Materials selection of a bicycle frame using cost per unit property and digital logic methods

The aim of this paper is to develop the material selection method and select the optimum material for the application of folding bicycle frame. Two methods are introduced for the selection of materials, such as cost per unit property and digital logic methods. In cost per unit property, only one property (strength) is considered whereas in digital logic method, multiple properties such as tensile strength, yield strength, young’s modulus, toughness and density were considered for the optimum selection of the materials. The Ashby’s material selection chart was used for the initial screening of the candidate materials. The results are presented both in tabular and graphical forms. The materials selection method showed that AISI 1020 steel, Ti-alloy, carbon fiber reinforced polymer (CFRP), kevlar fiber reinforced polymer (KFRP) and glass fiber reinforced polymer (GFRP) are the candidate materials for the design of bicycle frame. From the cost per unit property method it is found that the KFRP shows the least cost material followed by AISI 1020 steel material. The digital logic method also showed the highest figure of merit value for KFRP material followed by AISI steel and Ti-alloy. Based on the developed materials selection method and analysis of the few candidate materials it can be concluded that the KFRP is the suitable material for the design and application of bicycle frame

Material selection method in design of automotive brake disc

An automotive brake disc or rotor is a device for slowing or stopping the motion of a wheel while it runs at a certain speed. The widely used brake rotor material is cast iron which consumes much fuel due to its high specific gravity. The aim of this paper is to develop the material selection method and select the optimum material for the application of brake disc system emphasizing on the substitution of this cast iron by any other lightweight material. Two methods are introduced for the selection of materials, such as cost per unit property and digital logic methods. Material performance requirements were analyzed and alternative solutions were evaluated among cast iron, aluminium alloy, titanium alloy, ceramics and composites. Mechanical properties including compressive strength, friction coefficient, wear resistance, thermal conductivity and specific gravity as well as cost, were used as the key parameters in the material selection stages. The analysis led to aluminium metal matrix composite as the most appropriate material for brake disc system

A Combined Finite Element-Multiple Criteria Optimization Approach for Materials Selection of Gas Turbine Components

The design of critical components for aerospace applications involves a number of conflicting functional requirements: reducing fuel consumption, cost, and weight, while enhancing performance, operability and robustness. As several materials systems and concepts remain competitive, a new approach that couples finite element analysis (FEA) and established multicriteria optimization protocols is developed in this paper. To demonstrate the approach, a prototypical materials selection problem for gas turbine combustor liners is chosen. A set of high temperature materials systems consisting of superalloys and thermal barrier coatings is considered as candidates. A thermo-mechanical FEA model of the combustor liner is used to numerically predict the response of each material system candidate. The performance of each case is then characterized by considering the material cost, manufacturability, oxidation resistance, damping behavior, thermomechanical properties, and the FEA postprocessed parameters relating to fatigue and creep. Using the obtained performance values as design criteria, an ELECTRE multiple attribute decision-making (MADM) model is employed to rank and classify the alternatives. The optimization model is enhanced by incorporating the relative importance (weighting factors) of the selection criteria, which is determined by multiple designers via a group decision-making process.Engineering and Applied Science

A Review of Cutting-edge Techniques for Material Selection

Selecting the optimum material for a given application is a complex task for engineers and designers across all industrial fields. There are a huge number of materials now available with a range of different properties and behaviours and so it has become even more necessary to carry out a systematic process in order to screen and/or rank the materials to give a promising number of candidates. The output of the material selection process depends upon which method is used. In some methods, a chart can be used to identify promising candidates whereas in others a single ‘optimum’ material may be chosen or a ranked list of candidates identified. This paper aims to summarise the documented techniques for material selection, evaluating the methods that are currently available, and compare the methods for consistency and effectiveness

A weighted rough set based fuzzy axiomatic design approach for the selection of AM processes

Additive manufacturing (AM) or 3D printing, as an enabling technology for mass customization or personalization, has been developed rapidly in recent years. Various design tools, materials, machines and service bureaus can be found in the market. Clearly, the choices are abundant, but users can be easily confused as to which AM process they should use. This paper first reviews the existing multi-attribute decision-making methods for AM process selection and assesses their suitability with regard to two aspects, preference rating flexibility and performance evaluation objectivity. We propose that an approach that is capable of handling incomplete attribute information and objective assessment within inherent data has advantages over other approaches. Based on this proposition, this paper proposes a weighted preference graph method for personalized preference evaluation and a rough set based fuzzy axiomatic design approach for performance evaluation and the selection of appropriate AM processes. An example based on the previous research work of AM machine selection is given to validate its robustness for the priori articulation of AM process selection decision support

Experimental Investigation, ANN Modelling and TOPSIS Optimization of a Gasoline Premixed HCCI-DI Engine with Direct Injection of FeCl3 Nanodditive Blended WCO

Experiments have been carried out to compute performance, combustion and emission characteristics of a homogeneous charge compression ignition – direct injection (HCCI-DI) engine in which 20% of the fuel was premixed in the intake manifold and the remaining 80% of the fuel was injected directly. Gasoline was selected as the premixed fuel and three different fuel combinations, namely, diesel, B50 (50% waste cooking oil (WCO) and 50% diesel by volume) and WCO were selected as direct injection (DI) fuels. 100 ppm of FeCl3 nanoadditive was blended with the DI fuels aimed at enhancing favourable fuel properties. The experimental investigations show a reduction of 54.17% and 50% in hydrocarbon (HC) and carbon monoxide (CO) emissions, respectively, in the case of WCO fuelled DI combustion compared with the diesel fuelled combustion. Significant increase in the cylinder pressure (pcyl) and the rate of heat release (ROHR) values was observed when the FeCl3 nanoadditive blended fuel was used. Also, with this type of fuel smoke emissions were reduced by 34.8%. Significant increase in the brake thermal efficiency (ηbth) with reduced nitrogen oxide (NOx) emissions was observed in the HCCI-DI combustion. Artificial neural network (ANN) was used for forecasting the performance of and emissions from the engine in different operating conditions. The technique for order preference by similarity to ideal solution (TOPSIS) was used for optimizing engine input parameters, which can result in maximum efficiency and minimum emissions

Evaluation of performance factors of FMS by combined decision making methods as AHP, CMBA and ELECTRE methodology

Present research is aimed to analyze the performance factors of flexible manufacturing systems by combined decision-making methodologies like analytical hierarchy process (AHP), combinatorial mathematics-based approach (CMBA) and improved ELECTRE. Six variables affecting the three factors of performance of flexible manufacturing systems viz. productivity, flexibility and quality are considered for the evaluation of performance factors. The weights of the attributes are calculated with AHP and the index score is calculated with CMBA methodology. CMBA methodology is the fusion of AHP and GTMA. ELECTRE approach has been used for the outranking of factors. The results show that productivity had the maximum impact on the performance of manufacturing systems. A high Spearman’s rank correlation also exists among the methods used

FAILURE MODE AND EFFECTS ANALYSIS OF SHIP SYSTEMS USING AN INTEGRATED DEMPSTER SHAFER THEORY AND ELECTRE METHOD

Failure Mode and Effects Analysis (FMEA) is a risk analysis tool which is used to define, identify, and eliminate known and/or potential failures from a system. The task is generally performed by team of experts. Each of the team of experts can express diverse opinions in rating of failure modes of systems which may be in the form of precise data and imprecise distribution ratings. However the RPN of FMEA is incapable of using these various forms of information in the prioritisation of risk of failure modes. This is one of the main limitations of FMEA. Furthermore the technique is limited to the use of three decision criteria thereby excluding other important decision criteria such as production loss in prioritising risk. To address these problems a novel FMEA tool is proposed which combines Dempster Shafer Theory with the ELECTRE method to provide a more efficient failure mode prioritisation method. With this technique the Dempster Shafer Theory is used in aggregating different failure mode ratings from experts and the ELECTRE method is applied in the ranking of failure modes. The applicability of the proposed technique is demonstrated with a case study of a marine diesel engine. Results showed that the proposed method can be applied in addressing risk prioritisation problem more efficiently than the FMEA and its variant

Barrier analysis approach in metal additive manufacturing implementation with environment consideration

Notwithstanding the developments in additive manufacturing technology have been set to overcome human limitations and improve efficiency in manual restoration activities, their widespread implementation as a disruptive production technology has brought various impacts on the environment, and the environmental assessment is limited in this regard. The Malaysian automotive industry has not seen widespread adoption of Life Cycle Assessment for additive manufacturing implementation. Based on the current literature review, there is a gap as the barriers for implementing Life Cycle Assessment in additive manufacturing technology within the Malaysian automotive manufacturing industry are not critically discussed. There is a need for developing appropriate approaches to weight and determine the interrelationships between these obstacles and the most prevalent ones in order to devise mitigation strategies for them. The purposes of this study are to identify various barriers of implementing Life Cycle Assessment in metal additive manufacturing within Malaysian automotive manufacturing industry and, secondly, to develop an approach to prioritize the barriers and recognize the most critical barriers. In this regard, the extant literature has critically reviewed the barriers of implementing Life Cycle Assessment in metal additive manufacturing within Malaysian automotive manufacturing industry. Fuzzy preference programming, as one of the newest and most accurate fuzzy modifications of the Analytical Hierarchy Process, was used to achieve the research purposes. Suitable Triangular Fuzzy Number has been defined and the selected data collection method was expert opinion. A total of eight industry experts from one company were involved in this research study to give their opinion on the Fuzzy Analytical Hierarchy Process pairwise comparison table. The expert opinions indicated that the main concern of industry is financial-related topic. The data collected have been analyzed using Fuzzy Analytical Hierarchy Process calculations and confirmed by the consistency check. Following the results, dominant barriers were accordingly identified and ranked in each category as well as overall. According to the results from expert opinions, the highest-ranking barrier is lack of financial resources, followed by lack of Life Cycle Assessment expertise in the additive manufacturing context, and the third rank is the lack of laws and directives for Life Cycle Assessment application in additive manufacturing. The findings may be useful to managers to develop suitable mitigation strategies and make more informed decisions with individual focus, level focus, or cluster focus. It may also contribute to the additive manufacturing literature by the weighted presentation of the barriers to implementing Life Cycle Assessment in additive manufacturing within the Malaysian automotive manufacturing industry. This study will contribute to a framework of roadmaps and strategies for sound and environmentally friendly additive manufacturing implementation in Malaysian automotive industry

Αξιολόγηση εκπαιδευτικών σεναρίων σε περιβάλλοντα ηλεκτρονικής μάθησης με τεχνικές εξόρυξης δεδομένων

O σχεδιασμός αποτελεί εκ φύσεως ένα πολύπλοκο και δύσκολο εγχείρημα και ιδιαίτερα όταν αναφέρεται στη μάθηση. Δεν είναι δυνατόν να ισχυριστούμε ότι σχεδιάζουμε τη μάθηση αλλά τις συνθήκες που μπορεί να οδηγήσουν έναν εκπαιδευόμενο στη μάθηση. Οι συνθήκες αυτές αποτυπώνονται σε αυτό που συνήθως ονομάζουμε εκπαιδευτικό σενάριο και περιλαμβάνουν την παροχή διαφόρων κινήτρων για μάθηση που ενεργοποιούνται μέσα από ένα σύνολο δραστηριοτήτων, οι οποίες κάνουν χρήση ποικίλων μαθησιακών πόρων και εκπαιδευτικών εργαλείων. Η διαδικασία της αξιολόγησης και του επανασχεδιασμού ενός εκπαιδευτικού σεναρίου απαιτεί την αξιολόγηση ποικίλων εναλλακτικών, που διαμορφώνονται από την συμπεριφορά που έδειξαν οι εμπλεκόμενοι κατά τη μαθησιακή διαδικασία. Σε μια τέτοια προσπάθεια ο εκπαιδευτικός - σχεδιαστής εκπαιδευτικών σεναρίων χρειάζεται ένα μεθοδολογικό και καλά οργανωμένο πλαίσιο, που να υποστηρίζεται από "έξυπνα" εργαλεία. Στη διατριβή αυτή παρουσιάζουμε ένα τέτοιο πρωτότυπο πλαίσιο στο πρόβλημα της αξιολόγησης εκπαιδευτικών σεναρίων σε περιβάλλον ηλεκτρονικής μάθησης, το οποίο έχει ως βασικό άξονα τις δομές προτιμήσεων των εκπαιδευομένων. Το πλαίσιο που προτείνουμε περιλαμβάνει τα παρακάτω στοιχεία: • Προσδιορίζει τις δομές προτίμησης των εκπαιδευόμενων εφαρμόζοντας μια νέα μέθοδο από την περιοχή της Πολυκριτήριας Ανάλυσης Αποφάσεων • Καταγράφει και αναλύει την συμπεριφορά των εκπαιδευόμενων σε τρεις διαστάσεις: (α) στη διάσταση της εμπλοκής τους με δραστηριότητες και πόρους του ηλεκτρονικού περιβάλλοντος, (β) στη διάσταση της επίδοσης που πέτυχαν (αφορά όλες τις δραστηριότητες που βαθμολογούνται με οποιονδήποτε τρόπο) και (γ) στη διάσταση της μαθησιακής εμπειρίας όπως την "εισέπραξαν" οι ίδιοι οι εκπαιδευόμενοι μέσα από τις δραστηριότητες και τους πόρους του περιβάλλοντος στο οποίο εκτέθηκαν. • Παρουσιάζει ένα πρωτότυπο εργαλείο που αναπτύξαμε για την ανάλυση της συμπεριφοράς των εκπαιδευόμενων με βάση συγκεκριμένους δείκτες εμπλοκής, το οποίο διευκολύνει την ανάλυση της συμπεριφοράς των ομάδων προτιμήσεων. Ο σχεδιαστής ενός εκπαιδευτικού σεναρίου μπορεί να αναλύσει την συμπεριφορά των ομάδων προτιμήσεων ξεκινώντας από τη διάσταση που επιθυμεί ανάλογα με τα ενδιαφέροντά του. Συνήθως, η ανάλυση εστιάζεται στη διάσταση της επίδοσης σε μια προσπάθεια εντοπισμού προβληματικών καταστάσεων, όπως είναι οι ομάδες προτίμησης που παρουσιάζουν χαμηλά ποσοστά επιτυχίας. Ο συνδυασμός των δεικτών επίδοσης με τους δείκτες εμπλοκής αλλά και ανατροφοδότησης από την μαθησιακή εμπειρία μπορεί να εντοπίσει πιθανά στοιχεία του εκπαιδευτικού σεναρίου που χρήζουν βελτίωσης. Γενικά, μπορούμε να πούμε ότι οι προβληματικές καταστάσεις εντοπίζονται σε εκείνα τα σημεία στα οποία οι αντίστοιχοι δείκτες παρουσιάζουν ακραίες τιμές. Όμως, ένας εκπαιδευτικός - σχεδιαστής μπορεί να εντοπίσει και καλές πρακτικές αναλύοντας σημεία στα οποία οι αντίστοιχοι δείκτες επιτρέπουν μια τέτοια προσέγγιση στην συμπεριφορά των ομάδων αυτών που τις πέτυχαν. Για παράδειγμα, μελετώντας την συμπεριφορά μιας ομάδας που πέτυχε υψηλές τιμές στη διάσταση της επίδοσης μπορεί να αποκαλύψει καλές πρακτικές χρήσιμες και στις άλλες ομάδες. Στη διατριβή παρουσιάζεται επίσης και μια πιλοτική εφαρμογή της προσέγγισής μας σε ένα πραγματικό μάθημα του Ανώτατου Εκπαιδευτικού Ιδρύματος Πειραιά Τεχνολογικού Τομέα με πολλά υποσχόμενα αποτελέσματα. Το να προσαρμόσουμε και να αποδώσουμε στην εκπαίδευση μια μαθητο-κεντρική και προσωποποιημένη διάσταση, δεν αποτελεί εύκολη υπόθεση. Το πλαίσιο που παρουσιάζουμε παρέχει μια ολιστική και πλήρως μαθητο-κεντρική προσέγγιση στη διαδικασία επανασχεδιασμού ενός ηλεκτρονικού μαθήματος και μπορεί να χρησιμοποιηθεί σε διάφορα επίπεδα, από μια μικρή μαθησιακή ενότητα έως ένα ολόκληρο πρόγραμμα σπουδών.Design, by its nature is a difficult and complex task especially when it concerns learning. It is not possible to claim that we design learning, but only the conditions that can guide and help a student to learn. These conditions are imprinted to what we usually call educational scenario and include the provision of various motives that are activated through a set of activities, which utilize various learning resources and educational tools. The procedure of the evaluation and redesign of an educational scenario demands the assessment of various alternatives, which are determined by the behavior that is displayed by those involved in the learning process. In such effort, the educator-designer of the educational scenario needs a methodological and well-organized framework that is supported by "smart" tools. In this dissertation we present an original framework for the problem of the evaluation of educational scenarios in e-learning environments that has as its fundamental keystone the structures of preference of the learner. The proposed framework includes the following elements: It identifies the learner's structures of preference by applying a new method from the domain of Multicriteria Decision Making. It records and analyses the learners' behavior in three dimensions: a) the dimension of their involvement with the activities and the resources in the e-learning environment, b) the dimension of their achieved performance (which refers to all the activities that can be graded in any way), and c) the dimension of their learning experience as it was "cashed out" by the learners through the activities and the resources in the learning environment that they were exposed. It presents an prototype tool that was developed for the analysis of the learners' behavior based on specific engagement indices, which facilitates the analysis of the behavior of groups of preferences. The designer of an educational scenario can analyze the behavior of groups of preferences initiating the analysis from the desired dimension, according to his/hers interests. Usually, the analysis focuses on the dimension of the performance in an effort to identify problematic situations, such as groups of preferences with low succession rates. The correlation of the performance indicators with the indices for the engagement and the feedback acquired regarding the learning experience, can pin point potential elements of the educational scenario that require improvement. In general, we can say that problematic situations are located in those points that the corresponding indices present extremely low values. However, the designer-educator can also identify good practices by analyzing the points that the indices allow such an approach with respect to the behavior of the groups. For example, studying the behavior of a group of students that achieved high values in the dimension of the performance can reveal good practices that can be proven useful to other groups as well. In this dissertation is also presented with promising results, a pilot application of our approach on a real course of the Piraeus Technological Education Institute. Adapting and at the same time attributing education with a learner-centered and personalized dimension is not an easy task. The framework we present provides a holistic and fully learner-centered approach for the redesign process of an e-learning course and can be used in various levels, from a small learning unit to a whole curriculum