Hybrid-fuzzy techniques with flexibility and attitudinal parameters for supporting early product design and reliability management

The main aim of the research work presented in this thesis is to define and develop novel Hybrid Fuzzy-based techniques for supporting aspects of product development engineering, specifically product reliability at the early phase of product design under the design for reliability philosophy and concept designs assessment problems when the required information is rough and incomplete. Thus, to achieve the above-stated aim, which has been formulated in the effort to filling the identified gaps in the literature which comprise of the need for a holistic, flexible and adjustable method to facilitate and support product design concept assessment and product reliability at the early product design phase. The need for the incorporation of the attitudinal character of the DMs into the product reliability and design concept assessment and finally, the need to account for the several interrelated complex attributes in the product reliability and design concept assessment process. A combination of research methods has been employed which includes an extensive literature review, multiple case study approach, and personal interview of experts, through which data were, collected that provided information for the real-life case study. With the new Hybrid Fuzzy-based techniques (i.e. the intuitionistic fuzzy TOPSIS model which is based on an exponential-related function (IF-TOPSISEF) and the Multi-attribute group decision-making (MAGDM) method which is based on a generalized triangular intuitionistic fuzzy geometric averaging (GTIFGA) operator), a more robust method for the product reliability and design concepts assessment respectively have been achieved as displayed in the comparative analysis in the thesis. The new methods have provided a more complete and a holistic view of the assessment process, by looking at the product reliability and design concept assessment from different scenario depending on the interest of the DMs. Using the above methods, the thesis has been able to evaluated some complex mechanical systems in literature and in real-life including Crawler Crane Machine and Forklift Truck for design change with the purpose of gaining appropriate reliability knowledge and information needed at the early product design phase, and that can subsequently aid and improve the product design concepts after all such useful information have been added into the new design. With the application of the new methods, and their proven feasibility and rationality as displayed in the assessment results of the complex mechanical systems in literature and that of the real-life case studies, this thesis, therefore, can conclude that the Hybrid Fuzzy-based techniques proposed, has provided a better and a novel alternative to existing product reliability and design concepts assessment methods

Need for Reliability Assessment of Parent Product before Redesigning a New Product

As companies increasingly invest on the development of new products, and in the redesigning of existing ones in order to meet the ever emerging and rapidly changing customer demands, they continue to face an extremely competitive and cost-cutting war. Since today’s product design works are mainly focused on the redesigning of existing products, most especially for complex products and systems, their properties are expected to be of higher technical content, reliability requirements as well as design characteristics

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

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

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

Interval-Valued Intuitionistic Fuzzy Topsis-Based Model For Troubleshooting Marine Diesel Engine Auxiliary System

In this paper, we present an interval-valued Intuitionistic Fuzzy TOPSIS model, which is based on an improved score function for detecting failure in a marine diesel engine auxiliary system, using groups of experts’ opinions to detect the root cause of failure in the engine system and the area most affected by failures in the diesel engine. The improved score function has been used for the computation of the separation measures from the intuitionistic fuzzy positive ideal solution (IFPIS) and intuitionistic fuzzy negative ideal solution (IFNIS) of alternatives while the criteria weight have been determined using an intuitionistic fuzzy entropy. The study is aimed at providing an alternative method for the identification and analysis of failure modes in engine systems. The results from the study show that although detection of failures in Engines is quite difficult to identify due to the dependency of the engine systems on each other, however using intuitionistic fuzzy multi-criteria decision-making method the faults/failure can easily be diagnosed

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

Interval-valued intuitionistic fuzzy multi-criteria model for design concept selection

This paper presents a new approach for design concept selection by using an integrated Fuzzy Analytical Hierarchy Process (FAHP) and an Interval-valued intuitionistic fuzzy modified TOP-SIS (IVIF-modified TOPSIS) model. The integrated model which uses the improved score func-tion and a weighted normalized Euclidean distance method for the calculation of the separation measures of alternatives from the positive and negative intuitionistic ideal solutions provides a new approach for the computation of intuitionistic fuzzy ideal solutions. The results of the two approaches are integrated using a reflection defuzzification integration formula. To ensure the feasibility and the rationality of the integrated model, the method is successfully applied for evaluating and selecting some design related problems including a real-life case study for the selection of the best concept design for a new printed-circuit-board (PCB) and for a hypothetical example. The model which provides a novel alternative, has been compared with similar com-putational methods in the literature

Intelligent Model for the Reliability of the Non-Intrusive Continuous Sensors Used for the Detection of Fouling-Layer in Heat Exchanger System

Faults in this sensor must be detected on time to ensure the functionality of the entire system’s architecture and to maintain system balance, which will keep false positive rates low during the system’s operational period. False positives reduce diagnostic confidence and necessitate unnecessary and costly mitigation actions, lowering system productivity. It is on this basis that this study proposes a clustering model algorithm (K-mean clustering) to investigate and manage the reliability and performance of the sensors. The results from the implementation of the K-mean clustering method show that the running of the algorithm fits the model correctly, both for the training of the dataset and for the prediction of the cluster in each of the datasets considered. A reasonable grouping was found for the two and three clusters considered, which are represented by the colors (blue, orange, and green). These colors indicate the fault state, non-fault state, normal state, and abnormal state of the non-intrusive continuous sensor. The simulated results show the fault state in the blue region and the non-fault state in the orange region for the two clusters, while the normal state is in the blue region and the abnormal state is in the orange and green regions for the three clusters considered

Application of Fuzzy AHP for Ranking Critical Success Factors for the Successful Implementation of Lean Production Technique

The implementation of lean production techniques in a product assembly environment depends on a numbers of factors and these factors constitute the backbone for the successful implementation of the lean technique. Although, many research efforts, both theoretical and practical studies have been made over the year on the identification and evaluation of the critical success factors (CSFs) for lean implementation, but very little or less effort has been devoted to evaluating the actual contribution of each of these factors to the overall success of the lean implementation program. This study therefore presents a framework for ranking and evaluating the contribution of these critical success factors in the order in which they accounts for the successful implementation of lean production techniques using Fuzzy Analytic Hierarchy Process (FAHP) approach

Systematic model for lean product development implementation in an automotive related company

Lean product development is a major innovative business strategy that employs sets of practices to achieve an efficient, innovative and a sustainable product development. Despite the many benefits and high hopes in the lean strategy, many companies are still struggling, and unable to either achieve or sustain substantial positive results with their lean implementation efforts. However, as the first step towards addressing this issue, this paper seeks to propose a systematic model that considers the administrative and implementation limitations of lean thinking practices in the product development process. The model which is based on the integration of fuzzy Shannon’s entropy and Modified Technique for Order Preference by Similarity to the Ideal Solution (M-TOPSIS) model for the lean product development practices implementation with respective to different criteria including management and leadership, financial capabilities, skills and expertise and organization culture, provides a guide or roadmap for product development managers on the lean implementation route