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Utilization of off‐highway vehicles forms an essential part of UK industry's efforts to augment the productivity of plant operations and reduce production costs. However, uninterrupted utilization of plant and equipment is requisite to reaping the maximum benefit of mechanization; one particular problem being plant breakdown duration and its impact upon process productivity. Predicting the duration of plant downtime would enable plant managers to develop suitable contingency plans to reduce the impact of downtime. This paper presents a stochastic mathematical modelling methodology (more specifically, probability density function of random numbers) which predicts the probable magnitude of ‘the next’ breakdown, in terms of duration for tracked hydraulic excavators. A random sample of 33 machines was obtained from opencast mining contractors, containing 1070 observations of machine breakdown duration. Utilization of the random numbers technique will engender improved maintenance practice by providing a practical methodology for planning, scheduling and controlling future plant resource requirements. The paper concludes with direction for future research which aims to: extend the model's application to cover other industrial settings and plant items; to predict the time at which breakdown will occur (vis‐à‐vis the duration of breakdown); and apply the random numbers modelling to individual machine compartments.

The purpose of this paper is to develop a stochastic detailed schedule for a preventive/scheduled/periodic maintenance program of a military aircraft, specifically a rotorcraft or helicopter.

The new model, entitled the military “periodic aviation maintenance stochastic schedule” (PAM-SS), develops a stochastic detailed schedule for a PUMA SA 330SM helicopter for the 50-h periodic inspection, using cyclic operation network (CYCLONE) and Monte Carlo simulation (MCS) techniques. The PAM-SS model identifies the different periodic inspection tasks of the maintenance schedule, allocates the resources required for each task, evaluates a stochastic duration of each inspection task, evaluates the probability of occurrence for each breakdown or repair, develops the CYCLONE model of the stochastic schedule and simulates the model using MCS.

The 50-h maintenance stochastic duration follows a normal probability distribution and has a mean value of 323 min and a standard deviation of 23.7 min. Also, the stochastic maintenance schedule lies between 299 and 306 min for a 99 per cent confidence level. Furthermore, except the pilot and the electrical team (approximately 90 per cent idle), all other teams are around 40 per cent idle. A sensitivity analysis is also performed and yielded that the PAM-SS model is not sensitive to the number of technicians in each team; however, it is highly sensitive to the probability of occurrence of the breakdowns/repairs.

The PAM-SS model is specifically developed for military rotorcrafts, to manage the different resources involved in the detailed planning and scheduling of the periodic/scheduled maintenance, mainly the 50-h inspection. It evaluates the resources utilization (idleness and queue), the stochastic maintenance duration and identifies backlogs and bottlenecks.

The PAM-SS tackles military aircraft planning and scheduling in a stochastic methodology, considering uncertainties in all inspection task durations and breakdown or repair durations. The PAM-SS, although developed for rotorcrafts can be further developed for any other type of military aircraft or any other scheduled maintenance program interval.

The boiler pressure parts are a major asset of a power station, and the maintenance cost is often accountable for a huge portion of the annual budget. In the power generation industry, the outage costs due to loss of production, both planned or forced, are very significant and thus it is of interest to seek for a meaningful approach to the management of boiler pressure parts maintenance such that the enterprise performance is optimised. This paper aims to do this.

This paper proposes a framework that introduces the division of the enterprise objectives into the three decision dimensions. The framework is applied to the case of power station boiler pressure parts maintenance to optimise maintenance outages decisions for Loy Yang, a power station in Victoria, Australia.

The study finds that the framework provides meaningful approach to optimising maintenance decisions and is generic for application in different cases.

The paper provides a new insight and integrated approach to optimising asset maintenance for an enterprise with the use of a case study.

This paper describes industrial research in which the implementation of a computerised maintenace management system (CMMS) was used as an effective tool that supports decision making with the objective of acheiving world‐class manufacturing status. Breakdown trends and performance levels were analysed in a continuous improvement environment. Critical performance measures were then identified and these became the driving force for specific benchmarking metrics and improvement techniques which enabled approaches to eliminate breakdown losses to be formulated. Data collected were analysed using a multiple criteria decision making (MCDM) methodology and the MCDM technique was implemented into the software in order to add value to the data. This gave increased support to decision making and enabled appropriate maintenance strategies to be implemented.

The introduction of advanced manufacturing technologies can result in prolonged start‐up phases long after commercial production has started up. Progress of manufacturing performance is often prevented owing to extensive start‐up losses, giving rise to uncertainty. Based on a longitudinal case study of a Swedish manufacturer of engines for the automotive industry, the paper investigates the start‐up process of an advanced manufacturing system. The theory underlying learning curves and manufacturing progress functions are used to illustrate progress in manufacturing performance that takes place as time passes and the production volume is accumulated. A start‐up methodology, the concept of full‐speed testing, is outlined, empirically documented and analyzed by means of qualitative and quantitative inquiry. Full‐speed testing is a methodology for detecting potential problems and limitations in technology and organization, and for increasing the rate of direct labor‐ and cognitive learning. Tentative support is found for the notion that material supply, organization design and increased problem‐solving capacity are related to the rate with which manufacturing performance progresses as time passes and production capacity is accumulated.

Preventive maintenance is an effective maintenance strategy to ensure the constant and efficient usage of building systems and their components. The reactive-based maintenance as the main strategy in high-rise residential buildings is a concern as the maintenance output resulting from the strategy could not achieve the standard level of performance. The purpose of this paper is to identify the characteristics of preventive maintenance and establish the relationship with maintenance performance in high-rise residential buildings.

The characteristics of preventive maintenance and maintenance performance parameters were identified through the literature review. A quantitative approach was adopted, where a questionnaire was distributed to the maintenance personnel of high-rise residential buildings. Then, ranking analysis and correlation were conducted to produce findings that help to achieve the research objectives.

The research findings indicate that there are seven maintenance characteristics significantly correlated with maintenance performance indicators (maintenance costs deviation, time variance of maintenance work, customer service and downtime rate). It is recommended that these characteristics are considered during the execution of preventive maintenance as they have a significant effect on the maintenance performance.

The extensive literature suggests the relationship between the characteristics of preventive maintenance and maintenance performance, but is still questionable. Thus, this research investigates the relationship between preventive maintenance characteristic and maintenance performance for high-rise residential buildings in Malaysia. The findings of the research can act as a guide for maintenance personnel to optimise maintenance performance by focusing on the highlighted preventive maintenance characteristics.

This paper aims to be a balance of mixed management and engineering concepts that aims to fuse classical engineering methodologies into a systems engineering framework to assess and compare systematically and comprehensively services rendered by engineering systems.

An auditing framework is developed to assess the performance of engineering services in the context of engineering services found within a facility. As a result of a system heterogeneity factor, an approach to remove this confounding issue is developed to provide a different insight into the performance of engineering services.

The output of the audit exercise serves as an input to the second methodology, direct age‐adjusted failure, which overcomes systems attributes confounding issues when comparison is made between different systems populations of the same class type. This method allows management to identify areas in which extra resources are needed to improve maintenance performance.

The proposed standardization technique, which can be applied to system attributes other than age, overcomes the systems heterogeneity issue between localities. This research work is positioned in the context of building engineering services, as they are the most important in terms of socio‐economical impact. A case study based on an actual facilities assessment in Singapore is used to demonstrate the usefulness of such an integrated systems approach.

This paper presents a qualitative‐quantitative assessment framework that consists of two major methodologies to help in identifying and prioritising engineering system services in order to allocate limited resources to the appropriate engineering service so as to improve its performance.

Transport logistics systems in companies with additional public service roles are complex and could benefit from new approaches to performance management. Existing approaches tend to be fragmented; thus, the purpose of this paper is to integrate balanced performance measures, a dynamics model, and the problem-solving method into a new model.

An integrated framework is developed by reviewing literature and synthesising attributes of performance measurement systems, system dynamics and problem-solving methods. The framework is then applied to a multiple-role company’s sea transportation system. The study uses statistical methods to identify performance indicators, management interviews with document study to develop a dynamics model, and simulation methods to formulate an improvement plan.

The performance measurement design stage allowed for the identification of balanced, aligned performance indicators, while the system dynamics model illuminated the impact of the system components’ interrelationships on performance output. The problem-solving method allowed for analysis of system performance, identification of constraints and formulation of a performance improvement plan.

This framework can help transport logistics system stakeholders in multiple-role companies avoid silo thinking, misaligned performance objectives, local optima and short-term solutions.

This study contributes to the existing body of research by introducing a novel framework integrating performance measurement, system dynamics and the problem-solving method. It also addresses a theoretical gap by showing how interconnecting components of sea transportation systems affect transport logistics performance.

WHEN technological change began to make a serious impact upon manufacturing industry widespread fears were expressed about the volume of unemployment that would follow. In the succeeding years those fears have not been realized, but that does not mean that workers and their jobs have remained unaffected.

The purpose of this paper is to develop a systematic strategic approach to handle corrective maintenance onto the failures/breakdowns of construction equipment. For the maintenance crew/team, a breakdown code management is proposed, which will provide focused and unambiguous approach to manage any kind of breakdowns in construction equipments.

The past breakdown records of a construction organization in the UAE are considered for analysis. From the failure data, through cause effect analysis (CEA) tools, the components and the breakdown codes namely breakdown main codes (BMC) and breakdown sub-codes (BSC) are formulated. With Pareto analysis, the critical codes are identified and validated through failure modes and effects analyses (FMEA) tools for the critical effect on the affected components. From this identified BSC's further closer failure identification codes namely breakdown symptom codes (BSyC) and breakdown reason codes (BRC) are identified through fault tree analysis (FTA) tools. The approach to modified breakdown maintenance management (MB2M) with breakdown maintenance protocol (BMP) is envisaged.

The study was conducted on four different types of heavy lifting/earth moving/material handling system of equipment and further focused with two earth moving equipment namely dumpers and wheel loaders. Failure analysis is performed and the failure ratio and the component contribution to the failures are identified. Based on the information, the preliminary codes namely BMC and BSC are identified through CEA tools and the BMC and BSC are identified to find the most contributing codes to the maximum number of failures through Pareto analysis. Further the critical sub-codes are further verified through FMEA tools on the severity levels of the sub components due to these codes. The FTA methods are used to identify the closer reasoning and relations of these codes and the further codes namely BSyC and BRC are identified which are the exact cause of the failures. The management of breakdowns is further proposed through MB2M which includes BMP which provides all resources for the breakdowns.

The failure data collected are only pertaining to the Middle East region and applicable to similar regions for similar plant mix in construction companies. The sample equipment is only part representative of the construction equipment. A more robust model can be suggested in the future covering all aspects and for other regions as well.

The proposed methodology and model approach is highly adaptable to similar industries operating in the Middle East countries.

Many authors have studied the preventive maintenance models and procedures and proposals have been proposed. On the breakdown maintenance management of construction equipment, very few studies have been proposed mostly on the cost analysis. This model attempts to provide a code management solution to manage the unpredictable failures in construction equipment through failure data analysis on a construction organization.