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Life cycle analysis (LCA) is more and more used in the context of electromagnetic product design. But it is often used to check a design solution regarding environmental impacts after technical and economical choices. This paper aims to investigate life cycle impact optimization (LCIO) and compare it with the classical life cycle cost optimization (LCCO).

First, a model of a dry-type transformer using different materials for windings and the magnetic core is presented. LCCO, which is a mixed continuous-discrete, multi-objective technico-economic optimization, is done using both deterministic and genetic algorithms. LCCO results and optimization performances are analyzed, and an LCA is presented for a set of optimal solutions. The final part is dedicated to LCIO, where the paper shows that these optimal solutions are close to those obtained with LCCO.

This paper investigated LCIO using an environmental impacts model that has been introduced in the optimization framework Component Architecture for the Design of Engineering Systems. The paper shows how a mixed continuous-discrete, multi-objective technico-economic optimization can be done using an efficient deterministic optimization algorithm such as Sequential Quadratic Programming. Thanks to the technico-economic-environmental model and the efficient optimization algorithm, both LCCO and LCIO were performed separately and together. It has been shown that optimal solutions are similar, leading to the conclusion that only one modeling is required (economic or environmental) but on the life cycle.

The classical sequential methodology of design is improved here by the use of a model of calculation of the environmental impacts allowing the optimization. This original optimization allowed the authors to show that an analysis of the life cycle from an economic point of view or from an environmental point of view led to quasi-equivalent technical solutions. The key is to take into account the life cycle of the product.

The purpose of this paper is to demonstrate that the result of an optimisation via life cycle costs (LCC) depends on the assumptions made throughout the process of calculating LCC.

A framework is used to structure the assumptions made in the process of calculating LCC. These include the following three pairs: technical versus economic life‐span, static versus dynamic calculation method or costs only versus income minus costs. In a broader sense, these LCC are referred to as the life cycle economy (LCE). Two case studies form the basis for the LCC calculations. Using different assumptions, the LCC of virtual design variations of these buildings are compared to each other.

The rankings drawn from the calculations differ according to the chosen calculation method, i.e. the chosen variation for the optimisation of a building is not consistent.

This is essentially an exploratory study and the prognosis of future cash flow in relation to certain design variations requires further research.

The credibility of life cycle costing should improve with a greater transparency of assumptions in the context of the outlined framework.

All players in facilities management who support their decisions with LCC will benefit from this quantification of the impact of different calculation methods. The extension of LCC to LCE will help planners, investors and owners of real estate in evaluating building options with respect to quality, image, flexibility or comfort.

Reliability analysis is required to identify the components or subsystems with low reliability for a given designed performance. Life cycle cost analysis helps understand the cost implications over the entire life span of a product. The purpose of this paper is to present a case study describing reliability analysis and life cycle cost optimization of a band saw cutting machine manufactured and used in India.

The data required for reliability analysis is collected from the manufacturer and users of band saw cutting machine. The parameters of failure distribution have been estimated by using ReliaSoft’s Weibull++6 software. The life cycle cost is divided into various cost elements such as acquisition cost, operation cost, failure cost, support cost and net salvage value.

The results of the analysis show that the components such as band wheel bearing, guide roller bearing, limit switch, carbide pad, hydraulic cylinder oil seal, control panel dial, control panel and solenoid valve are critical from reliability and life cycle cost analysis perspective.

With certain design changes it is found that the reliability of the system is increased by 15.85 percent while the life cycle cost is reduced by 22.09 percent. The study also shows that the reliability analysis is useful for deciding maintenance intervals.

The purpose of this paper is to eliminate the wastes and inefficient procedures in the maintenance organization of aircraft so as to reduce its downtime and increase mission availability.

Customized lean Six Sigma (LSS) was applied at the task level and servicing cycle level to reduce the task content, cycle length and resources in servicing. The loading of the servicing facility was simulated through a simulation program developed from a statistical analysis of historical data for validating/simulating/determining optimum loading of servicing facility with refined tasks, reduced cycle length and resources. In simulation, the optimum combination of manpower, resources and infrastructure at the facility level was determined through sensitive analysis and design of experiments (DoE).

Optimization at the task level and its re-organization at the servicing cycle level reduced the cycle length by 55-68 per cent and manpower resources by 26 per cent. This further reduced facility-level manpower by 25 to 40 per cent, capacity requirements by more than 33 per cent and annual aircraft downtime by 78 per cent. The approach reduced the average number of aircraft undergoing servicing at each airbase at any time from 2.35 to just 0.76 and increased the mission availability to 20 per cent.

The hallmark of the paper has been the design of LSS approach from structured historical data and its validation through innovative simulation. The multi-pronged bottom-up approach practically bundles all wastes resident in the maintenance organization. The paper provides cursory approach to lean practitioners in the elimination of wastes in the maintenance of capital assets like aircraft.

The aim of this study is to assess the opportunity for the development of hydrocarbon transportation using high-strength steel (HSS) in pipeline construction in terms of cost savings and reliability.

Several optimizations of pipeline design and operations were performed to estimate the total life-cycle cost variation associated with different grades of high-strength steel. The generalized reduced gradient (GRG) method was used in an Excel table to determine optimal total life cycle each pipeline. Variables used in this optimization with respect to each steel grade were as follows: pipeline external diameter, wall thickness, number of compression stations and installed power in each compression station. The reliability of a pipeline with optimal cost was assessed to highlight the impact of steel grade on pipeline reliability.

The study showed that the cost reduction is strongly dependent on the adopted gas pipeline configuration. The number of compression stations and external diameter are the main factors influencing the pipeline total life cycle cost, while the steel price seems to have a minor effect, the reduction of the gas pipeline total life cycle does not exceed 5% even with a 50% difference in pipe steel prices between X70 and X100 steels. On the other side, for the same external diameter, X100 steel presents better pipeline reliability against carbonic corrosion compared to X70 steel.

The main contribution of this study is to provide a decision-support tool to help pipeline constructors enhance the profitability of natural gas transmission pipelines. The optimization method used is simple to use for design engineers during a feasibility study.

The present study presents one step to fill the gap concerning the question of balancing the trade-off between cost savings and structural reliability in high-strength steel pipelines during the early stages of feasibility studies. The optimal design and operations parameters ensuring cost savings on total life cycle costs are identified via an optimization method. The impact of selected optimal parameters on the long-term pipeline service life was estimated via a structural reliability analysis.

Continuous improvement is a cyclic process of product and process optimization over a product life cycle. Optimization is beyond quality and reliability management – meaning, an organization is keeping in constant touch with new technological advances and frequently employs the applicable technologies to improve an existing product. Cycling means that an organization is continually exploring new frontiers in manufacturing technologies. The latest advances in related fields such as computers and systems are reviewed regularly for possible inclusion in the produced and process optimization cycle. Today, there is no single unique structure or process that defines “continuous improvement”, or, in a larger sense, what is described here as product and process optimization (PPO). Outlines a new structured approach to product and process optimization which includes, in addition to change management, three sets of metrics and measurements. PPO is a function of life‐cycle management. There are three aspects of life‐cycle management applicable to manu‐facturing and service industries: managing reprocessing, restructuring or re‐engineering change; managing continuity; and managing revision change.

Transportation infrastructure asset management has long been an active but challenging problem for agencies, which urges to maintain a good state of their assets but faces budgetary limitations. Managing a network of transportation infrastructure assets, especially when the number is large, is a multifaceted challenge. This paper aims to develop a life-cycle cost analysis (LCCA) based transportation infrastructure asset management analytical framework to study the impacts of a few key parameters/factors on deterioration and life-cycle cost. Using the bridge as an example infrastructure type, the framework incorporates an optimization model for optimizing maintenance, repair, rehabilitation (MR&R) and replacement decisions in a finite planning horizon.

The analytical framework is further developed through a series of model variations, scenario and sensitivity analysis, simulation processes and numerical experiments to show the impacts of various parameters/factors and draw managerial insights. One notable analysis is to explicitly model the epistemic uncertainties of infrastructure deterioration models, which have been overlooked in previous research. The proposed methodology can be adapted to different types of assets for solving general asset management and capital planning problems.

The experiments and case studies revealed several findings. First, the authors showed the importance of the deterioration model parameter (i.e. Markov transition probability). Inaccurate information of p will lead to suboptimal solutions and results in excessive total cost. Second, both agency cost and user cost of a single facility will have significant impacts on the system cost and correlation between them also influences the system cost. Third, the optimal budget can be found and the system cost is tolerant to budge variations within a certain range. Four, the model minimizes the total cost by optimizing the allocation of funds to bridges weighing the trade-off between user and agency costs.

On the path forward to develop the next generation of bridge management systems methodologies, the authors make an exploration of incorporating the epistemic uncertainties of the stochastic deterioration models into bridge MR&R capital planning and decision-making. The authors propose an optimization approach that does not only incorporate the inherent stochasticity of bridge deterioration but also considers the epistemic uncertainties and variances of the model parameters of Markovian transition probabilities due to data errors or modeling processes.

The purpose of this paper is to develop a practical economic replacement decision model to identify the economic lifetime of the ventilation system used by Trafikverket in its Stockholm tunnels.

The proposed data-driven optimisation model considers operating and maintenance costs, purchase price and system resale value for a ventilation system consisting of 121 fans. The study identified data quality problems in Trafikverket’s MAXIMO database.

It is found that the absolute economic replacement time (ERT) of the ventilation system is 108 months but for a range of 100–120 months, the total cost remains almost constant. Sensitivity and regression analysis showed that the operating cost has the largest impact on the ERT.

The results are promising; the company has the possibility of significantly reducing the LCC of the ventilation system by optimising its lifetime. In addition, the proposed model can be used for other systems with repairable components, making it applicable, useful and implementable within Trafikverket more generally.

The modern helicopters are designed with maximum serviceability and long life expectancy to ensure minimum life cycle cost. The purpose of this paper is to present a framework to incorporate the customer requirements on reliability and maintainability (R&M) parameters into the design and development phase of a contemporary helicopter, and to discuss the way to capture operational data to establish and improve the R&M parameters to reduce life cycle cost.

From the analysis, it is established that the reliability and maintainability cost is the major contributor to the life cost. The significant reliability and maintainability parameters which influence R&M cost are identified from analysis. The operational and design data of a contemporary helicopter are collected, compiled and analyzed to establish and improve the reliability and maintainability parameters.

The process depicted in the paper is followed for a contemporary helicopter and substantial amount of life cycle cost reduction is observed with improvement of R&M parameters.

The benefits of this methodology not only reduce life cycle cost but also improve the availability/serviceability through less failure and less time for scheduled maintenance. The methodologies also provide the reliability trends indicating potential area for design improvement.

The proposed approach assists asset managers to reduce the life cycle costs through improvement of R&M parameters.

Despite existing life cycle costing (LCC) method descriptions and practicable suggestions for conducting LCC analyses, no systematic analyses on actual implementations of LCC methods exist. This paper aims to review reports on LCC applications to provide an overview of LCC uses and implementation feasibility.

A review of LCC cases reported in academic and practitioner literature. Case reports were compared against one another and against the defining articles in the field.

Most of the reported LCC applications were far from ideal. Compared to the methods suggested in the literature many of the case study applications: covered fewer parts of the whole life cycle, estimated the costs on a lower level of detail, used cost estimation methods based on expert opinion rather than statistical methods, and were content with deterministic estimates of life cycle costs instead of using sensitivity analyses.

This review is limited to reported LCC applications only. Further research is encouraged in the form of a field‐based multiple‐case study to reveal context‐specific dimensions of LCC analysis and implementation challenges in more detail.

This review highlights the difficulty of conducting a reliable LCC analysis, and points out typical problems that should be carefully considered before drawing conclusions from the LCC analysis.

First systematic analysis of LCC applications that gives directions for further research on the LCC concept.