Kevin L. Edwards

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.

Biocomposites for Hard Tissue Replacement and Repair

Biomaterials with single composition suffer from shortcomings limiting their lifetime and sometimes restricting their applications. Therefore, biocomposites have been started to develop by combining two or more biomaterials with different characteristics to provide superior properties compared to each biomaterial alone. These materials can be flexibly tailored to provide material properties fitted with a given application. In their way to be designed, the principles exist in human body tissues that can be used as a guide. This helps in providing biomimetic materials. Over the recent past decades, research on composite materials for biomedical applications has been progressively increased. A large number of composites, therefore, have been developed and tested for hard tissue replacements and repair. This includes total joint replacements, devices used for fractured bone treatment, dental restorative materials, dental implants, and bone scaffolds. This chapter provides information on permanent and temporary implants and the essential material requirements for their applications. Furthermore, it specifically explains different types of composite biomaterials used in hard tissue replacements and repair. However, this chapter does not include ancillary implants or fasteners used to treat fractured bone.

Evaluating promising applications of a new nanomaterial produced by accumulative roll bonding process: A preliminary multiple criteria decision-making approach

Although many new materials are developed in laboratories, most of them do not get commercialized. The ranking of applications gives material engineers a better understanding of the advantages and disadvantages of any new or improved material under development. This is possible through simultaneously considering different technical, economic, and environmental criteria. It also helps to guide future research on developing new materials and identify the requirements that any new material must fulfill for the most fitting applications. The appropriateness of the proposed approach for evaluating promising applications of a new material is demonstrated using a case study in nanostructured Al/Al2O3 metal matrix composite produced via the accumulative roll bonding process. Al/Al2O3 metal matrix composite provides superior mechanical and physical properties and accumulative roll bonding is a severe plastic deformation process that can be applied to the continuous production of bulky sheet materials. The material is in growing use and becoming indispensable in several key industrial sectors such as aerospace, automobile, marine, and defense, and the enhanced properties created by accumulative roll bonding will only increase its potential. The innovative approach described in this paper will be of interest to academic researchers and practitioners involved in new materials, processing, and product development.

Case studies of materials selection and design

Ten detailed practical examples, or case studies, have been chosen to explain and impart a better understanding of the methods described in the previous chapters. The first example describes the problem of selecting materials for a hip joint prosthesis, which includes target criteria. The process of obtaining three types of weightings, ranking with comprehensive VIKOR and extended TOPSIS methods, and the aggregation process for optimal materials selection has been exhibited in this example. The second example, which includes the target value of criteria as well as interval data in some criteria, describes the problem of selecting materials for the femoral component of a total knee replacement. The third to fifth examples are all related to materials selection and design of knee prostheses. The third example is the design and multi-objective optimization of a functionally graded material for the femoral component of knee prosthesis. The fourth example deals with materials selection and design optimization problem, and the fifth example is a simultaneous material and design selection problem, while demonstrating the role of quality function deployment (QFD) in design decision-making. The sixth example is a typical engineering problem, selecting materials using interval data, in this case to repair aircraft structures. The seventh example uses a mechanical turnbuckle assembly to introduce the concept of multiple component materials selection. In addition, it tries to reveal cost uncertainty in the early stages of the design process. The eighth example explains the place of multiple attribute decision-making (MADM) in the lightweight design of a thin-walled tube for the energy absorption structure in a motorcar. A strategy for decision-making, in the presence of a difference between physical and simulation experiments, is also highlighted in this example. The ninth example describes the use of fuzzy MADM when selecting materials for a motorcar dashboard. The last example discusses selecting hard coating materials to resist wear.

Materials selection in the context of design problem-solving

Satisfying consumers in all expected quality dimensions is the major challenge in product design. In the integrated chain of actions for developing new, or improving existing products, creativity is considered to be essential. The process of selecting the best material to fulfill the desired requirements deals with a lot of trade-offs. An increased requirement for the production of high-quality products implies the need to use modern approaches for modeling and analyzing customer expectations as well as contemporary computing facilities for supporting decision-making about the selection of materials, processing and design. Applying lean design principles in the material design/selection phase can help in better translating the customer’s requirements, cost saving goals, faster time-to-market, increasing quality, and innovating industries.

Multiple objective decision-making for material and geometry design

During the design process for a product, materials are either selected or designed to meet the desired requirements. In material selection the outcome is that typically the ideal solution is not always chosen. Also, because of the conflicting nature of materials characteristics, improvement of material properties usually does not meet the expected requirements, hence material design benefits from multi-objective optimization. However, despite the complexity, the final product can benefit from simultaneous material and structural optimization.

Multi-criteria decision-making for materials selection

Designing mostly involves complex problem-solving and the need to consider many different options. Design support tools facilitate the process of obtaining optimum solutions such as the most appropriate choice of material for the component of a product. Multi-criteria decision-making (MCDM) methods are useful when multi-criteria need to be considered simultaneously. MCDM can be further categorized as multi-objective decision-making, usually appropriate for design problems, and multi-attribute decision-making that typically fits better to materials selection problems. The strategic combination of materials science and computational modeling and analysis plays a key role in evaluating the performance metrics necessary to support materials selection and design.

Case Studies of Using Materials Ranking

Three practical examples have been chosen to explain and impart a better understanding of the methods described in the previous chapter. The first example describes the problem of selecting materials for a hip joint prosthesis, which includes target criteria. The process of obtaining three types of weightings, ranking with comprehensive VIKOR and extended TOPSIS approaches, and the aggregation process for optimal materials selection has been exhibited in this example. The second example, which includes the target value of criteria as well as interval data in some criteria, describes the problem of selecting materials for the femoral component of a total knee replacement. The example helps to elaborate and demonstrate the application of the extended model on a technically challenging problem. The third example is a typical engineering problem, selecting aircraft repair materials with interval data. The last example has also been used to confirm the importance of interval data in ranking of materials.