Life cycle optimization has been a concern over decades; it has been clear that an asset well-kept will have a longer life with a higher return for the organization; this life cycle depends of several factors. The standard ISO 55001 defines a set of requirements that, when implemented and maintained, guarantee the good performance of an organization's asset management, responding to stakeholders need and expectations and ensuring the value creation and maintenance as well as a global vision of assets on the Optimizing the Life Cycle of Physical Assets. The organizations where physical asset management is of major importance include all those that involves facilities, machinery, buildings, roads and bridges, utilities, transportation industries, oil and gas extraction and processing, mining and mining processing, chemicals, manufacturing, distribution, aviation and defence. However, since ISO 55001 is a new standard in the global market, due to its necessity to involve all the organization its implementation becomes difficult; but, it is clear that an organization that certifies by the ISO 55001 is ahead on life cycle optimization because it is part of its requirements; so, what model of life cycle optimization to use? Is there anyone that fits on the ISO 55001? Can an existing one be adapted to be used according to ISO 55001 requirements? The approaches of this paper bring a literary review of life cycle models used in asset management and their major concerns, this is the beginning to build a model to optimize the life cycle of physical assets including the ISO 55001 perspective.

Circular economy arises at a time when the needs for the reduction, reuse, recovery and recycling of materials and energy need to consolidate. Today's economy is unsustainable in the short run. The standard ISO 55001 defines a set of requirements that, when implemented and maintained, guarantee the good performance of an organization's asset management, responding to stakeholder needs and expectations and ensuring the value creation and maintenance as well as a global vision of assets in a circular economy.The organizations where physical asset management is of major importance include all those that involve: facilities, machinery, buildings, roads and bridges, utilities, transportation industries; oil and gas extraction and processing; mining and mining processing; chemicals, manufacturing, distribution, aviation and defence.However, since ISO 55001 is a new standard in the global market, because it is intrinsically difficult to implement, a diagnostic model on the state of organizations can greatly help on the implementation. This paper proposes a diagnostic model to evaluate the state of the organizations in relation to their potential to implement the ISO 55001. The diagnosis allows to identify the aspects of the organization that are ready to receive the new standard, as well of the critical, the fragile and the weak points of the company that must be corrected.The diagnostic model is based on surveys, with several questions and with five possible answers. Each possibility of response has a quantification and a critical classification.The final result is a global positioning of the company with the identification of the various aspects to be corrected in order to be possible to implement the ISO 55001. A radar chart provides a global "radiography" of the company diagnosis.The diagnostic template has been validated and the results are presented in the paper.

Usually, the Reserve Fleet, or Spare Fleet, of passenger urban buses, is based on indicators used in some international relevant companies and extrapolated for many others, almost as a dogma. However, it must be taken into consideration pragmatic variables intrinsic to the buses namely their maintenance and in a more pragmatic approach, indexing their availability and by consequence the reserve fleet indexed to the maintenance policy used in each company. The paper discusses these subjects and presents a global model that integrates the maintenance planning policy, based on a condition monitoring model, maintenance Key Maintenance Indicators (KPI), and an economic life cycle model. The paper presents some results based both in theoretical considerations and also in real data from an urban fleet of a European Countr