Daniel Osezua Aikhuele

Intuitionistic fuzzy-based model for failure detection

In identifying to-be-improved product component(s), the customer/user requirements which are mainly considered, and achieved through customer surveys using the quality function deployment (QFD) tool, often fail to guarantee or cover aspects of the product reliability. Even when they do, there are always many misunderstandings. To improve the product reliability and quality during product redesigning phase and to create that novel product(s) for the customers, the failure information of the existing product, and its component(s) should ordinarily be analyzed and converted to appropriate design knowledge for the design engineer. In this paper, a new intuitionistic fuzzy multi-criteria decision-making method has been proposed. The new approach which is based on an intuitionistic fuzzy TOPSIS model uses an exponential-related function for the computation of the separation measures from the intuitionistic fuzzy positive ideal solution (IFPIS) and intuitionistic fuzzy negative ideal solution (IFNIS) of alternatives. The proposed method has been applied to two practical case studies, and the result from the different cases has been compared with some similar computational approaches in the literature.

Proposal for a Conceptual Model for Evaluating Lean Product Development Performance: A Study of LPD Enablers in Manufacturing Companies

The instability in todays market and the emerging demands for mass customized products by customers, are driving companies to seek for cost effective and time efficient improvements in their production system and this have led to real pressure for the adaptation of new developmental architecture and operational parameters to remain competitive in the market. Among such developmental architecture adopted, is the integration of lean thinking in the product development process. However, due to lack of clear understanding of the lean performance and its measurements, many companies are unable to implement and fully integrate the lean principle into their product development process and without a proper performance measurement, the performance level of the organizational value stream will be unknown and the specific area of improvement as it relates to the LPD program cannot be tracked. Hence, it will result in poor decision making in the LPD implementation. This paper therefore seeks to present a conceptual model for evaluation of LPD performances by identifying and analysing the core existing LPD enabler (Chief Engineer, Cross-functional teams, Set-based engineering, Poka-yoke (mistakeproofing), Knowledge-based environment, Value-focused planning and development, Top management support, Technology, Supplier integration, Workforce commitment and Continuous improvement culture) for assessing the LPD performance.

A Hybrid Fuzzy Model for Lean Product Development Performance Measurement

In the effort for manufacturing companies to meet up with the emerging consumer demands for mass customized products, many are turning to the application of lean in their product development process, and this is gradually moving from being a competitive advantage to a necessity. However, due to lack of clear understanding of the lean performance measurements, many of these companies are unable to implement and fully integrated the lean principle into their product development process. Extensive literature shows that only few studies have focus systematically on the lean product development performance (LPDP) evaluation. In order to fill this gap, the study therefore proposed a novel hybrid model based on Fuzzy Reasoning Approach (FRA), and the extension of Fuzzy-AHP and Fuzzy-TOPSIS methods for the assessment of the LPDP. Unlike the existing methods, the model considers the importance weight of each of the decision makers (Experts) since the performance criteria/attributes are required to be rated, and these experts have different level of expertise. The rating is done using a new fuzzy Likert rating scale (membership-scale) which is designed such that it can address problems resulting from information lost/distortion due to closed-form scaling and the ordinal nature of the existing Likert scale.

A modified exponential score function for troubleshooting an improved locally made Offshore Patrol Boat engine

ABSTRACT In this paper, we present an Intuitionistic Fuzzy Technique for Order Preference by Similarity to the Ideal Solution model which is based on a modified exponential score function for detecting early failure in a locally made Offshore Patrol Boat engine, with special regard to component interaction failure, using groups of experts’ opinions to detect the root cause and the engine systems most affected by the failures in the Boat engine. The study is aimed at providing an alternative method for the traditional product development failure mode identification and analysis methods which hitherto are limited when it comes to component interaction accidents and failure analysis in the machine system. The results from the study show that although early detection of failures in engines is quite difficult due to the dependency of machine systems and components on each other, using an intuitionistic fuzzy multi-criteria decision-making method which is based on experts’ opinions these faults/failure can easily be diagnosed and detected.

A Conceptual Model for the Implementation of Lean Product Development

Companies are faced with the need to address their product development challenges innovatively in order to stay competitive in todays market. One way of doing that is the integration of lean thinking in their product development process. However, due to the lack of clear understanding of the lean thinking performance measurements, the near absent of a holistic and unifying measuring method and the near or non-existence of an evaluating conceptual model to allow for the evaluation of the performance of the lean product development processes, many companies are unable to fully implement the lean thinking principle in their Product development process. In dealing with these issues, this article has therefore proposed a conceptual model which is based on some core critical success factors for the examination of lean performance in the product development process.

Application Of Intuitionistic Fuzzy Topsis Model For Troubleshooting An Offshore Patrol Boat Engine

Abstract In this paper, an Intuitionistic Fuzzy TOPSIS model which is based on a score function is proposed for detecting the root cause of failure in an Offshore Boat engine, using groups of expert’s opinions. The study which has provided an alternative approach for failure mode identification and analysis in machines, addresses the machine component interaction failures which is a limitation in existing methods. The results from the study show that although early detection of failures in engines is quite difficult to identify due to the dependency of their systems from each other. However, with the Intuitionistic Fuzzy TOPSIS model which is based on an improved score function such faults/failures are easily detected using expert’s based opinions.

Unethical Admissions: Academic Integrity in Question

The increasing unethical practices of graduates’ admissions have heightened concerns about the integrity of the academy. This article informs this important subject that affects the students, admission systems, and the entire scientific community, thus, representing an approach against scholarly black market activities including falsified documents and unethical practices by consultants and students’ recruitment agencies.

An exponential-related function for decision-making in engineering and management

Abstract An intuitionistic fuzzy TOPSIS model, which is based on an exponential-related function (IF-TOPSIS) and a fuzzy entropy method, has been proposed in this study. The exponential-related function, which represents the aggregated effect of positive and negative evaluations in the performance ratings of the alternatives, based on the intuitionistic fuzzy set (IFS) data. Serves, as a computational tool for measuring the separation distance of decision alternatives from the intuitionistic fuzzy positive and negative ideal solution to determine the relative closeness coefficient. The main advantage of this new approach is that (1) it uses a subjective and objective based approach for the computation of the criteria weight and (2) its simplicity both in its concept and computational procedures. The proposed method has successfully been implemented for the evaluation of some engineering designs related problems including the selection of a preferred floppy disk from a group of design alternatives, the selection of the best concept design for a new air-conditions system and finally, the selection of a preferred mouse from a group of alternatives as a reference for a new design. Also, for each of the three case studies, the method has been compared with some similar computational approaches.

An integrated model of Kano and quality function deployment for evaluation of lean production tools in assembly environment

The idea of introducing decision support system in manufacturing is to enable companies work more economically by using their manufacturing skills, time, space, money, and other manufacturing influencing factors more efficiently and effectively. The challenges associated with decision-making in manufacturing are numerous and sometimes complicated, most especially when faced with large number of factors and criteria to choose from. Many of the decisions in practice are usually made without a formal method or discussion and in most cases often leads to conflicts and waste of resources. In this study, a decision making model was developed for the evaluation and selection of lean production tools for the implementation of lean technique in a product assembly environment using a combined Kano model and Quality Function Deployment (QFD). The combined Kano model and QFD method was tested and applied in a simulated multiple decision-making problems with numerical examples. The proposed model in this study was found to be helpful and effective in dealing with multi-criteria problems.

Reliability information to support decision making for e-government projects

E-government implementations in developing countries still face difficulties, leading to a large failure ratio. This paper proposed an exponential-related function adopted in an intuitionistic Fuzzy TOPSIS model for improving the understanding of failure and for building appropriate reliability knowledge to support decision making for e-government projects. The new method which is simple and straightforward have been successfully applied by virtue of numerical case studies for detecting failures, which in turn has provided information for building reliability knowledge to support decision making process. The method has been compared successfully with some similar computational approach in literature.