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The aim of this research is to determine the optimal upgrade and preventive maintenance actions that minimize the total expected cost (maintenance costs+penalty costs).

The problem is a four‐parameter optimization with two parameters being k‐dimensional. The optimal solution is obtained by using a four‐stage approach where at each stage a one‐parameter optimization is solved.

Upgrading action is an extra option before the lease of used equipment, in addition to preventive maintenance action. Upgrading action makes equipment younger and preventive maintenance action lowers the ROCOF.

There is a growing trend towards leasing equipment rather than owning it. The lease contract contains penalties if the equipment fails often and repairs are done within reasonable time period. This implies that the lessor needs to look at optimal preventive maintenance strategies in the case of new equipment lease, and upgrade actions plus preventive maintenance in the case of used equipment lease. The paper deals with this topic and is of great significant to business involved with leasing equipment.

Nowadays many organizations are interested in leasing equipment and outsourcing maintenance. The model in this paper addresses the preventive maintenance problem for leased equipment. It provides an approach to dealing with this problem.

Purpose – This article examines the operating lease cost stickiness characteristics exhibited by retail firms.

Methodology/approach – Anderson, Banker, and Janakiraman (2003) laid important groundwork for the study of asymmetric cost behavior or cost stickiness. The authors found that a firm’s selling, general, and administrative costs (SG&A) costs increase more with a sales increase than those expenses decrease with an equivalent sales decline. Their findings provided avenues for many studies with differing focal variables; however, extant research has not explored the degree of cost stickiness associated with operating lease expenses. Recognizing the nature and magnitude of operating leases and the competitive and changing environment for retailers, this study adapts Anderson et al.’s (2003) model to provide insights into operating lease stickiness. The study uses archival financial data from 1997 through 2016 for specialty retail firms in testing the lease cost stickiness hypotheses.

Findings – The results of this study supported the hypotheses that operating lease expenses exhibit stickiness behavior and are relatively stickier than future lease commitments for retail firms.

Originality/value – By focusing on retail firms and related lease expenses, this study provides insights into the increasingly competitive retailer environment. This article’s findings will enhance understanding of how specialty retail firms’ managers react to reduced revenues. Finally, given recent authoritative pronouncements affecting accounting for leases and the significance of leasing transactions, research providing insights into cost behavior and managerial actions stands to make an important contribution to literature and practice.

The purpose of this paper is to present a decision model for second-hand products to determine the optimal upgrade level, warranty period and preventive maintenance (PM) effort level which maximize the total expected profit generated by the dealer considering any given past age of the product and the effect of the sales volume.

A mathematical model is developed to derive the optimal triplet: upgrade level, warranty period and PM effort level, which maximize the total expected profit generated by the dealer for any second-hand product with a given past age. Numerical experimentations have been conducted to investigate the effectiveness of the proposed model and to explore the interactions among the model variables.

Numerical experimentations including a sensitivity analysis have been conducted on the model key parameters. The obtained results show that performing PM actions during the warranty period helps the dealers to provide extended warranty for older second-hand products without spending a significant effort on upgrade actions and therefore increase the volume of sales. Also, the interaction between the PM level and the profit margin threshold is demonstrated. Finally, the effect of the sales volume function parameters (the price and warranty elasticity parameters) on the optimal solution is characterized.

Given the complexity of the profit function to be maximized involving a considerable number of decision variables with different nature, the authors limited the study to the case where the past age of the second-hand product is known.

The proposed model aims to provide second-hand product dealers with a modeling framework that enables them to have a realistic estimation of the generated profit by integrating the marketing and engineering key parameters of the second-hand product.

Most of the existing literature dealing with the reliability improvement of second-hand products does not take into account the fact that a realistic estimation of the total profit generated by the dealer requires the consideration of the sales volume. The latter is closely related to the marketing parameters characterized by the warranty period length and the second-hand product selling price. The proposed model introduces the effect of the total sales volume on the total expected profit. The authors also introduce the concept of discrete upgrade levels for a better control of the restoration degree. The authors study the impact of warranty and price elasticity parameters on the optimal solution and the resultant interaction with the customer purchase decision and consequently the sales volume.

Load haul dumper (LHD) is one of the main ore transporting machineries used in underground mining industry. Reliability of LHD is very significant to achieve the expected targets of production. The performance of the equipment should be maintained at its highest level to fulfill the targets. This can be accomplished only by reducing the sudden breakdowns of component/subsystems in a complex system. The identification of defective component/subsystems can be possible by performing the downtime analysis. Hence, it is very important to develop the proper maintenance strategies for replacement or repair actions of the defective ones. Suitable maintenance management actions improve the performance of the equipment. This paper aims to discuss this issue.

Reliability analysis (renewal approach) has been used to analyze the performance of LHD machine. Allocations of best-fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K–S) test. Parametric estimation of theoretical probability distributions was made by utilizing the maximum likelihood estimate (MLE) method.

Independent and identical distribution (IID) assumption of data sets was validated through trend and serial correlation tests. On the basis of test results, the data sets are in accordance with IID assumption. Therefore, renewal process approach has been utilized for further investigation. Allocations of best-fit distribution of data sets were made by the utilization of Kolmogorov–Smirnov (K–S) test. Parametric estimation of theoretical probability distributions was made by utilizing the MLE method. Reliability of each individual subsystem has been computed according to the best-fit distribution. In respect of obtained reliability results, the reliability-based preventive maintenance (PM) time schedules were calculated for the expected 90 percent reliability level.

As the reliability analysis is one of the complex techniques, it requires strategic decision making knowledge for the selection of methodology to be used. As the present case study was from a public sector company, operating under financial constraints the conclusions/findings may not be universally applicable.

The present study throws light on this equipment that need a tailored maintenance schedule, partly due to the peculiar mining conditions, under which they operate. This study mainly focuses on estimating the performance of four numbers of well-mechanized LHD systems with reliability, availability and maintainability (RAM) modeling. Based on the drawn results, reasons for performance drop of each machine were identified. Suitable recommendations were suggested for the enhancement of performance of capital intensive production equipment. As the maintenance management is only the means for performance improvement of the machinery, PM time intervals were estimated with respect to the expected rate of reliability level.

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.

The purpose of this paper is to review the literature on maintenance management and suggest possible gaps from the point of view of researchers and practitioners.

The paper systematically categorizes the published literature and then analyzes and reviews it methodically.

The paper finds that important issues in maintenance management range from various optimization models, maintenance techniques, scheduling, and information systems etc. Within each category, gaps have been identified. A new shift in maintenance paradigm is also highlighted.

Literature on classification of maintenance management has so far been very limited. This paper reviews a large number of papers in this field and suggests a classification in to various areas and sub areas. Subsequently, various emerging trends in the field of maintenance management are identified to help researchers specifying gaps in the literature and direct research efforts suitably.

The paper contains a comprehensive listing of publications on the field in question and their classification according to various attributes. The paper will be useful to researchers, maintenance professionals and others concerned with maintenance to understand the importance of maintenance management

The purpose of this paper is to review the literature on maintenance optimization models and associated case studies. For these optimization models critical observations are made.

The paper systematically classifies the published literature using different techniques, and also identifies the possible gaps.

The paper outlines important techniques used in various maintenance optimization models including the analytical hierarchy process, the Bayesian approach, the Galbraith information processing model and genetic algorithms. There is an emerging trend towards uses of simulation for maintenance optimization which has changed the maintenance view.

A limited literature is available on the classification of maintenance optimization models and on its associated case studies. The paper classifies the literature on maintenance optimization models on different optimization techniques and based on emerging trends it outlines the directions for future research in the area of maintenance optimization.

The paper provides many references and case studies on maintenance optimization models and techniques. It gives useful references for maintenance management professionals and researchers working on maintenance optimization.