Development of a fuzzy FMEA based product design system

Chin, Kwai‐Sang; Chan, A.M.M.; Yang, Jian

doi:10.1007/s00170-006-0898-3

Cited by 162 publications

(91 citation statements)

References 44 publications

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“…2) Same magnitude of RPNs can be obtained from different combinations of occurrence (O), severity (S) and detection (D), in which their hidden risk implications may be totally different (Chin et al, 2008;Wang et al, 2009); 3) Sensitivity to small changes means that a small change in one factor has a much larger effect when the other factors are larger compared with when they are small (e.g., RPN on 9×9×3 = 243 and on 9×9×4 = 324; RPN in 3×4×3 = 36 and on 3×4×4 = 48); 4) Inadequate scaling of the ratios on occurrence table is not proportional or linear; 5) Other important factors are ignored, such as economic aspects (von Ahsen, 2008;Chin et al, 2009); 6) Risk evaluation using RPN cannot always be assessed by detection (D) (Segismundo and Miguel, 2008); and 7) No exact rule is given to determine the probability of occurrence (O) and detection (D) (Segismundo and Miguel, 2008).…”

Section: Discussionmentioning

confidence: 99%

“…Therefore, the development of "InfoSec FMEA Circle" can provide solutions to overcome the above insufficiencies of FMEA stated by different scholars (Chin et al, 2008Wang et al, 2009;von Ahsen, 2008;Segismundo and Miguel, 2008; BS EN 60812:2006):…”

Section: Discussionmentioning

confidence: 99%

“…The development of "Information Security FMEA Circle" can provide solutions to overcome the insufficiencies of FMEA stated by different scholars (Chin et al, 2008Wang et al, 2009;von Ahsen, 2008;Segismundo and Miguel, 2008;IEC 60812:2006) below: 1) The proposed FMEA-based risk assessment sets the risk acceptable level below or at the score of 100 (that is 10% of the maxima score of 1000). Even though RPN is heavily distributed at the bottom (say below 100), the Information Asset Classification shall also be considered.…”

Section: Development Of a Failurementioning

confidence: 99%

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Development of a Failure Mode and Effects Analysis Based Risk Assessment Tool for Information Security

Lai¹,

Chin²

2014

Industrial Engineering and Management Systems

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Risk management is recognized as a significant element in Information Security Management while the failure mode and effects analysis (FMEA) is widely used in risk analysis in manufacturing industry. This paper aims to present the development work of the Information Security FMEA Circle (InfoSec FMEA Circle) which is used to support the risk management framework by modifying traditional FMEA methodologies. In order to demonstrate the "appropriateness" of the InfoSec FMEA Circle for the purposes of assessing information security, a case study at Hong Kong Science and Technology Parks Corporation (HKSTP) is employed. The "InfoSec FMEA Circle" is found to be an effective risk assessment methodology that has a significant contribution to providing a stepwise risk management implementation model for information security management.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Development Of a Failurementioning

confidence: 99%

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Development of a Failure Mode and Effects Analysis Based Risk Assessment Tool for Information Security

Lai¹,

Chin²

2014

Industrial Engineering and Management Systems

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“…Failure mode refers to a form of system failure or system malfunction and effects analysis is used to research the impact on the total system when a local system is unable to work [5]. The main purpose of FMEA is to define, identify, and eliminate potential failure or problems in different products, designs, systems, and services [6,7]. FMEA not only can provide a basis to help designers improve or upgrade their scheme to reduce the loss but also can help decision makers to formulate corresponding preventive measures or improve the emergency response capability [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Risk Evaluation in Failure Mode and Effects Analysis Using Fuzzy Measure and Fuzzy Integral

2017

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Failure mode and effects analysis (FMEA) is a popular and useful approach applied to examine potential failures in different products, designs, processes, and services. As a vital index, the risk priority number (RPN) can determine the risk priorities of failure modes by some risk factors such as occurrence (O), severity (S), and detection (D). However, in FMEA, the traditional risk priority number approach has some shortcomings, especially in setting the weight of risk factors. This paper presents an improved risk priority number approach based on a fuzzy measure and fuzzy integral. A fuzzy measure is used to reflect the importance of the individual indicators and the indicator set and a fuzzy integral is a nonlinear function defined on the basis of fuzzy measure. The weights of risk factors given by domain experts are seen as fuzzy densities to generate a λ-fuzzy measure which can reflect the weights' difference and relevance about risk factors. Then, the Choquet integral is used to fuse every value of risk factors about failure modes so as to obtain the comprehensive evaluation result. The result can reflect the comprehensive risk level, so it has a definite physical significance. Finally, an illustrative example and a comparison with another approach are given to show the effectiveness of the proposed approach in the paper.

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“…past experience of similar products, judgments of expert) [25]. In turn, Chin [10] presents the use of information acquired from customers (needs, requirements) and company (business goals, resources and constraints) in the stage of concepts evaluation, and in the context of product, process, time, and cost. These approaches use information from enterprise and its environment to assess product reliability and product development cost that can be specified in the form of variables and constraints.…”

Section: Introductionmentioning

confidence: 99%

Portfolio selection of new product projects: a product reliability perspective

Relich¹

2016

EiN

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Article citation info: (*) Tekst artykułu w polskiej wersji językowej dostępny w elektronicznym wydaniu kwartalnika na stronie www.ein.org.pl IntroductionNew product development (NPD) and its launch is one of the most important business processes in contemporary enterprises. Dynamic development of technology, increasing customer requirements and growth of global competition result in a reduction of product life cycle [8,11]. Product complexity and limited resources (e.g. financial, personal) hinder quick development of innovative products. Therefore, companies often modernise existing products to develop a new product according to changing customer requirements [8,31]. Modernisation of an existing product reduces time, cost and risk compared with designing a new product from scratch [13,15,28]. A faster launch of a new product can ensure company an advantage over competitors. However, a reduction of product design time often leads to the decrease of product reliability, and consequently, increases the warranty cost in the post-sale phase. Moreover, a decline of customers' loyalty due to unsatisfactory product quality can decrease future sales and profits. On the other hand, the greater expenses for improving product quality usually lead to increasing product price, what is also adversely perceived by customers. Hence, there is a need to develop a system approach to ensure the desired product reliability from the viewpoint of entire business, and from the stage of selecting portfolio of new product development projects.Product reliability is defined as the ability of a product to perform required functions, under given environment and operational conditions and for a stated period of time [22]. Product reliability is widely considered in the literature from an engineering perspective (e.g. determining stress-strain models of materials in the stage of testing a new product) that aims to improve durability of a product and ensure reliability-related standards [7,12]. Product reliability is less often considered in a system approach that includes all stages of product life cycle and aligns reliability with business goals such as customer satisfaction, sale/profit growth, and a reduction of development, production and warranty costs.Murthy [22] proposes a decision support system for determining parameters of product reliability based on development cost model, warranty cost model, and reliability and usage models. There is considered product reliability in the context of three levels (business, product and component), and three stages (pre-development, development, and post-development). In turn, Kumar [19] presents a knowledge based reliability engineering approach to manage product safety that takes into account manufacturing process of a new product and business environment (customer requirements, quality of materials purchased from suppliers). These studies consider product reliability from the perspective of a system approach, however, they do not Relich M. Portfolio selection of new product projects: a product ...

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Development of a fuzzy FMEA based product design system

Cited by 162 publications

References 44 publications

Development of a Failure Mode and Effects Analysis Based Risk Assessment Tool for Information Security

Development of a Failure Mode and Effects Analysis Based Risk Assessment Tool for Information Security

Risk Evaluation in Failure Mode and Effects Analysis Using Fuzzy Measure and Fuzzy Integral

Portfolio selection of new product projects: a product reliability perspective

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