A risk-based decision model proposal in the evaluation of metallic biomaterials

Metallic biomaterials are widely used in orthopedic applications. The main role of these biomaterials in orthopedic surgery is to restore bone and joint functions and to eliminate an existing pain. For the long-term effectiveness of metallic biomaterials in the human body, metals need to have desired properties such as high corrosion resistance, tensile strength, and wear resistance. Metallic biomaterials have significant effects on various aspects such as human health, medical treatments, and quality of life. The success and risk reduction/prevention in biomedical applications are linked to the examination of material properties. Due to the unique properties of metallic biomaterials and the aggressive and sensitive nature of the biological environment they are exposed to, it has become important to evaluate and select these materials correctly. Biomaterials should be economically reasonable and their development should be supported for long-term service. Additionally, the consideration of design and production requirements is important in the material selection process. On the other hand, materials possess different combinations of physical, mechanical, chemical, and biological properties. Hence, the metallic biomaterial examination problem necessitates the simultaneous consideration of multiple criteria. In the biomaterial evaluation process, similar to other decision-making areas, some problems and risks may arise. In this context, making informed and accurate decisions requires a risk analysis. The failure modes and effects analysis (FMEA) is one of the most widely adopted and effective methods among risk analysis tools. The FMEA method can be utilized to assess and prevent potential failures and challenges. The FMEA calculates risk priority coefficients by multiplying the values of three risk factors (severity, occurrence, and detectability) to prioritize decision elements. However, the classical FMEA method has faced criticism due to some limitations. It is commonly acknowledged that all risk factors carry equal importance. The use of discrete ordinal scales in calculating risk priority numbers leads to a large number of intervals between these coefficients. Additionally, the assessment of risk levels for decision elements based on risk factors relies on precise numerical judgments. Nevertheless, obtaining exact numerical values can be challenging, and at times even impossible, in many applications due to problem complexity, limitations of human thinking, subjectivity, and data constraints. The multicriteria decision-making technique and fuzzy set theory can be integrated into the FMEA to provide more effective risk assessment and management. In this study, stainless steel, titanium, and cobalt-chromium alloys, which fall within the category of metallic biomaterials, are examined using a decision-making approach that integrates the interval type-2 fuzzy analytical hierarchy process (AHP), the interval type-2 fuzzy FMEA, and the interval type-2 fuzzy evaluation based on distance from an average solution (EDAS). Based on the literature review and expert opinions, six main criteria, thirty-one subcriteria, and three risk factors are identified. The risk factors considered in the study are severity, occurence, and detectability. The material properties are finalized under six groups: (i) economic properties, (ii) design and production properties, (iii) mechanical properties, (iv) physical properties, (v) chemical properties, and (vi) biological properties. The subcriteria of economic properties are identified as funding trend for research, development, and application, longevity, cost, and availability. The subcriteria of design and production properties are determined as ease of production, lightness, machinability, sterilizability, formability, and compatibility. The subcriteria of mechanical properties are specified as wear resistance, fatigue resistance, tensile strength, toughness, hardness, and time-dependent deformation. The subcriteria of physical properties are identified as density, dimensional stability, conductivity, and magnetic susceptibility. The subcriteria of chemical properties are defined as ion release, corrosion resistance, reactivity, biodegradation, and pH changes. Lastly, the subcriteria of biological properties are determined as osseointegration, allergenic effect, infection, toxicity, calcification, and carcinogenicity. While the interval type-2 fuzzy AHP reveals the criterion and factor weights, the risk priority coefficients provided by the interval type-2 fuzzy FMEA are analyzed via the interval type-2 fuzzy EDAS. In the biomaterial evaluation process, many experts are asked to complete a questionnaire consisting of the following items: (i) what is the severity of each material property in relation to human health, medical treatments, and quality of life after an undesired event occurs?, (ii) what is the probability of a failure or risk occurring?, and (iii) how easy is it to detect a failure or risk before it happens?. The experts provides judgments based on their personal knowledge and expertise. The ranking order obtained for the risk factors is as follows: severity > detectability > occurence. According to the importance weights obtained for the main criteria, the highest priority group is biological properties. Furthermore, the subcriteria possessing the highest local importance are: cost in the economic properties group, compatibility in the design and production properties group, tensile strength in the mechanical properties group, dimensional stability in the physical properties group, corrosion resistance in the chemical properties group, and infection in the biological properties group. According to the global importance weights, infection, carcinogenicity, and tensile strength are the top priority decision criteria. Therefore, in biomaterial evaluation and selection, more importance should be given to these decision criteria. The priority order of the materials is titanium > stainless steel > cobalt-chromium alloys. Based on this ranking result, it can be said that titanium is the best material option. This study presents a comprehensive framework and a risk-based decision-making approach for the examination of metallic biomaterials. The proposed approach considers the risks associated with the decision-making process. By doing so, it provides a structured framework that facilitates effective decision-making, even in the face of uncertainties. Moreover, it offers an alternative and well-defined framework specifically tailored for ranking decision elements. The key strength of this approach lies in its ability to enable comparisons through the utilization of a risk decision matrix. This matrix allows for a comprehensive evaluation of various options by enabling a thorough assessment of their associated risks. By incorporating the risk analysis into the decision-making process, this study addresses a crucial aspect of biomaterial examination. This ensures that decision-makers have a holistic understanding of the potential risks associated with each option and enables them to make informed choices. As a result, the current study provides a roadmap for making informed and effective decisions in the evaluation and selection of various alternatives.