Maintenance strategies affecting equipment performance

Proper maintenance of plant items is crucial for the safe and profitable operation of process plants, The relevant maintenance policies fall into the following four categories: (i) preventivejopportunistic/breakdown replacement policies, (ii) inspection/inspection-repair-replacernent policies, (iii) restorative maintenance policies, and (iv) condition based maintenance policies, For correlating failure times of component equipnent and complete systems, the Weibull failure distribution has been used, A new powerful method, SEQLIM, has been proposed for the estimation of the Weibull parameters; particularly, when maintenance records contain very few failures and many successful operation times. When a system consists of a number of replaceable, ageing components, an opporturistic replacernent policy has been found to be cost-effective, A simple opportunistic rrodel has been developed. Inspection models with various objective functions have been investigated, It was found that, on the assumption of a negative exponential failure distribution, all models converge to the same optimal inspection interval; provided the safety components are very reliable and the demand rate is low, When deterioration becomes a contributory factor to same failures, periodic inspections, calculated from above models, are too frequent, A case of safety trip systems has been studied, A highly effective restorative maintenance policy can be developed if the performance of the equipment under this category can be related to some predictive modelling. A novel fouling model has been proposed to determine cleaning strategies of condensers, Condition-based maintenance policies have been investigated. A simple gauge has been designed for condition monitoring of relief valve springs. A typical case of an exothermic inert gas generation plant has been studied, to demonstrate how various policies can be applied to devise overall maintenance actions.

Concreteness effects in different tasks: implications for models of short-term memory

This study investigates concreteness effects in tasks requiring short-term retention. Concreteness effects were assessed in serial recall, matching span, order reconstruction, and free recall. Each task was carried out both in a control condition and under articulatory suppression. Our results show no dissociation between tasks that do and do not require spoken output. This argues against the redintegration hypothesis according to which lexical-semantic effects in short-term memory arise only at the point of production. In contrast, concreteness effects were modulated by task demands that stressed retention of item versus order information. Concreteness effects were stronger in free recall than in serial recall. Suppression, which weakens phonological representations, enhanced the concreteness effect with item scoring. In a matching task, positive effects of concreteness occurred with open sets but not with closed sets of words. Finally, concreteness effects reversed when the task asked only for recall of word positions (as in the matching task), when phonological representations were weak (because of suppression), and when lexical semantic representations overactivated (because of closed sets). We interpret these results as consistent with a model where phonological representations are crucial for the retention of order, while lexical-semantic representations support maintenance of item identity in both input and output buffers.

State-of-the-art of ‘Lean’ in the aviation maintenance, repair, and overhaul industry

The increasing need for maintenance, repair, and overhaul (MRO) organizations to meet customers' demands in quality and reduced lead times is key to its survival within the aviation industry. Furthermore, with the unpredictability in the global market and difficulties with forecasting characteristic of the MRO industry there is an increased need for the reevaluation of the operation models of organizations within this sector. However, severe economic turmoil and ever-increasing global competition introduce the opportunity for the adoption of a resilient, tried, and tested business operation model such as 'Lean'. In order to understand this concept, its long-term viability, and its application within the aerospace MRO sector fully, this paper presents the state-of-the-art in terms of the adoption of Lean within the MRO industry by carrying out a systematic review of the literature. This paper establishes the common perception of Lean by the MRO industry and the measurable progress that has been made on the subject. Some issues and challenges are also highlighted including the misconceptions that arise from the direct transference of the perception of Lean from other industrial sectors into the aerospace MRO industry. The 'enablers and inhibitors' of Lean within the aviation industry are also discussed. This paper exposes the scarcity of the literature and the general lagging behind of the industry to the adoption of the Lean paradigm and thus highlights areas where further research is required. © 2011 Authors.

Self-explanation in adaptive systems based on runtime goal-based models

The behaviour of self adaptive systems can be emergent, which means that the system’s behaviour may be seen as unexpected by its customers and its developers. Therefore, a self-adaptive system needs to garner confidence in its customers and it also needs to resolve any surprise on the part of the developer during testing and maintenance. We believe that these two functions can only be achieved if a self-adaptive system is also capable of self-explanation. We argue a self-adaptive system’s behaviour needs to be explained in terms of satisfaction of its requirements. Since self-adaptive system requirements may themselves be emergent, we propose the use of goal-based requirements models at runtime to offer self-explanation of how a system is meeting its requirements. We demonstrate the analysis of run-time requirements models to yield a self-explanation codified in a domain specific language, and discuss possible future work.

Automatic maintenance of category hierarchy

Category hierarchy is an abstraction mechanism for efficiently managing large-scale resources. In an open environment, a category hierarchy will inevitably become inappropriate for managing resources that constantly change with unpredictable pattern. An inappropriate category hierarchy will mislead the management of resources. The increasing dynamicity and scale of online resources increase the requirement of automatically maintaining category hierarchy. Previous studies about category hierarchy mainly focus on either the generation of category hierarchy or the classification of resources under a pre-defined category hierarchy. The automatic maintenance of category hierarchy has been neglected. Making abstraction among categories and measuring the similarity between categories are two basic behaviours to generate a category hierarchy. Humans are good at making abstraction but limited in ability to calculate the similarities between large-scale resources. Computing models are good at calculating the similarities between large-scale resources but limited in ability to make abstraction. To take both advantages of human view and computing ability, this paper proposes a two-phase approach to automatically maintaining category hierarchy within two scales by detecting the internal pattern change of categories. The global phase clusters resources to generate a reference category hierarchy and gets similarity between categories to detect inappropriate categories in the initial category hierarchy. The accuracy of the clustering approaches in generating category hierarchy determines the rationality of the global maintenance. The local phase detects topical changes and then adjusts inappropriate categories with three local operations. The global phase can quickly target inappropriate categories top-down and carry out cross-branch adjustment, which can also accelerate the local-phase adjustments. The local phase detects and adjusts the local-range inappropriate categories that are not adjusted in the global phase. By incorporating the two complementary phase adjustments, the approach can significantly improve the topical cohesion and accuracy of category hierarchy. A new measure is proposed for evaluating category hierarchy considering not only the balance of the hierarchical structure but also the accuracy of classification. Experiments show that the proposed approach is feasible and effective to adjust inappropriate category hierarchy. The proposed approach can be used to maintain the category hierarchy for managing various resources in dynamic application environment. It also provides an approach to specialize the current online category hierarchy to organize resources with more specific categories.