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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

The aim of this paper is to develop a new tool for reliability and failure mode analysis by integrating the conventional aspects of the popular failure mode and criticality analysis (FMECA) procedure with economic considerations. Here FMECA is approached as a multicriteria decision making technique which integrates four different factors: chance of failure, chance of non-detection, severity, and expected cost. To aid the analyst to formulate an efficient and effective priority ranking of the possible causes of failure, the analytic hierarchy process technique is adopted. With this technique, factors and alternative causes of failure are arranged in a hierarchic structure and evaluated only through the use of a series of pairwise judgements. With this new approach to failure investigation, the critical FMECA problem concerning the (direct) evaluation of failure factors is also by-passed. The principles of the theory and an actual application in an Italian refrigerator manufacturing company are reported in the paper. IntroductionConsidered as the last point in failure investigation (Holmberg and Folkeson, 1991), the failure mode, effects and criticality analysis (FMECA) technique (or FMEA, failure mode and effect analysis) is devoted to determining design reliability by considering potential causes of failure and their effects on the system under study (Countinho, 1964;Dillon, 1985; O'Connor, 1981). Briefly, FMECA is concerned with listing each potential failure mode of a (global) system and its effects on the listed subsystems. This bottom-up approach can be utilised at any level, from complete systems to components.The main advantages of FMECA are:

In an era of global sourcing, the firm's success often hinges on the most appropriate selection of its suppliers. Supplier selection is sometimes very complicated, owing to a variety of uncontrollable and unpredictable factors which affect the decision. Describes a multiple attribute utility theory based on the use of data envelopment analysis (DEA), aimed at helping purchasing managers to formulate viable sourcing strategies in the changing market place. An application of the methodology using actual data retrieved from a firm operating in the bottling industry is illustrated. DEA has proved to be capable of handling multiple conflicting attributes inherent in supplier selection while simultaneously trading-off key supplier selection criteria.

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

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 ideal cycle time, explaining it in terms of: bottleneck inefficiency, quality rate, and synchronisation-transportation problems.Research limitations/implications -OEEML alone fails to explain to which extent effectiveness is supported by in process-inventories and should be integrated with additional metrics to estimate the inventories-related costs. Practical implications -OEEML provides practitioners with an operative tool useful to highlight the points where the major inefficiencies take place and to foresee the potential benefits of corrective actions. Originality/value -In relation to other methodologies, OEEML presents two main advantages: it detects and quantifies the line's critical points and it can be applied even in presence of buffers, without underestimating the efficiency of the system.