Decision-focussed resource modelling for design decision support

Resource management including resource allocation, levelling, configuration and monitoring has been recognised as critical to design decision making. It has received increasing research interests in recent years. Different definitions, models and systems have been developed and published in literature. One common issue with existing research is that the resource modelling has focussed on the information view of resources. A few acknowledged the importance of resource capability to design management, but none has addressed the evaluation analysis of resource fitness to effectively support design decisions. This paper proposes a decision-focused resource model framework that addresses the combination of resource evaluation with resource information from multiple perspectives. A resource management system constructed on the resource model framework can provide functions for design engineers to efficiently search and retrieve the best fit resources (based on the evaluation results) to meet decision requirements. Thus, the system has the potential to provide improved decision making performance compared with existing resource management systems

Cost Decision Support in Product Design

The constraints addressed in decision making during product design, process planning and production planning determine the admissible solution space for the manufacture of products. The solution space determines largely the costs that are incurred in the production process. In order to be able to make economically sound decisions, costing data support must be integrated into the decision making processes. Regarding product design, the designer must be supplied with transparent costing data, that is ready for direct application. In this paper a functional architecture for costing data support during product design, as well as a corresponding data structure are presented

Data Mining to Support Engineering Design Decision

The design and maintenance of an aero-engine generates a significant amount of documentation. When designing new engines, engineers must obtain knowledge gained from maintenance of existing engines to identify possible areas of concern. Firstly, this paper investigate the use of advanced business intelligence tenchniques to solve the problem of knowledge transfer from maintenance to design of aeroengines. Based on data availability and quality, various models were deployed. An association model was used to uncover hidden trends among parts involved in maintenance events. Classification techniques comprising of various algorithms was employed to determine severity of events. Causes of high severity events that lead to major financial loss was traced with the help of summarization techniques. Secondly this paper compares and evaluates the business intelligence approach to solve the problem of knowledge transfer with solutions available from the Semantic Web. The results obtained provide a compelling need to have data mining support on RDF/OWL-based warehoused data

Design of Decision Support System Selection of Beach Tourism Object in GunungKidul Using Fuzzy AHP Method

The tourism industry is currently one of the important assessments for a certain region. Gunungkidul has a lot of of beach tourism potentials until visitors are confused to choose the right beach. The purpose of this research is to analyze and apply Fuzzy Analytical Hierarchy Process method in calculating the selection of beach tourism object in Gunungkidul with eight main criteria into a website.Multi Criteria Decision Making (MCDM) is a decision-making method to establish the best alternative of a number of alternatives based on several criteria that will be considered. One method of MCDM is the Fuzzy Analytical Hierarchy Process method. Fuzzy Analytical Hierarchy Process is a method of developing Analytical Hierarchy Process (AHP), which can describe unclear decisions and minimize uncertainty on AHP. Fuzzy approach, especially triangular fuzzy number to AHP scale, is expected to minimize uncertainty so that expected result was obtained more accurately.The decision support system for choosing a beach resort in Gunungkidul has been successfully built by applying the Fuzzy Analytical Hierarchy Process method. The calculation of Fuzzy Analytical Hierarchy Process method with the same computer result with manual calculation. The testing system was done using Black Box method by testing Alpha and Betha. From the results of system testing, it was known that the average result of the overall function score was 104 which was on rating scale 97.51 - 120 (Very Good)

Information system support in construction industry with semantic web technologies and/or autonomous reasoning agents

Information technology support is hard to find for the early design phases of the architectural design process. Many of the existing issues in such design decision support tools appear to be caused by a mismatch between the ways in which designers think and the ways in which information systems aim to give support. We therefore started an investigation of existing theories of design thinking, compared to the way in which design decision support systems provide information to the designer. We identify two main strategies towards information system support in the early design phase: (1) applications for making design try-outs, and (2) applications as autonomous reasoning agents. We outline preview implementations for both approaches and indicate to what extent these strategies can be used to improve information system support for the architectural designer

A decision-based perspective for the design of methods for systems design

Organization of material, a definition of decision based design, a hierarchy of decision based design, the decision support problem technique, a conceptual model design that can be manufactured and maintained, meta-design, computer-based design, action learning, and the characteristics of decisions are among the topics covered

Ontology Building of Manufacturing Quality Knowledge for Design Decision Support

This work was funded by National Natural Science Foundation of China (No: 70472066, 70771091), the project of Bureau of Science, Technology and Industry for National Defence, China (No. Z142008A001), the NPU Foundation for Humanities, Social Science, and Management Science Development (No. RW200817), which are gratefully acknowledged.Manufacturing knowledge on product quality is a kind of typical knowledge for supporting design decisions. In order to clearly identify and understand design decisions and their knowledge needs on manufacturing quality, an ontology of design decisions and manufacturing quality knowledge is developed. The methodology and tool used for the development of the proposed ontology is firstly introduced. The design decisions are organized along with five main design phases ranging from planning and task clarification, conceptual design, embodiment design to detail design. The knowledge needs of different design decisions, especially on the manufacturing quality knowledge, are analyzed through competition questions. Then, the ontology is built in the form of a hierarchical structure through the proposed methodology and ontology editor. Based on the developed ontology, further instances of the classes in the ontology can be filled as detailed knowledge, and can be accumulated for further construction of knowledge base

DEKAS - An evolutionary case-based reasoning system to support protection scheme design

This paper describes a decision support system being developed in conjunction with two UK utility companies to aid the design of electrical power transmission protection systems. A brief overview of the application domain is provided, followed by a description of the work carried out to date concerning the development and deployment of the Design Engineering Knowledge Application System (DEKAS). The paper then discusses the provision of intelligent decision support to the design engineer through the application of case-based reasoning (CBR). The key benefits from this will be outlined in conjunction with a relevant case study

Decision Support System for Design and Evaluation of Pipeline Projects

Petronet India Limited (PIL) was created to give impetus to investments in pipeline projects for transportation of petroleum products in the country. Since these projects have a long life and require large investments, correct assessment of location, capacity and financial viability are of critical importance. This paper is based on the study undertaken for PIL to evaluate a few of their pipeline projects. The study resulted in creation of a comprehensive software package that is capable of operational and financial evaluation of pipeline projects based on countrywide view on production and distribution of petroleum products. The core of the package is an LP based optimization model. The package is capable of performing sensitivity analysis to investigate the impact of uncertainty on the proposed project due to from changes in the values of key factors including distribution network and capacities, refining capacities and pattern of demand. •A model is developed for identification of viable pipeline projects, taking into account the demand and capacity additions to production and distribution network for petroleum products in the future. •The model can be used for financial evaluation of such projects based on appropriate assumptions to forecast the investments required as well as the net cash flows from the project. •The solution procedure is implemented for the models developed in the form of a software package that would allow the decision maker to experiment with assumption and generate solutions with ease and with little manual intervention. •The software package developed above is further embellished so that it also provides additional information to the decision maker in the form of reports that contain details of movement of products and the mode combinations used for the movements.