Medical product development (MPD) process is highly multidisciplinary in nature, which increases the complexity and the associated risks. Managing the risks during MPD process is very crucial. The objective of this research is to explore risks during MPD in a dental product manufacturing company and propose a model for risk mitigation during MPD process to minimize failure events. A case study approach is employed. The existing MPD process is mapped with five phases of the customized phase gate process. The activities during each phase of development and risks associated with each activity are identified and categorized based on the source of occurrence. The risks are analyzed using traditional Failure mode and effect analysis (FMEA) and fuzzy FMEA. The results of two methods when compared show that fuzzy approach avoids the duplication of RPNs and helps more to convert cognition of experts into information to get values of risk factors. The critical, moderate, low level and negligible risks are identified based on criticality; risk treatments and mitigation model are proposed. During initial phases of MPD, the risks are less severe, but as the process progresses the severity of risks goes on increasing. The MPD process should be critically designed and simulated to minimize the number of risk events and their severity. To successfully develop the products/devices within the manufacturing companies, the process risk management is very essential. A systematic approach to manage risks during MPD process will lead to the development of medical products with expected quality and reliability. This is the first research of its kind having focus on MPD process risks and its management. The methodology adopted in this paper will help the developers, managers and researchers to have a competitive edge over the other companies by managing the risks during the development process.

Purpose The purpose of this paper is to outline and prioritizes risk sources in medical device development (MDD) process using an integrated “structural equation modeling” (SEM) and fuzzy “technique for order performance by similarity to ideal solution (TOPSIS)” framework. Design/methodology/approach Risk sources which deter MDD process are explored through literature review. Initial structural model is proposed, factor loadings are determined by exploratory factor analysis and model fit is established by confirmatory factor analysis. Further, the sources are ranked using FTOPSIS, and sensitivity analysis is carried to check robustness of results. Findings The sources of risks have catastrophic effect on MDD process. The initial SEM model developed based on survey of experts is found reliable and valid which breaks up the risk sources into three categories – internal sources of risks, user-related sources of risks and third-party-related sources of risks. The risk sources are ranked and prioritized based on perspective of experts from the categories using FTOPSIS; unmet user needs/requirements is found as the most important source of risk. Results of sensitivity analysis confirm that the factors are relatively less sensitive to criteria weights confirming reliability of initial solution. Research limitations/implications The proposed methodology combines qualitative and quantative approaches, making it little complex and lengthy, but results in dual confirmation. Practical implications The outcomes of this research will be of prime use for MDD industries to mitigate risk sources. It will help to increase the success rate of MDD. Originality/value Integrated SEM-FTOPSIS provides a unique and effective structural modeling-based decision support tool. The framework can be effectively utilized in other domains, and failure events of medical devices can be potentially controlled by applying risk mitigation measures.

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Efficacious product development is a critical issue faced by medical device manufacturing industries. Indian medical device industry is in nascent stage constituting of 75 % imports indicating diminutive device development activities unlike other sectors of manufacturing which are vigorously making forays through indigenous product development. The objective of this paper is to identify barriers to medical device development (MDD) and develop a structural model of it. 11 most significant barriers are identified using opinions of MDD experts and the literature review. They are further ranked by 33 experts through questionnaire survey. The mutual relationships among the barriers are established based on opinions of one group of experts using interpretive structural modelling (ISM) approach. The barriers are quantified using reachability matrix and further categorised as: autonomous, dependent, linkage and driver barriers using MICMAC analysis based on the mutual influence and dependence. The model is further validated by another group of MDD experts. Combination of ISM and MIC-MAC analysis gives a high level contextual relationship among the barriers identified. The barriers have compounding effect. Dependent barriers have higher dependence and present resulting actions. The driver barriers have high driving power and low dependence indicating need for systematic plan of action. Identification of barriers to MDD and developing the contextual relationships among them is a unique effort. It will provide an aid to the top management, developers and policy makers to develop strategies for MDD. Moreover, it will assist to accelerate indigenous contribution towards MDD which will ultimately deepen the penetration of low cost and better quality medical care for larger part of the population. This paper develops a model of barriers to MDD in India; which can be customised for other sectors and contexts.

Purpose Successful device development brings substantial revenues to medical device manufacturing industries. This paper aims to evaluate factors contributing to the success of medical device development (MDD) using grey DEMATEL (decision-making trial and evaluation laboratory) methodology through an empirical case study. Design/methodology/approach The factors are identified through literature review and industry experts’ opinions. Grey-based DEMATEL methodology is used to establish the cause-effect relationship among the factors and develop a structured model. Most significant factors contributing to the success of MDD are identified. An empirical case study of an MDD and manufacturing organisation is presented to demonstrate the use of the grey DEMATEL method. Sensitivity analysis is carried out to check robustness of results. Findings The results of applying the grey DEMATEL methodology to evaluate success factors of MDD show that availability of experts and their experience (SF4) is the most prominent cause factor, and active involvement of stakeholders during all stages of MDD (SF3) and complete elicitation of end-user requirements (SF1) are the most prominent effect factors for successful MDD. A sensitivity analysis confirms the reliability of the initial solution. Practical implications The findings will greatly help medical device manufacturers to understand the success factors and develop strategies to conduct successful MDD processes. Originality/value In the past, few success factors to MDD have been identified by some researchers, but complex inter-relationships among factors are not analysed. Finding direct and indirect effects of these factors on the success of MDD can be a good future research proposition.