Identification and Ranking the Implementation Barriers of TPM Using Fuzzy AHP: A Case Study of Gas Industry in Iran

Total Productive Maintenance or TPM is a philosophy to enhance an organization’s productivity and produce high quality goods by minimizing waste thereby reducing costs. TPM is designed to maximize equipment efficiency by determining an extensive productive maintenance system covering the whole life of the equipment, extending across all equipment-related fields and with participation of all employees from the top management to the shop-floor workers, to advance productive maintenance through voluntary small group activities (Tsuchiya 1992). Most of the automotive manufacturing industries are focusing on strict quality standards in their production process and implementing a quality program called Total Productive Maintenance. With the fast development of the maintenance, it becomes critical to set up a TPM Evaluation criteria system. Fuzzy Analytic Hierarchy Process is a new multi-criteria evaluation method evolved from Saaty's AHP. So, this paper aimed to find out and rank the key factors and obstacles that affect success in TPM in Gas industry using fuzzy AHP approach, and give an evaluation method for TPM in order to help researches and managers to determine the drawbacks and opportunities

Explaining the impact of reconfigurable manufacturing systems on environmental performance: The role of top management and organizational culture

This study develops a theoretical model that links reconfigurable manufacturing systems with top management beliefs, participation, and environmental performance, drawing on agency theory and organizational culture. The study takes into account the possible confounding effects of organization size and organizational compatibility. Drawing on responses from 167 top managers, the results of hypothesis testing suggest that (i) higher top management participation, being influenced by top management beliefs, leads to higher chances of RMS becoming adopted by organizations as their manufacturing strategy; (ii) organizational culture moderates the relationship between the level of top management participation and RMS (and manufacturing strategies) adoption; and (iii) higher re-configurability of manufacturing systems leads to better environmental performance. Furthermore, we integrate Agency Theory and organizational culture to explain the role of top management beliefs and participation in achieving environmental performance via RMS. Finally, we offer guidance to those managers who would like to engage in leveraging top management commitment for achieving environmental performance, and outline further research directions

Key performance indicators for sustainable manufacturing evaluation in automotive companies

The automotive industry is regarded as one of the most important and strategic industry in manufacturing sector. It is the largest manufacturing enterprise in the world and one of the most resource intensive industries of all major industrial system. However, its products and processes are a significant source of environmental impact. Thus, there is a need to evaluate sustainable manufacturing performance in this industry. This paper proposes a set of initial key performance indicators (KPIs) for sustainable manufacturing evaluation believed to be appropriate to automotive companies, consisting of three factors divided into nine dimensions and a total of 41 sub-dimensions. A survey will be conducted to confirm the adaptability of the initial KPIs with the industry practices. Future research will focus on developing an evaluation tool to assess sustainable manufacturing performance in automotive companies

Critérios para avaliação da gestão de periódicos científicos eletrônicos sob a ótica do capital intelectual

Tese (doutorado) - Universidade Federal de Santa Catarina, Centro Tecnológico, Programa de Pós-Graduação em Engenharia de Produção, Florianópolis, 2014.A propagação de novos títulos de periódicos científicos nas diversas áreas do conhecimento tem sido preocupação dos profissionais que se interessam pela qualidade da informação científica, quer sejam autores, editores, publicadores, serviços de indexação, centros de documentação, bibliotecas e, de maneira especial, pesquisadores (usuários da informação). No processo de formação da revisão de literatura observou-se, que as pesquisas sobre o tema periódico científico eletrônico ainda não abordaram a visão de Capital Intelectual (CI) como forma de avaliar sua gestão. Este trabalho propõe critérios para avaliar a gestão dos periódicos científicos eletrônico utilizando a abordagem de CI. Foi utilizada uma metodologia matemática híbrida com a integração dos métodos Fuzzy Delphi (FDELPHI) e Fuzzy Analytic Hierarchy Process (FAHP). O FDELPHI foi utilizado para levantar os fatores críticos (critérios/subcritérios) presentes na gestão dos periódicos científicos eletrônicos. O método FAHP foi aplicado para calcular os pesos relativos dos critérios/subcritérios selecionados que afetam a sua gestão. Os resultados apontaram que o Capital Humano foi apontado como um dos aspectos que mais (60%) influencia na gestão de um periódico. Quantos aos critérios os que mais influenciam são: Normalização dos artigos; Qualidade dos artigos; Conhecimento dos envolvidos; Reconhecimento pelo trabalho dos referees e colaboradores; Trabalho em equipe; Acurácia das informações publicadas e Visibilidade. Assim com esse trabalho espera-se contribuir para o melhoramento da gestão de periódicos científicos eletrônicos e proporcionar vantagens competitivas.Abstract : The spread of new scientific journal titles in different areas of knowledge has been a concern to professionals who care about the quality of scientific information, whether they are authors, editors, publishers, indexing services, documentation centers, libraries, and in a special way, researchers (information users). In the formation process of literature review, it was noted that the research on electronic scientific journal topic has not addressed yet the vision of Intellectual Capital (IC) as a way to assess their management. This work proposes criteria to evaluate the management of electronic scientific journals using the IC approach. A hybrid mathematical methodology with the integration of Fuzzy Delphi (FDELPHI) and Fuzzy Analytic Hierarchy process (FAHP) was used. FDELPHI was used to raise critical factors (criteria/sub-criteria) present in electronic scientific journals management. The FAHP method was applied to calculate the relative weights of the criteria/sub-criteria selected that affect their management. The results indicated that the Human Capital was appointed as one of the aspects that most (60%) influences the management of a periodical. Regarding criteria, the most influential ones are: Article normalization; Article quality; Knowledge of those involved; Recognition for the work of referees and contributors; Teamwork; Accuracy of published information and Visibility. So, this work is expected to contribute to improvement in the management of electronic scientific journals and to provide competitive advantages

Novel methodologies and a comparative study for manufacturing systems performance evaluations

The purpose of this work is to establish complex fuzzy methodologies in the evaluation of a manufacturing system's performance. Many empirical studies have been presented about the evaluation of manufacturing system's performance. However, the performance evaluation is quite subjective, since it relies on the individual judgment of the managers who have different, various and multi-factor assessment methods of a system's performance. In this study, two fuzzy modeling designs were developed and in the construction of the models, a hierarchy process was used. In the first method, the performance factors and the Analytic Hierarchy Process (AHP) were fuzzified and the use of fuzzy numbers and a fuzzy AHP for this problem was recommended. Also, the relative importance of these factors with respect to each other and their contribution to the overall performance was quantified with fuzzy linguistic terms. In the other method, we proposed Approximate Reasoning (AR) based on experts' knowledge which is represented with the collection of the rules. These fuzzy rule bases are "if-then" linguistic rules that are formed with linguistic variables such as poor, below average, average, above average and superior. Additionally, the problem was structured with the normal AHP and System-With-Feedback (SWF), Finally, these methods were compared. The results showed that fuzzy AHP leads to the best result. It is expected that the recommended models would have an advantage in the competitive manufacturing including cost, flexibility, quality, speed and dependability. (C) 2007 Elsevier Inc. All rights reserved. The purpose of this work is to establish complex fuzzy methodologies in the evaluation of a manufacturing system&rsquo;s performance. Many empirical studies have been presented about the evaluation of manufacturing system&rsquo;s performance. However, the performance evaluation is quite subjective, since it relies on the individual judgment of the managers who have different, various and multi-factor assessment methods of a system&rsquo;s performance. In this study, two fuzzy modeling designs were developed and in the construction of the models, a hierarchy process was used. In the first method, the performance factors and the Analytic Hierarchy Process (AHP) were fuzzified and the use of fuzzy numbers and a fuzzy AHP for this problem was recommended. Also, the relative importance of these factors with respect to each other and their contribution to the overall performance was quantified with fuzzy linguistic terms. In the other method, we proposed Approximate Reasoning (AR) based on experts&rsquo; knowledge which is represented with the collection of the rules. These fuzzy rule bases are &lsquo;&lsquo;if-then&rsquo;&rsquo; linguistic rules that are formed with linguistic variables such as poor, below average, average, above average and superior. Additionally, the problem was structured with the normal AHP and System-With-Feedback (SWF), Finally, these methods were compared. The results showed that fuzzy AHP leads to the best result. It is expected that the recommended models would have an advantage in the competitive manufacturing including cost, flexibility, quality, speed and dependability.</p

Novel methodologies and a comparative study for manufacturing systems performance evaluations

The purpose of this work is to establish complex fuzzy methodologies in the evaluation of a manufacturing system's performance. Many empirical studies have been presented about the evaluation of manufacturing system's performance. However, the performance evaluation is quite subjective, since it relies on the individual judgment of the managers who have different, various and multi-factor assessment methods of a system's performance. In this study, two fuzzy modeling designs were developed and in the construction of the models, a hierarchy process was used. In the first method, the performance factors and the Analytic Hierarchy Process (AHP) were fuzzified and the use of fuzzy numbers and a fuzzy AHP for this problem was recommended. Also, the relative importance of these factors with respect to each other and their contribution to the overall performance was quantified with fuzzy linguistic terms. In the other method, we proposed Approximate Reasoning (AR) based on experts' knowledge which is represented with the collection of the rules. These fuzzy rule bases are "if-then" linguistic rules that are formed with linguistic variables such as poor, below average, average, above average and superior. Additionally, the problem was structured with the normal AHP and System-With-Feedback (SWF), Finally, these methods were compared. The results showed that fuzzy AHP leads to the best result. It is expected that the recommended models would have an advantage in the competitive manufacturing including cost, flexibility, quality, speed and dependability. (C) 2007 Elsevier Inc. All rights reserved

Decision Making Analysis for an Integrated Risk Management Framework of Maritime Container Port Infrastructure and Transportation Systems

This research proposes a risk management framework and develops generic risk-based decision-making, and risk-assessment models for dealing with potential Hazard Events (HEs) and risks associated with uncertainty for Operational Safety Performance (OSP) in container terminals and maritime ports. Three main sections are formulated in this study: Section 1: Risk Assessment, in the first phase, all HEs are identified through a literature review and human knowledge base and expertise. In the second phase, a Fuzzy Rule Base (FRB) is developed using the proportion method to assess the most significant HEs identified. The FRB leads to the development of a generic risk-based model incorporating the FRB and a Bayesian Network (BN) into a Fuzzy Rule Base Bayesian Network (FRBN) method using Hugin software to evaluate each HE individually and prioritise their specific risk estimations locally. The third phase demonstrated the FRBN method with a case study. The fourth phase concludes this section with a developed generic risk-based model incorporating FRBN and Evidential Reasoning to form an FRBER method using the Intelligence Decision System (IDS) software to evaluate all HEs aggregated collectively for their Risk Influence (RI) globally with a case study demonstration. In addition, a new sensitivity analysis method is developed to rank the HEs based on their True Risk Influence (TRI) considering their specific risk estimations locally and their RI globally. Section 2: Risk Models Simulations, the first phase explains the construction of the simulation model Bayesian Network Artificial Neural Networks (BNANNs), which is formed by applying Artificial Neural Networks (ANNs). In the second phase, the simulation model Evidential Reasoning Artificial Neural Networks (ERANNs) is constructed. The final phase in this section integrates the BNANNs and ERANNs that can predict the risk magnitude for HEs and provide a panoramic view on the risk inference in both perspectives, locally and globally. Section 3: Risk Control Options is the last link that finalises the risk management based methodology cycle in this study. The Analytical Hierarchal Process (AHP) method was used for determining the relative weights of all criteria identified in the first phase. The last phase develops a risk control options method by incorporating Fuzzy Logic (FL) and the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to form an FTOPSIS method. The novelty of this research provides an effective risk management framework for OSP in container terminals and maritime ports. In addition, it provides an efficient safety prediction tool that can ease all the processes in the methods and techniques used with the risk management framework by applying the ANN concept to simulate the risk models