Search results

The well-operating condition of journal bearing is the assurance to keep superior performance of water-lubricated twin-screw compressor. To design the journal bearing more reasonably for this type of compressor, this paper aims to study the effects of rotating speed and design parameters on bearing characteristics, considering surface roughness and bending deformation of the shaft at the same time.

The average Reynolds equation considering the effect of surface roughness is adopted and solved by finite difference method and successive over-relaxation method to calculate pressure distribution with real bearing shapes and boundary conditions. The bending deformation of the shaft is calculated using simply supported beam model of variable cross-section.

The dynamic lubrication characteristics of four water-lubricated journal bearings in twin-screw air compressor are calculated and analyzed. In addition, the static characteristics of journal bearing including friction coefficient, film thickness ratio distribution and water film pressure distribution are calculated numerically with different rotating speed and design parameters. Moreover, some design principles of water-lubricated bearing for twin-screw compressor are put forward.

The lubrication characteristics of the water-lubricated journal bearing in twin-screw air compressor are calculated considering surface roughness and bending deformation of the shaft at the same time. The paper’s results may provide design guidelines for journal bearing in this kind of twin-screw compressor.

International investors have shown considerable recent interest regarding property investment in China via both direct and indirect property. The purpose of this paper is to assess the significance and performance of the China commercial property market compared to six developed and emerging commercial property markets in Asia.

This paper analyses the performance of commercial property in China over 1998‐2007 for both direct and indirect property. Risk‐adjusted performance analysis is used to assess the added value of China commercial property in a pan‐Asia portfolio, with the portfolio diversification benefits of China commercial property also assessed. Sub‐period analyses are also used to assess the dynamics of China commercial property.

This paper finds that China commercial property has shown significantly enhanced performance and diversification benefits in recent years. In a pan‐Asia property fund context, there are clear diversification benefits provided by China commercial property, with these benefits also being evident in the other Asian property markets. The findings highlight the benefits of a pan‐Asia property investment strategy by international property investors, as well as the key benefits and added‐value of including China commercial property in this pan‐Asia property investment strategy.

Previous empirical research into the China commercial property markets has been very limited. This paper rigorously assesses the role of China commercial property in a pan‐Asia property portfolio context. Given the increasing interest by the leading international property investors regarding investing in China commercial property, this research enables more informed and practical investment decision‐making regarding the role of both direct and indirect China commercial property as part of a pan‐Asia institutional property investment strategy.

The purpose of this paper is to deal with the problem of integration of production and maintenance policies. In this context, the authors consider production systems made of parallel machines producing a single product over a finite horizon made of equal periods for which a forecasted demand is known. The authors investigate the impact of switching production in case of failure of any given machine.

A mathematical model is first developed to find an optimal production plan which minimizes the average total storage, shortage and production costs. Then, using this optimal production plan and taking into account the influence of the production rate on the degradation of each machine, optimal preventive maintenance (PM) policies are proposed for the situations with and without switching.

Optimal production rates are determined for each production period and for each machine. Optimal PM periods are also computed for each machine.

Usually, in manufacturing systems, the production rate of a machine influences its failure rate. In case a machine fails, it takes a random time to repair it during which production is lost. The paper attempts to propose a switching policy (SP) according to which the lost production is compensated by all the other machines. The effects of the SP coupled with the PM strategy are shown through a numerical example.

Contrarily to previous works, the authors consider more realistic settings with a non-negligible random time for repairing failed machines. In order to compensate the lost production during the repair of a failed machine, a SP is proposed to transfer the load uniformly to all the other machines. As a result, those machines will produce at a higher production rate and will consequently have their failure rate increased. It will therefore be essential to determine an optimal PM schedule knowing that durations of these activities are not negligible. It is shown that the simultaneous implementation of periodic PM and load transfer in case of failure is the most economical integrated strategy.

The findings of this study have lightened the focal research areas in maintenance planning and scheduling. These also served as effective guidelines for future studies in this area. This research, therefore, contributes in fulfilling the gap by carrying out an SLR of contemporary research studies in the area of models for maintenance planning and scheduling. At present, SLR rooted in BA has not been carried focusing on a survey over models for maintenance planning and scheduling. SLR uses advanced scientific methodologies from BA tools to unveil thematic structures.

We have systematically reviewed over 1,021 peer-reviewed journal articles. Advanced contemporary tools from Bibliometric Analysis (BA) are used to perform a Systematic Literature Review (SLR). First, exploratory analysis is presented, highlighting the influential authors, sources and region amongst other key indices. Second, the large bibliographical data is visualized using co-citation network analyses, and research clusters (themes) are identified. The co-citation network is extended into a dynamic co-citation network and unveils the evolution of the research clusters. Last, cluster-based content analysis and historiographical analysis is carried out to predict the prospect of future research studies.

BA tools first outlined an exploratory analysis that noted influential authors, production countries, top-cited papers and frequent keywords. Later, the bibliometric data of over 1,021 documents is visualized using co-citation network analyses. Later, a dynamic co-citation analysis identified the evolution of research clusters over time. A historiographical direct citation analysis also unveils potential research directions. We have clearly observed that there are two main streams of maintenance planning and scheduling applications. The first has focused on joint maintenance and operations on machines. The second focused on integrated production and maintenance models in an echelon setting for unrealizable production facilities.

There are many literature review-based research studies that have contributed to maintenance scheduling research surveys. However, most studies have adopted traditional approaches, which often fall short in handling large bibliometric data and therefore suffer from selection biases from the authors. As a result, in this area, the existing reviews could be non-comprehensive. This study bridges the research gap by conducting an SLR of maintenance models, which to the best of our knowledge, has not been carried out before this study.

The purpose of this paper is to propose an empirical investigation targeting companies operating in Northern Italy and focusing on some main topics of maintenance.

Through a combined application of factor analysis and cluster analysis, the paper first identified the main approaches implemented by Italian companies with the purpose of preventing failures and reducing their consequences. Then, the paper grouped companies on the basis of such approaches, and derived the profile of each cluster, in terms of both the company's characteristics and some key maintenance elements, including the maintenance policy or the use of advanced techniques to make maintenance interventions more effective.

Results of this study suggest that the approach to maintenance management could be related to the implementation of specific maintenance policies, as well as to other topics, such as the company characteristics, the use of advanced techniques for enhancing maintenance effectiveness and the criteria used for selecting the maintenance policy.

The sample of companies investigated in this study is quite limited, and prevented the possibility of providing statistical evidence of all outcomes.

The outcomes of this study can be useful for practitioners to understand the positioning of companies towards the implementation of maintenance policies, as a function of their approach to maintenance management.

This study complements previous empirical works on maintenance by exploring the relationships between maintenance management, maintenance policies, the application of different tools and techniques for maintenance management, and the criteria adopted for the maintenance policy selection.

The purpose of this paper is to consider various possible constraints of the problem of production and maintenance planning control for a multi-machine under subcontracting constraint, in order to bring the manufacturer industry closer to real mode. In this paper, we present an efficient and feasible optimal solution, by comparing optimization procedures.

Our manufacturing system is composed of parallel machines producing a single product, to satisfy a random demand under a given service level. In fact, the demand is greater than the total capacity of the set of machines; hence there rises a necessity of subcontracting to complete the missing demand. In addition, we consider that the unit cost of subcontracting is a variable depending on the quantity subcontracted. As a result, we have developed a stochastic optimal control model. Then, to solve the problem we compared three optimization methods: (exact/approximate), the genetic algorithm (GA), the Pattern Search (PS) and finally fmincon. Thus, we validate our approach via a numerical example and a sensitivity analysis.

This paper defines an internal production plan, a subcontracting plan and an optimal maintenance strategy. The optimal solution presented in this paper significantly improves the ability of the decision maker to consider larger instances of the integrated model. In addition, the decision maker can answer the following question: Which is the most optimal subcontractor to choose?

The approach developed deals with the case of the real-mode manufacturing industry, taking into consideration different constraints and determining decision variables which allow it to expand the profits of the manufacturing industry in different domains such as automotive, aeronautics, textile and pharmacies.

This paper is one of the few documents dealing with the integrated maintenance in subcontracting constraint production which considers the complex aspect of the multi-machine manufacturing industry. We also dealt with the stochastic aspect of demand and failures. Then, we covered the impact of the unit cost variation of subcontracting on the total cost. Finally, we shed light on a comparison between three optimization methods in order to arrive at the most optimal solution.

Highly anisotropic zirconium is a material used in the cladding of nuclear fuel rods, ensuring containment of the radioactive material within. The complex material structure of anisotropic zirconium requires model developers to replicate not only the macro-scale stresses but also the meso-scale material behavior as the crystal structure evolves; leading to strongly coupled multi-scale plasticity models. Such strongly coupled models can be achieved through partitioned analysis techniques, which couple independently developed constituent models through an iterative exchange of inputs and outputs. Throughout this iterative process, biases, and uncertainties inherent within constituent model predictions are inevitably transferred between constituents either compensating for each other or accumulating during iterations. The paper aims to discuss these issues.

A finite element model at the macro-scale is coupled in an iterative manner with a meso-scale viscoplastic self-consistent model, where the former supplies the stress input and latter represents the changing material properties. The authors present a systematic framework for experiment-based validation taking advantage of both separate-effect experiments conducted within each constituent’s domain to calibrate the constituents in their respective scales and integral-effect experiments executed within the coupled domain to test the validity of the coupled system.

This framework developed is shown to improve predictive capability of a multi-scale plasticity model of highly anisotropic zirconium.

For multi-scale models to be implemented to support high-consequence decisions, such as the containment of radioactive material, this transfer of biases and uncertainties must be evaluated to ensure accuracy of the predictions of the coupled model. This framework takes advantage of the transparency of partitioned analysis to reduce the accumulation of errors and uncertainties.

Opportunistic and delayed maintenances are increasingly becoming important strategies for sustainable maintenance practices since they increase the lifetime of complex systems like aircrafts and heavy equipment. The objective of the current study is to quantify the optimal time window for adopting these strategies.

The current study considers the trade-offs between different costs involved in the opportunistic and delayed maintenances (of equipment) like the fixed cost of scheduled maintenances, the opportunistic rewards that may be earned and the cost of premature parts replacement. The probability of the opportunistic maintenance has been quantified under two different scenarios – Mission Reliability and Renewal Process. In the case of delayed maintenance, the cost of the delayed maintenance is also considered. The study uses optimization techniques to find the optimal maintenance time windows and also derive useful insights.

Apart from finding the optimal time window for the maintenance activities the study also shows that opportunistic maintenance is beneficial provided the opportunistic reward is significantly large; the cost of conducting scheduled maintenance in the pre-determined slot is significantly large. Similarly, the opportunistic maintenance may not be beneficial if the pre-mature equipment parts replacement cost is significantly high. The optimal opportunistic maintenance time is increasing function of Weibull failure rate parameter “beta” and decreasing function of Weibull failure rate parameter “theta.” In the case of optimal delayed maintenance time, these relationships reverse.

To the best of our knowledge, very few studies exist that have used mission reliability to study opportunistic maintenance or considered the different cost trade-offs comprehensively.

This paper deals with a particular type of leasing contracts according to which an equipment is leased for free with the condition for the lessee to purchase a predetermined minimum quantity of consumables during each leasing period. Maintenance actions are performed by the lessor and borne by him. Imperfect preventive maintenance is carried out every t time units throughout the leasing period. Minimal repairs are performed following equipment failures. At the end of the leasing period, an overhaul which restores the equipment to “as good as new” state is performed. The equipment is leased many times during its life cycle. The purpose of this paper is to determine the values of the decision variables for the lessor, which are the preventive maintenance (PM) period and the minimum quantity of consumables to be sold to ensure profit.

A mathematical model is developed to express the expected maintenance cost per time unit incurred by the lessor as well as his expected profit over the equipment life cycle. The optimal PM period minimizing the maintenance cost is determined first. Then, given the corresponding minimum maintenance cost, the minimum quantity of consumables (the lessor's break-even point) to be purchased by the lessee is computed. A numerical example and a sensitivity study are presented, and the obtained results are discussed.

The outcome of this work is supposed to help the lessors determining two key values to be included in each leasing contract, namely: (1) the periodicity according to which they will commit to perform preventive maintenance actions such that their average total cost of maintenance is minimized, (2) the minimum quantity of consumables that the lessee must commit to purchasing during the leasing period. This quantity must be between the break-even point and the maximum quantity associated with the capacity of the equipment.

Practically, the objective of this work is first to determine the optimal strategy to be adopted by the lessor in terms of effort relating to PM and second to determine the minimum quantity of consumables that the lessee must purchase during the leasing period such as profit is insured for the lessor.

This type of leasing (for free) has not been addressed in the literature particularly when considering maintenance strategies.