An Ontology-Based Framework for Decision Support in Assembly Variant Design

2020 ◽  
Vol 21 (2) ◽  
Author(s):  
Shantanu Kumar Das ◽  
Abinash Kumar Swain
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Knowledge Base ◽  
Support System ◽  
Expert Knowledge ◽  
Complex Problem ◽  
Variant Design ◽  
Knowledge Based ◽  
Core Concepts ◽  
Design Type

Abstract The designer generates a variant product by applying several design suggestions that fulfilled a variety of customer requirements. These design suggestions rely on multiple domains of expert knowledge, which are unstructured and implicit. Moreover, these design suggestions have an impact on assembly joint information (liaison), which makes the variant design a complex problem. To effectively support the designers, this work presents a knowledge-based decision support system for assembly variant design using ontology. First, a knowledge base is built by the development of an ontology to formally represent the taxonomy, properties, and causal relationships of/among core concepts involved in the variant design. Second, a five-step sequential procedure is established to facilitate the utilization of this knowledge base for decision-making in variant design. The procedure takes the extracted liaison information from the CAD model of an existing product as the input and further used for generating a set of variant design decisions as the output through Semantic Web Rule Language (SWRL) rule-based reasoning. The inferred outputs by the process of reasoning are the design suggestions, the variant design type required for each design suggestion, and its effect on joint information. Based on the evaluation of the ontology, the precision, recall, and F-measure obtained are 79.3%, 82.1%, and 80.67%, respectively. Finally, the efficacy of the knowledge-based decision support system is evaluated using case studies from the aerospace and automotive domain.

Development of a knowledge-based decision support system for identifying adequate wastewater treatment for small communities

2004 ◽  
Vol 48 (11-12) ◽  
pp. 393-400 ◽  
Author(s):  
J. Comas ◽  
J. Alemany ◽  
M. Poch ◽  
A. Torrens ◽  
M. Salgot ◽  
...  
Keyword(s):  
Wastewater Treatment ◽  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Treatment Plan ◽  
Complex Problem ◽  
Treatment Level ◽  
Adequate Treatment ◽  
Small Communities ◽  
Knowledge Based

The identification of adequate treatment for small communities is a complex problem since it makes it necessary to combine aspects of the community and landscape, the receiving environment, and the available wastewater treatment technologies. This paper presents the development and implementation of a Knowledge-Based Decision Support System (KB-DSS) to tackle this problem. Different knowledge sources have been consulted in order to make up a comprehensive and accurate knowledge base. The core of the KB-DSS embraces two objectives. The first one is to assist in the selection of the treatment level adequate to fulfil the target quality standards for the receiving environment. The second one is to select the specific type of treatment. The KB-DSS is being applied to each one of the 3,482 different small communities comprised in the Small Communities Wastewater Treatment Plan of Catalonia, grouped according to river catchments. This paper also summarizes the different steps involved in the operation of the knowledge-based DSS when solving a real case study.

Contextual Fuzzy-Based Decision Support System Through Opinion Analysis: A Case Study at University of the Salerno

2016 ◽  
Vol 15 (05) ◽  
pp. 923-948 ◽  
Author(s):  
Carmen De Maio ◽  
Aurelio Tommasetti ◽  
Orlando Troisi ◽  
Massimiliano Vesci ◽  
Giuseppe Fenza ◽  
...  
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Description Logic ◽  
Expert Knowledge ◽  
Business Strategies ◽  
Management Decision ◽  
Simulation Environment ◽  
Knowledge Based

According to the literature about customer satisfaction and loyalty, it is possible to define knowledge-based system to support management decision-making in the organizations. Nevertheless, the problem as to how much the context impacts on correlation has not been investigated in the literature. This paper focuses on developing of Decision Support System (DSS) taking into account correlations among statistical factors, i.e., expert knowledge, and customers’ opinions depending on several contextual features, e.g., culture, location, in order to build context-sensitive simulation environment. The proposed work defines a general system design workflow to tailor knowledge-based DSS by using a fuzzy model to quantify correlations among variables in a given context. We explore ontologies to represent correlations among statistical factors, e.g., Calculative Commitment, Quality of Service. We apply fuzzy data analysis techniques to train fuzzy classifier on the customer’s opinions collected by survey. Finally, synergistic usage of Description Logic and Fuzzy Theory allows the implementation of a simulation environment that supports the management team to tune business strategies. The framework has been instantiated for a case study to support public administration at the University of the Salerno.

scholarly journals SUSTAINABLE AGRICULTURAL DEVELOPMENT: KNOWLEDGE‐BASED DECISION SUPPORT

2009 ◽  
Vol 15 (2) ◽  
pp. 294-309 ◽  
Author(s):  
Algimantas Kurlavičius
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Decision Analysis ◽  
Knowledge Base ◽  
Support System ◽  
Agricultural Development ◽  
Production Efficiency ◽  
Programming Model ◽  
Knowledge Based ◽  
Farm Model

The article introduces the knowledge‐based agricultural decision support system. The system includes database and knowledge base as well as modules used for formation of models, optimization, simulation, decision analysis and inference. The linear programming model contains several hundreds of variables and restrictions. The farm model, using entered data, is formed according to “if‐then” type rules that are stored in the knowledge base. Having solved the task of optimization, the particular values of variables indicate what kind of crops should be grown and in what area, as well as what animals and how many of them should be kept and what resources and how much of them have to be used for achieving the biggest benefit under the environmental and other conditions. The simulation was employed to test the sensitivity of the plan to weather and market variations. Having applied a set of production rules to the given facts and modelling results within the module of decision analysis and inference, conclusions and suggestions are made. Decision support system performs the analysis of production efficiency, resource reserves and shortage, and with the help of the Internet in real time provides a farmer with conclusions and suggestions necessary to increase the efficiency of production conforming to environmental constraints. The integration of optimization calculations and knowledge management into the agricultural decisions‐support system expands its possibilities and improves the quality of solutions. Santrauka Pristatoma žiniomis grįsta žemės ūkio sprendimų paramos sistema. Ją sudaro duomenų ir žinių bazės, modelių formavimo, optimizavimo, imitavimo, sprendimų analizės ir išvadų formavimo moduliai. Žemės ūkio įmonės modelis sudaromas pagal įvestus duomenis, remiantis žinių bazėje saugomomis „jeigu–taip“ tipo taisyklėmis. Išsprendus optimizavimo uždavinį gautos kintamųjų vertės rodo, kokie javai ir kokiame plote turi būti auginami, taip pat kokie gyvuliai ir kiek jų turi būti laikoma, kokie ištekliai ir kiek jų turi būti panaudota, norint pasiekti didžiausią naudą ūkyje nurodytomis aplinkosaugos ir kitomis sąlygomis. Imitavimo būdu patikrinamas gamybos plano jautrumas orų ir rinkos pokyčiams. Išvadų formulavimo modulyje, pritaikius duotiems faktams ir modeliavimo rezultatams produkcinių taisyklių rinkinį, gaunamos išvados bei pasiūlymai. Sprendimų paramos sistema atlieka gamybos efektyvumo, išteklių rezervų bei išteklių trūkumo analizę. Ūkininkas internetu gauna išvadas bei pasiūlymus, kaip didinti gamybos efektyvumą. Optimizavimo skaičiavimų ir žinių bazės integravimas į žemės ūkio sprendimų paramos sistemą išplečia jos galimybes ir pagerina sprendimų kokybę.

IMPLEMENTASI METODE VIKOR DALAM PENERIMAAN JURNALIS PADA KORAN WASPADA MEDAN

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Soraya Rahma Hayati ◽  
Mesran Mesran ◽  
Taronisokhi Zebua ◽  
Heri Nurdiyanto ◽  
Khasanah Khasanah
Keyword(s):  
Decision Making ◽  
Decision Support ◽  
Decision Support System ◽  
Decision Support Systems ◽  
Support System ◽  
Support Systems ◽  
Knowledge Based ◽  
Computer Based ◽  
Support Decision Making ◽  
Made In

The reception of journalists at the Waspada Daily Medan always went through several rigorous selections before being determined to be accepted as journalists at the Waspada Medan Daily. There are several criteria that must be possessed by each participant as a condition for becoming a journalist in the Daily Alert Medan. To get the best participants, the Waspada Medan Daily needed a decision support system. Decision Support Systems (SPK) are part of computer-based information systems (including knowledge-based systems (knowledge management)) that are used to support decision making within an organization or company. Decision support systems provide a semitructured decision, where no one knows exactly how the decision should be made. In this study the authors applied the VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) as the method to be applied in the decision support system application. The VIKOR method is part of the Multi-Attibut Decision Making (MADM) Concept, which requires normalization in its calculations. The expected results in this study can obtain maximum decisions.Keywords: Journalist Acceptance, Decision Support System, VIKOR

Rancang Bangun Aplikasi Penjurusan Minat Bakat Menggunakan Metode Forward Chaining

2016 ◽  
Vol 7 (2) ◽  
pp. 155-160
Author(s):  
Levi Jordan Halim ◽  
Ranny Ranny ◽  
P.M. Winarno
Keyword(s):  
Decision Support ◽  
Decision Support System ◽  
Support System ◽  
Multiple Intelligence ◽  
Student Activities ◽  
Forward Chaining ◽  
Knowledge Based ◽  
Activity Unit ◽  
Index Terms ◽  
Intelligence Scores

Plentiful choices of Student Activities Unit that offered by a campus like Multimedia Nusantara University can help students who want to choose a unit that suitable for them. The decision support system application with Forward Chaining method is built to help students choosing the Student Activity Unit that suits them. Multiple Intelligence method is used as the knowledge base at making the rules. The aspects that considered as attributes to choosing the Student Activities Unit is the initial interest and also the multiple intelligence scores that the level of conformity will be searched by using Forward Chaining method. This research has produced a knowledge-based decision support system that can help students at choosing Student Activities Unit that suitable for them with the highest accuracy of 86.67 percent. This system is designed in website with PHP and MySQL database programming language. Index Terms—Forward Chaining, Knowledge-based, Multimedia Nusantara University, Multiple Intelligence, Student Activities Unit 

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