V. Duraccio

Validation and application of a reliability allocation technique (Advanced Integrated Factors Method) to an industrial system

The proposed work analyses and applies a new reliability and redundancy allocation procedure. Starting from a similar methodology previously developed by the authors, Integrated Factors Method (IFM), a new reliability allocation and optimization method is developed: Advanced Integrated Factors Method (AIFM). The new technique has been proposed to analyze complex systems in the pre-design phase, even if its general characteristics allow extending the method to different design and production phases. The previous method has been improved through the introduction of new indexes that help improve underperforming components in order to achieve the allocated reliability values. The method introduces a big number of factors, so it can be applied to a wide range of systems. It is characterized by a very simple mathematical formulation, that can be made more complicated for a more detailed analysis.

Failure Prevention Through Performance Evaluation of Reliability Components in Working Condition

The reliability of a system during operation can be expressed quantitatively through different time functions. Mathematical procedures and statistical laws allow to assess the precise analytical relations between these functions. Referring to a generic system or component is a common experience that its duration in-service is not predictable in a deterministic way. This consideration identifies the lifetime (or time to failure) of the component as a continuous random variable, susceptible to a statistical description, whose estimate is crucial in the design phase, or in any case before the commissioning of equipment. In a second stage, the actual values of reliability must be compared with the forecast values arising from the theoretical statistical model used. This comparison allows assessment of the goodness-of-fit level and the confidence level of the prediction model, in order to validate it for any future equipment redesigns or for similar equipment. In this context, the present work is aimed at identifying the most appropriate statistical tools for the comparison above, and then to assess the reliability of the forecast data, compared to the real performance of a reliability system. For this purpose, a literature analysis was conducted, with a dual purpose: The identification of statistical models most commonly used to describe the reliability function of a system; to provide a choice of appropriate indicators and effective tests for assessing the confidence of the statistical models for reliability scopes. The models identified were then applied, as an example, to the real case of a catalytic cracking catalyst with the fluidized bed of a petrochemical plant. The results obtained from the case study, discussed in the final section of the work, offer many points of comparison between the various statistical models as well as a first overview of their reliability.

A New Method for Reliability Allocation: Critical Flow Method

A complex system consists of many subsystems, which are developed concurrently and sometimes independently. It would be too late to validate the system reliability until the final system prototype is ready after months or years of development. From a project management point of view, the reliability of each subsystem or sub-function should be examined as early as possible. Therefore, the allocation of a reasonable reliability requirement to each subsystem and sub-function based on the system reliability target is very important. The present work analyses, in literature, the main reliability allocation techniques. Starting from the known methodologies, a new critical flow method for reliability allocation method has been developed. The proposed method can be used for complex system with serial and parallel configurations.

Assessment of the Effectiveness of Maintenance-oriented Design

This work aims to assess the impact of maintenance-oriented design on a production line in the pharmaceutical industry, which includes operations in a clean room. The case study analyses the downtimes of a production line of large volume parental solutions. The results obtained at the end of an appropriate period of observation were used to identify the main problems, in terms of maintenance time. Some of the critical issues were overcome by requiring that part of the production line be redesigned by a company specialized in the design of clean room lines. In this context, the focus of the case study is not on the technical aspects of maintenance-oriented design application, but its consequences in terms of the increase in performance. The performance of the new production line was analysed and compared with that obtained in the first phase of the study. This comparison allowed us to estimate and quantify the achieved improvements referring to system availability and consequently to a production increase quantified at more than 110,000 units per year. The impact of the maintenance-oriented design was also evaluated from an economic point of view. In particular, the production increase obtained and the corresponding economic advantages were evaluated. Through this comparison, it was possible to estimate the payback period for the investment of redesign, quantified in less than six years.

Maintenance Management and Organization

Maintenance management is a relatively new field and the corresponding body of knowledge is continuing to grow (Visser, 2002). For example, in Europe, two technical committees of the Comite Europeen de Normalisation (CEN) are currently adding to the body of knowledge terminologies, guidance to prepare agreements, control systems for maintenance management, and other development directions (CEN, 2008). In particular, CEN Technical Committee 319 deals specifically with maintenance. They have published one standard (EN 15341) that provides maintenance management with the support of a control system (made up from more than 70 indicators) to achieve maintenance excellence and to competitively use technical assets, regardless of industry. Moreover, this committee has been addressing the issues of defining a maintenance management general framework (including buildings) through a standard currently in progress and identifying three very promising development directions (i.e., responsibilities in maintenance; identification, classification, and costs in maintenance actions; and maintenance in the healthcare industry).