Marco Frosolini

Fuzzy criticality assessment model for failure modes and effects 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.

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

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...

An analytical method for maintenance outsourcing service selection

In this paper an experience dealing with the analysis of maintenance outsourcing by means of multi‐criteria decision methods (MCDM) is reported. In particular, the analytic hierarchy process technique (AHP) is used as a managerial decision support system to select the best alternative between different outsourcing contracts in terms of maintenance services. The proposed methodology has been tested on an industrial case study dealing with an important italian brickwork. This application shows how the AHP is able to support the choice of the correct level of the maintenance activities outsourcing. In particular, the hierarchic decisional structure developed represents an instrument able to give a well balanced synthesis of several different factors that must be taken into account during this type of decision problem.

AHP‐based evaluation of CMMS software

Purpose – To provide a structured methodology to permit an optimal selection of the best suited Computer Managed Maintenance System (CMMS) software within process industries.Design/methodology/approach – The analysis has been executed adopting a multi‐attribute decision making methodology, namely the analytic hierarchic process (AHP) technique. A specific hierarchic structure has been defined considering 46 criteria outlined via questionnaires and interviews with administration, production and maintenance managers of several industries. To improve the effectiveness of the methodology, AHP has been coupled with a sound sensitivity analysis.Findings – The application of the proposed approach allows the maintenance practitioners to concentrate on a limited subset of CMMS applications and to compare their actual capabilities in order to select the right one, rather than considering only their purchase cost.Practical implications – The methodology enables decision makers to restrict the selection process to a ...

Uncertainty in value stream mapping analysis

In this article, two alternative approaches to include variability analysis in value stream mapping (VSM) are presented. Notoriously, VSM is one of the best tools to map a process and to identify its main criticalities in order to enhance lean manufacturing. Unfortunately, in the standard approach, data are recorded on the map as deterministic, disregarding the real variability of the process. This is a strong limit because, especially within manufacturing processes, variability has a significant impact on costs and leads to several wastes. Therefore, it must be carefully analysed and reduced before lean manufacturing can be set into place. To overcome this weakness, this article proposes two alternative approaches based on statistics and fuzzy algebra, respectively. Both methods are designed to support practitioners and can be easily applied to several industrial applications. Their practicality is finally demonstrated through an industrial application of relevance. Obtained results are compared and respective advantages/disadvantages are presented and discussed.

The house of reliability

Purpose – The purpose of this paper is to provide a structured methodology for performing build‐in reliability (BIR) investigation during a new product development cycle.Design/methodology/approach – The methodology in this paper represents an extension of the Quality Functional Deployment/House of Quality (QFD/HoQ) concepts to reliability studies. It is able to translate the reliability requisites of customers into functional requirements for the product in a structured manner based on a Failure Mode And Effect Analysis (FMEA). Besides, it then allows it to build a completely new operative tool, named House of Reliability (HoR), that enhances standard analyses, introducing the most significant correlations among failure modes. Using the results from HoR, a cost‐worth analysis can be easily performed, making it possible to analyse and to evaluate the economical consequences of a failure.Findings – The paper finds that the application of the proposed approach allows users to identify and control the design...

Overall equipment effectiveness of a manufacturing line (OEEML)

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...

A standard agreement for vendor managed inventory

Purpose – The purpose of this paper is to define the standard structure of a vendor managed inventory (VMI) agreement, which can be used as a guideline for the early definition of the agreement.Design/methodology/approach – Starting from an industrial application of relevance, the information flow and the technical details, which are to be defined before the operation startup, are identified and discussed. These data are used as the key points for the definition of the basic frame of the agreement. A particular emphasis is given to the “Technical Specification” and the “Service Level Agreement” sections.Findings – It is shown that a VMI agreement should be arranged into parts dealing with the generic and legal sides of the agreement, whereas the technical aspects and the relation‐specific topics should be addressed in the annexes. This increases the flexibility of the agreement in that, as the VMI relationship evolves over time, changes will affect only the annexes leaving the main body of the agreement u...

Stochastic overall equipment effectiveness

This article focuses on the overall equipment effectiveness (OEE), a key performance indicator typically adopted to support Lean Manufacturing and Total Productive Maintenance. Unfortunately, being a deterministic metric, the OEE only provides a static representation of a process, but fails to capture the real variability of manufacturing performances. To take into account the stochastic nature of the OEE, an approximated procedure based on the application of the Central Limit Theorem is presented: the OEE is considered as a stochastic random variable and its probability density function (pdf) is generated through the aggregation of the pdf of the basic causes of waste. Notwithstanding its approximated nature, the procedure can be applied in most practical cases, since the accuracy is assured provided that the average OEE is lower than 90% and the variability of the losses is high. The validity of the approach has also been confirmed by an industrial application included in this article. The results obtained demonstrate that the stochastic OEE can help in battling variation, for it allows one to identify the hidden losses that account for most of the variability and to estimate the impacts of potential corrective actions in terms of both efficiency and efficacy.

Failure rate prediction with artificial neural networks

Purpose – To suggest that a multi layer perception based artificial neural network (MLP‐ANN) is a practical instrument to evaluate the expected failure rates of 143 centrifugal pumps used in an oil refinery plant.Design/methodology/approach – A MLP is adopted to weigh up the correlation existing among the failure rates and the several different operating conditions which have some influence in the occurrence.Findings – During the training phase, it is possible to discriminate among those variables closely significant for the final outcome and those which can be kept off from the analysis. In particular, the neural network automatically calculates and classifies the centrifugal pumps in terms of both the failure probability and its variability degree, giving a better analysis instrument to take decisions and to justify them, in order to optimise and fully support an eventual preventive maintenance (PM) program.Originality/value – Aids in decision‐making to reduce the necessity of reactive maintenance activ...