* Starting from Need* Evolution of the Toyota Production System* Further Development* Genealogy of the Toyota Production System* The True Intention of the Ford System* Surviving the Low-Growth Period

Toyota production system : beyond large-scale production

Multi-Criteria Decision Aid (MCDA) or Multi-Criteria Decision Making (MCDM) methods have received much attention from researchers and practitioners in evaluating, assessing and ranking alternatives across diverse industries. Among numerous MCDA/MCDM methods developed to solve real-world decision problems, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) continues to work satisfactorily across different application areas. In this paper, we conduct a state-of-the-art literature survey to taxonomize the research on TOPSIS applications and methodologies. The classification scheme for this review contains 266 scholarly papers from 103 journals since the year 2000, separated into nine application areas: (1) Supply Chain Management and Logistics, (2) Design, Engineering and Manufacturing Systems, (3) Business and Marketing Management, (4) Health, Safety and Environment Management, (5) Human Resources Management, (6) Energy Management, (7) Chemical Engineering, (8) Water Resources Management and (9) Other topics. Scholarly papers in the TOPSIS discipline are further interpreted based on (1) publication year, (2) publication journal, (3) authors' nationality and (4) other methods combined or compared with TOPSIS. We end our review paper with recommendations for future research in TOPSIS decision-making that is both forward-looking and practically oriented. This paper provides useful insights into the TOPSIS method and suggests a framework for future attempts in this area for academic researchers and practitioners.

Review: A state-of the-art survey of TOPSIS applications

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This paper proposes a fuzzy TOPSIS method based on alpha level sets and presents a nonlinear programming (NLP) solution procedure. The relationship between the fuzzy TOPSIS method and fuzzy weighted average (FWA) is also discussed. Three numerical examples including an application to bridge risk assessment are investigated using the proposed fuzzy TOPSIS method to illustrate its applications and the differences from the other procedures. It is shown that the proposed fuzzy TOPSIS method performs better than the other fuzzy versions of the TOPSIS method.

Fuzzy TOPSIS method based on alpha level sets with an application to bridge risk assessment

Failure mode and effects analysis (FMEA) is a risk assessment tool that mitigates potential failures in systems, processes, designs or services and has been used in a wide range of industries. The conventional risk priority number (RPN) method has been criticized to have many deficiencies and various risk priority models have been proposed in the literature to enhance the performance of FMEA. However, there has been no literature review on this topic. In this study, we reviewed 75 FMEA papers published between 1992 and 2012 in the international journals and categorized them according to the approaches used to overcome the limitations of the conventional RPN method. The intention of this review is to address the following three questions: (i) Which shortcomings attract the most attention? (ii) Which approaches are the most popular? (iii) Is there any inadequacy of the approaches? The answers to these questions will give an indication of current trends in research and the best direction for future research in order to further address the known deficiencies associated with the traditional FMEA.

Review: Risk evaluation approaches in failure mode and effects analysis: A literature review

In this paper, an alternative multi-attribute decision-making approach for prioritizing failures in failure mode, effects and criticality analysis (FMECA) is presented. The technique is specifically intended to overcome some of the limitations concerning the use of the conventional US MIL-STD-1629A method. The approach is based on a fuzzy version of the ‘technique for order preference by similarity to ideal solution’ (TOPSIS).The use of fuzzy logic theory allows one to avoid the intrinsic difficulty encountered in assessing ‘crisp’ values in terms of the three FMECA parameters, namely chance of failure, chance of non-detection, and severity. With the proposed approach, the definition of a knowledge base supported by several qualitative rule bases is no longer required. To solve the fundamental question of ranking the final fuzzy criticality value, a particular method of classification is adopted, allowing a fast and efficient sorting of the final outcome. An application to an important Italian domestic appliance manufacturer and a comparison with conventional FMECA are reported to demonstrate the characteristics of the proposed method. Finally, a sensitivity analysis of the fuzzy judgement weights has confirmed that the proposed approach gives a reasonable and robust final priority ranking of the different causes of failure. Copyright © 2003 John Wiley & Sons, Ltd.

Fuzzy TOPSIS approach for failure mode, effects and criticality analysis

This paper presents a tool for reliability and failure mode analysis based on an advanced version of the popular failure mode, effects and criticality analysis (FMECA) procedure. To help the analyst formulating efficiently effective criticality assessments of the possible causes of failure, the fuzzy logic technique is adopted. Particular attention has been devoted to support the maintenance staff with a fuzzy criticality assessment model easy to implement and design. To test the proposed methodology, an actual application concerning a process plant in milling field for human consumption flour is showed in the paper.

Fuzzy criticality assessment model for failure modes and effects analysis

Purpose – Overall equipment effectiveness (OEE) is the key metric to measure the performance of individual equipment. However, when machines operate jointly in a manufacturing line, OEE alone is not sufficient to improve the performance of the system as a whole. The purpose of this paper is to show how to overcome this limitation, by presenting a new metric (overall equipment effectiveness of a manufacturing line – OEEML) and an integrated approach to assess the performance of a line.Design/methodology/approach – An alternative losses classification structure is developed to divide the losses that can be directly ascribed to equipment, from the ones that are spread in the line. Starting from this losses classification structure, an approach based on OEE is developed to evaluate the criticalities and the effectiveness of the line.Findings – This method has been applied to an automated line for engine basements production. Results show that OEEML successfully highlights the progressive degradation of the id...

Overall equipment effectiveness of a manufacturing line (OEEML): An integrated approach to assess systems performance

https://isiarticles.com/bundles/Article/pre/pdf/3328.pdf

Marco Frosolini

Papers

Fuzzy TOPSIS approach for failure mode, effects and criticality analysis

Fuzzy criticality assessment model for failure modes and effects analysis

Overall equipment effectiveness of a manufacturing line (OEEML): An integrated approach to assess systems performance

An integrated approach to implement Project Management Information Systems within the Extended Enterprise

A fuzzy multi-criteria approach for critical path definition