offering Lean management training before being tested in a real production unit.

scholarly journals Taxonomy of Fuzzy Multi-Attribute Decision Making Systems in Terms of Model, Inventor and Data Type

2018 ◽  
Vol 8 (1) ◽  
pp. 2568-2571
Author(s):  
R. Umar ◽  
. Sunardi ◽  
Y. B. Fitriana
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Calculation Method ◽  
Decision Makers ◽  
Decision Making Process ◽  
System A ◽  
Decision Making Processes ◽  
Multi Attribute Decision Making

Decision support systems are one of the choices decision-makers make in an attempt to cope with the problems related to the time length required in decision-making process. Such systems are known to improve the efficiency and accuracy in the decision-making processes. In developing a decision support system, a certain calculation method is required as part of its processing. One of the most commonly used methods is FMADM. This research discusses the clustering of decision support system using FMADM in an attempt to provide a taxonomy of decision support system based on FMADM.

A conceptual model of entrepreneurial reputation from a venture capitalist’s perspective

2016 ◽  
Vol 17 (3) ◽  
pp. 143-154 ◽  
Author(s):  
Claire Zerwas ◽  
Harald F.O. von Korflesch
Keyword(s):  
Decision Making ◽  
Literature Review ◽  
Corporate Reputation ◽  
New Venture ◽  
Decision Making Process ◽  
Venture Capitalists ◽  
Five Dimensions ◽  
System A ◽  
Key Drivers ◽  
Start Ups

Research on reputation has mainly focused on established companies ignoring the relevance of reputation for start-ups. However, start-ups also need to consider factors that influence their reputation with regard to different stakeholders, especially potential investors. In this article, we develop a model of the so-called ‘entrepreneurial reputation’ from a venture capitalist’s perspective. For that purpose, the RepTrak® System – a model of corporate reputation developed by the Reputation Institute – is discussed in the context of entrepreneurship. With the help of a literature review, we work out relevant criteria used by venture capitalists in their decision-making process of whether to invest or not to invest in a new venture and integrate these in the RepTrak® System. The following five dimensions appear to be the key drivers of entrepreneurial reputation from a venture capitalist’s perspective: (1) entrepreneur/team, (2) market/industry, (3) products/services, (4) innovation and (5) finance.

scholarly journals INFORMAÇÃO NO SISTEMA LOGÍSTICO REVERSO: UM GUIA AO PROCESSO DECISÓRIO/INFORMATION IN THE REVERSE LOGISTICS SYSTEM: A GUIDE TO THE DECISION-MAKING PROCESS

2020 ◽  
Vol 6 (10) ◽  
pp. 75128-75144
Author(s):  
Arnaldo Luis Darg Moreira ◽  
José Leandro Seguro ◽  
Aguinaldo Ferreira dos Santos ◽  
Daniel Ferreira dos Santos
Keyword(s):  
Decision Making ◽  
Reverse Logistics ◽  
Decision Making Process ◽  
Logistics System ◽  
System A

AAC Decision-Making and Mobile Technology: Points to Ponder

2014 ◽  
Vol 23 (2) ◽  
pp. 104-111 ◽  
Author(s):  
Mary Ann Abbott ◽  
Debby McBride
Keyword(s):  
Decision Making ◽  
Mobile Technology ◽  
Communication System ◽  
Augmentative And Alternative Communication ◽  
Evaluation Process ◽  
Decision Making Process ◽  
Alternative Communication ◽  
Ipod Touch ◽  
Feature Match

The purpose of this article is to outline a decision-making process and highlight which portions of the augmentative and alternative communication (AAC) evaluation process deserve special attention when deciding which features are required for a communication system in order to provide optimal benefit for the user. The clinician then will be able to use a feature-match approach as part of the decision-making process to determine whether mobile technology or a dedicated device is the best choice for communication. The term mobile technology will be used to describe off-the-shelf, commercially available, tablet-style devices like an iPhone®, iPod Touch®, iPad®, and Android® or Windows® tablet.

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