Obsolescence management for long-life contracts: State of the art and future trends

This paper provides a comprehensive literature review on the problem of obsolescence in “sustainment-dominated systems” that require support for many decades. Research on this topic continues to grow as a result of the high impact of obsolescence on the in-service phase of long-term projects. Research on obsolescence also seeks to understand how it can be managed, mitigated and resolved. The paper aims to clarify and classify the different activities that may be included in an obsolescence management planning, taking into account not only electronic components but also other aspects of the system such as mechanical components, software, materials, skills and tooling. The literature review shows that although there are many commercial tools available that support the obsolescence management during the in-service phase of the life cycle of a system, little research has been done to forecast the costs incu

FMECA-Based Risk Assessment Approach for Proactive Obsolescence Management

Part 4: Analytics in the Order Fulfillment ProcessInternational audienceOne of the most critical issues that can affect the useful life of a product is the obsolescence of its components or functionalities. To minimize its effects and bring long-term benefits to systems, obsolescence must be proactively managed. A critical step in the process of proactive obsolescence management is the obsolescence risk analysis of critical components or functionalities. However, estimating the degree of obsolescence of multi-component systems is an area that is still under-explored, particularly when interdependencies exist between components. This estimation can be more complicated where there is no prior knowledge about the interaction between components. We used Weibull’s distribution to model the components’ interaction and calculate the obsolescence degree of the global system. This approach is evaluated using a numerical example based on a meteorological data acquisition system. The obsolescence of main components of this system is modeled while taking into account the interaction between them. Results are presented and discussed while clarifying the scientific issues that should be tackled in future works

Field-Reliability Predictions Based on Statistical System Lifecycle Models

Part 1: MAKE-Main TrackInternational audienceReliability measures the ability of a system to provide its intended level of service. It is influenced by many factors throughout a system lifecycle. A detailed understanding of their impact often remains elusive since these factors cannot be studied independently. Formulating reliability studies as a Bayesian regression problem allows to simultaneously assess their impact and to identify a predictive model of reliability metrics.The proposed method is applied to currently operational particle accelerator equipment at CERN. Relevant metrics were gathered by combining data from various organizational databases. To obtain predictive models, different supervised machine learning algorithms were applied and compared in terms of their prediction error and reliability. Results show that the identified models accurately predict the mean-time-between-failure of devices – an important reliability metric for repairable systems - and reveal factors which lead to increased dependability. These results provide valuable inputs for early development stages of highly dependable equipment for future particle accelerators

The bioenergetics of inflammation: insights into obesity and type 2 diabetes

Diabetes mellitus is one of the most common chronic metabolic disorders worldwide, and its incidence in Asian countries is alarmingly high. Type 2 diabetes (T2DM) is closely associated with obesity, and the staggering rise in obesity is one of the primary factors related to the increased frequency of T2DM. Low-grade chronic inflammation is also accepted as an integral metabolic adaption in obesity and T2DM, and is believed to be a major player in the onset of insulin resistance. However, the exact mechanism(s) that cause a persistent chronic low-grade infiltration of leukocytes into insulin-target tissues such as adipose, skeletal muscle and liver are not entirely known. Recent developments in the understanding of leukocyte metabolism have revealed that the inflammatory polarization of immune cells, and consequently their immunological function, are strongly connected to their metabolic profile. Therefore, it is hypothesized that dysfunctional immune cell metabolism is a central cellular mechanism that prevents the resolution of inflammation in chronic metabolic conditions such as that observed in obesity and T2DM. The purpose of this review is to explore the metabolic demands of different immune cell types, and identify the molecular switches that control immune cell metabolism and ultimately function. Understanding of these concepts may allow the development of interventions that can correct immune function and may possibly decrease chronic low-grade inflammation in humans suffering from obesity and T2DM. We also review the latest clinical techniques used to measure metabolic flux in primary leukocytes isolated from obese and T2DM patients.European Journal of Clinical Nutrition advance online publication, 12 April 2017; doi:10.1038/ejcn.2017.45