Case Based Reasoning and TRIZ : a coupling for Innovative conception in Chemical Engineering

With the evolutions of the surrounding world market, researchers and engineers have to propose technical innovations. Nevertheless, Chemical Engineering community demonstrates a small interest for innovation compared to other engineering fields. In this paper, an approach to accelerate inventive preliminary design for Chemical Engineering is presented. This approach uses Case Based Reasoning (CBR) method to model, to capture, to store and to make available the knowledge deployed during design. CBR is a very interesting method coming from Artificial Intelligence, for routine design. Indeed, in CBR the main assumption is that a new problem of design can be solved with the help of past successful ones. Consequently, the problem solving process is based on past successful solutions therefore the design is accelerated but creativity is limited and not stimulated. Our approach is an extension of the CBR method from routine design to inventive design. One of the main drawbacks of this method is that it is restricted in one particular domain of application. To propose inventive solution, the level of abstraction for problem resolution must be increased. For this reason CBR is coupled with the TRIZ theory (Russian acronym for Theory of solving inventive problem). TRIZ is a problem solving method that increases the ability to solve creative problems thanks to its capacity to give access to the best practices in all the technical domains. The proposed synergy between CBR and TRIZ combines the main advantages of CBR (ability to store and to reuse rapidly knowledge) and those of TRIZ (no trade off during resolution, inventive solutions). Based on this synergy, a tool is developed and a mere example is treated

Soil Stabilization Manual 2014 Update

Soil Stabilization is used for a variety of activities including temporary wearing curses, working platforms, improving poor subgrade materials, upgrading marginal materials, dust control, and recycling old roads containing marginal materials. There are a number methods of stabilizing soils including modifying the gradation, the use of asphalt or cement stabilizers, geofiber stabilization and chemical stabilization. Selection of the method depends on the soil type, environment and application. This manual provide tools and guidance in the selection of the proper stabilization method and information on how to apply the method. A major portion of this manual is devoted to the use of stabilizing agents. The methods described here are considered best practices for Alaska.State of Alaska, Alaska Dept. of Transportation and Public Facilitie

Case Base Mining for Adaptation Knowledge Acquisition

In case-based reasoning, the adaptation of a source case in order to solve the target problem is at the same time crucial and difficult to implement. The reason for this difficulty is that, in general, adaptation strongly depends on domain-dependent knowledge. This fact motivates research on adaptation knowledge acquisition (AKA). This paper presents an approach to AKA based on the principles and techniques of knowledge discovery from databases and data-mining. It is implemented in CABAMAKA, a system that explores the variations within the case base to elicit adaptation knowledge. This system has been successfully tested in an application of case-based reasoning to decision support in the domain of breast cancer treatment

DecMS : an approach to providing decision support within NEC delivery

Decision-making across the military capability lifecycle phases can vary considerably in terms of the types of decisions made and the manner in which they are made. Although decision-making has received considerable attention within the research community, much work has concentrated on providing decision support for particular styles of decision-making. However, within capability delivery there is a need to develop approaches that can both map styles of decision-making to particular decision problems, and provide decision support at an executable level of detail. This paper presents the Decision Management and Support (DecMS) approach to providing decision support during capability delivery. The approach is based upon refining a fundamental model of decision-making to an executable level of detail. Refinement is controlled using analogical reasoning to ensure that the model is refined in accordance with the needs of the decision problem at hand. Future work will involve testing the effectiveness of the approach

Integrating case-based reasoning and hypermedia documentation: an application for the diagnosis of a welding robot at Odense steel shipyard

Reliable and effective maintenance support is a vital consideration for the management within today's manufacturing environment. This paper discusses the development of a maintenance system for the world's largest robot welding facility. The development system combines a case-based reasoning approach for diagnosis with context information, as electronic on-line manuals, linked using open hypermedia technology. The work discussed in this paper delivers not only a maintenance system for the robot stations under consideration, but also a design framework for developing maintenance systems for other similar applications

Constraint-based adaptation for complex space configuration in building services

In this paper an object-based CAD programming is used to take advantage of standardization to handle the schematic design, sizing and layout planning for ceiling mounted fan coil system in a building ceiling void. In order to deal with more complex geometry and real building size, we have used a hybrid approach combining case-based reasoning and constraint programming techniques. Very often, building services engineers use previous solutions and adapt them to new problems. Case-based reasoning mirrors this practical approach and did help us deal effectively with increasingly complex geometry. Our approach combines automation and interactivity. From the specification of the building 3D BIM model, our software prototype proceeds through four steps. First, the user divides the building into zones, each zone being defined by a geometrical primitive (i.e. rectangle zone, triangle zone, curved zone, etc.). Next, for each zone a similar case is retrieved from the case library. The retrieval process will generate a first incomplete 3D solution containing some inconsistencies. Next, the incomplete solution is adapted, using constraint programming techniques, to provide a consistent solution. Finally, distribution routes (i.e. ducts and pipes) are generated using constraint programming techniques. The 3D fan coil solution can be modified or improved by the designer, while providing further contribution by concentrating on interactivity. The project has been funded by the Engineering and Physical Sciences Research Council (EPSRC) in the UK

Case-based reasoning combined with statistics for diagnostics and prognosis

Many approaches used for diagnostics today are based on a precise model. This excludes diagnostics of many complex types of machinery that cannot be modelled and simulated easily or without great effort. Our aim is to show that by including human experience it is possible to diagnose complex machinery when there is no or limited models or simulations available. This also enables diagnostics in a dynamic application where conditions change and new cases are often added. In fact every new solved case increases the diagnostic power of the system. We present a number of successful projects where we have used feature extraction together with case-based reasoning to diagnose faults in industrial robots, welding, cutting machinery and we also present our latest project for diagnosing transmissions by combining Case-Based Reasoning (CBR) with statistics. We view the fault diagnosis process as three consecutive steps. In the first step, sensor fault signals from machines and/or input from human operators are collected. Then, the second step consists of extracting relevant fault features. In the final diagnosis/prognosis step, status and faults are identified and classified. We view prognosis as a special case of diagnosis where the prognosis module predicts a stream of future features

Feature weighting techniques for CBR in software effort estimation studies: A review and empirical evaluation

Context : Software effort estimation is one of the most important activities in the software development process. Unfortunately, estimates are often substantially wrong. Numerous estimation methods have been proposed including Case-based Reasoning (CBR). In order to improve CBR estimation accuracy, many researchers have proposed feature weighting techniques (FWT). Objective: Our purpose is to systematically review the empirical evidence to determine whether FWT leads to improved predictions. In addition we evaluate these techniques from the perspectives of (i) approach (ii) strengths and weaknesses (iii) performance and (iv) experimental evaluation approach including the data sets used. Method: We conducted a systematic literature review of published, refereed primary studies on FWT (2000-2014). Results: We identified 19 relevant primary studies. These reported a range of different techniques. 17 out of 19 make benchmark comparisons with standard CBR and 16 out of 17 studies report improved accuracy. Using a one-sample sign test this positive impact is significant (p = 0:0003). Conclusion: The actionable conclusion from this study is that our review of all relevant empirical evidence supports the use of FWTs and we recommend that researchers and practitioners give serious consideration to their adoption