Ali Jahan

An Approach for Web Service Selection Based on Confidence Level of Decision Maker

Web services today are among the most widely used groups for Service Oriented Architecture (SOA). Service selection is one of the most significant current discussions in SOA, which evaluates discovered services and chooses the best candidate from them. Although a majority of service selection techniques apply Quality of Service (QoS), the behaviour of QoS-based service selection leads to service selection problems in Multi-Criteria Decision Making (MCDM). In the existing works, the confidence level of decision makers is neglected and does not consider their expertise in assessing Web services. In this paper, we employ the VIKOR (VIšekriterijumskoKOmpromisnoRangiranje) method, which is absent in the literature for service selection, but is well-known in other research. We propose a QoS-based approach that deals with service selection by applying VIKOR with improvement of features. This research determines the weights of criteria based on user preference and accounts for the confidence level of decision makers. The proposed approach is illustrated by an example in order to demonstrate and validate the model. The results of this research may facilitate service consumers to attain a more efficient decision when selecting the appropriate service.

Multicriteria Decision Analysis in Improving Quality of Design in Femoral Component of Knee Prostheses: Influence of Interface Geometry and Material

Knee prostheses as medical products require careful application of quality and design tool to ensure the best performance. Therefore, quality function deployment (QFD) was proposed as a quality tool to systematically integrate consumer’s expectation to perceived needs by medical and design team and to explicitly address the translation of customer needs into engineering characteristics. In this study, full factorial design of experiment (DOE) method was accompanied by finite element analysis (FEA) to evaluate the effect of inner contours of femoral component on mechanical stability of the implant and biomechanical stresses within the implant components and adjacent bone areas with preservation of the outer contours for standard Co-Cr alloy and a promising functionally graded material (FGM). The ANOVA revealed that the inner shape of femoral component influenced the performance measures in which the angle between the distal and anterior cuts and the angle between the distal and posterior cuts were greatly influential. In the final ranking of alternatives, using multicriteria decision analysis (MCDA), the designs with FGM was ranked first over the Co-Cr femoral component, but the original design with Co-Cr material was not the best choice femoral component, among the top ranked design with the same material.

Using Design of Experiments Methods for Assessing Peak Contact Pressure to Material Properties of Soft Tissue in Human Knee

Contact pressure in the knee joint is a key element in the mechanisms of knee pain and osteoarthritis. Assessing the contact pressure in tibiofemoral joint is a challenging mechanical problem due to uncertainty in material properties. In this study, a sensitivity analysis of tibiofemoral peak contact pressure to the material properties of the soft tissue was carried out through fractional factorial and Box-Behnken designs. The cartilage was modeled as linear elastic material, and in addition to its elastic modulus, interaction effects of soft tissue material properties were added compared to previous research. The results indicated that elastic modulus of the cartilage is the most effective factor. Interaction effects of axial/radial modulus with elastic modulus of cartilage, circumferential and axial/radial moduli of meniscus were other influential factors. Furthermore this study showed how design of experiment methods can help designers to reduce the number of finite element analyses and to better interpret the results.

The Importance of Decision Support in Materials Selection

The selection of materials at all stages of the product design process requires effective decision-making. The nature of the problem is both complex and varying from having to consider a large number of available materials and vague information in the early design stages to a small number of acceptable materials and detailed information in the later design stages. The inclusion of hybrid materials and newly developed materials although offering the potential of enhanced performance can further exacerbate the problem. To fully satisfy the design requirements, decision-making support is essential to correctly select the most appropriate design, materials, and manufacturing processes in the design and development of new engineering products.

Screening of Materials

The screening methods available for materials selection range from simple manual procedures to sophisticated computer-based packages, as either stand-alone, or linked to materials’ properties databases, or integrated with other design support tools. Of all the current methods available, the most popular way of screening materials is via the use of materials selection charts (the so-called “Ashby” method). The charts allow a direct comparison to be easily made between different material properties, or a limited combination of material properties, via the use of performance indices. Multi-criteria decision-making techniques can also be applied when a large number of materials’ selection criteria need to be considered simultaneously.

Multi-attribute decision-making for ranking of candidate materials

Multi-Attribute Decision-Making methods have become accepted for determining the choice of materials when the “lowest price” approach does not realize the optimum result. These methods are especially useful for high technology markets, where product differentiation and competitive advantage are often achievable with just small gains in material performance. The strategy of applying objective and subjective weightings for all types of criteria is described in materials selection as well as a method to incorporate them. The whole process for optimal decision-making in materials selection includes selecting the proper ranking method, as well as the aggregation method for situations when there are a lot of similar alternatives. As a result, a systematic approach to optimal materials selection is explained that will be beneficial to materials engineers and designers.

Chapter 2 – Screening of Materials

When selecting materials, formalized screening methods help to narrow down the choice of materials to a more manageable number for subsequent detailed evaluation. The screening methods available range from manual to computer-based packages as either stand alone or linked to materials’ properties databases or integrated with other design support tools. Of all the current methods available, the most popular way of screening materials is via the use of materials selection charts (“Ashby” method). The charts allow a direct comparison to be easily made of different material properties or a limited combination of material properties via the use of performance indices. Multi-criteria decision-making techniques can be applied when a large number of materials selection criteria need to be considered simultaneously. The selection of materials derived from the charts is normally left quite broad to initially keep options open and narrowed down as the design develops.

ELECTRE-IDAT for design decision-making problems with interval data and target-based criteria

A majority of decision-making problems are accompanied by some kinds of predictions and uncertainties. Therefore, interval data are widely used instead of exact data. The elimination and choice expressing reality methods, referred to as ELECTRE, belong to the outranking methods. Despite their relative complexity, avoiding compensation between criteria is one of the main advantages of the ELECTRE methods. However, no version of ELECTRE methods has the capability to deal with both interval data and target-based criteria. Target-based criteria are applicable in many areas ranging from material selection to medical decision-making problems. Efficiency of the modified ELECTRE method (ELECTRE-IDAT) was examined through two challenging examples. Also, a sensitivity analysis was performed to show advantages of the ELECTRE-IDAT approach. Additionally, the concept of bounded criteria was explained and applicability of interval data as well as benefit, cost, and target criteria were described with a biomaterial selection problem.

Developing WASPAS-RTB method for range target-based criteria: toward selection for robust design

Recently, considerable attention has been devoted to application of multi-attribute decision-making (MADM) method in materials selection. Normalization can be considered as a foundation for rational MADM methods, which should deal with target-based criteria in addition to cost and benefit criteria. Although a good number of applications have been reported for point target criteria in MADM problems, in selection problems related to engineering design, it might be better to let the material and design criteria vary over a range in order to increase flexibility in subsequent design stages. The mentioned point supports a readily adaptable design in changing the customer requirements, which is also significant in offering a robust design. In this research, performance of three promising target-based normalization methods was investigated using simulation experiments to examine the effect of simulation parameters. The effect of parameters and normalization methods was examined using analysis of variance (ANOVA). Moreover, the best structure formula was identified to propose an inclusive range target-based normalization method. The suggested normalization method was used to enhance the capability of Weighted Aggregated Sum Product Assessment (WASPAS) method and applied to a real-word problem dealing with benefit-, cost-, and point target-based criteria as well as the range criterion.

Selection of Optimal Aluminum-Based Composite Produced by Powder Metallurgy Process in Uncertain Environment

Powder metallurgy is one of the important processes in the production of aluminum composites, whose design is governed by optimal reinforcing properties such as type, volume fraction, and particle size. Given the variety of reinforcements in aluminum composites and different expected properties, Multi-Attributes Decision-Making (MADM) methods can be employed to find the best feasible option. The objective of the present study is to select an appropriate type of reinforcement in aluminum matrix composites (AA6061), made through mechanical milling and powder metallurgy processes. In this research, a combinative decision-making process including interval TOPSIS and fuzzy group weighing approaches was used for the selection of aluminum-based composite reinforced (for structural applications) by aluminum nitride, silicon nitride, zirconium boride, and carbon nanotubes, all of which have high tensile strength, elastic modulus and hardness, lightweight, and low cost. Integrated MADM method demonstrated that the silicon nitride is the optimal alternative for structural applications in such types of composite. The sensitivity analysis further indicated that the change in the weights of attributes did not change the preferred option order (silicon nitride), rather influencing the ranking orders of the second and third alternatives.