Optimal maintenance of multi-component systems: a review

In this article we give an overview of the literature on multi-component maintenance optimization. We focus on work appearing since the 1991 survey "A survey of maintenance models for multi-unit systems" by Cho and Parlar. This paper builds forth on the review article by Dekker et al. (1996), which focusses on economic dependence, and the survey of maintenance policies by Wang (2002), in which some group maintenance and some opportunistic maintenance policies are considered. Our classification scheme is primarily based on the dependence between components (stochastic, structural or economic). Next, we also classify the papers on the basis of the planning aspect (short-term vs long-term), the grouping of maintenance activities (either grouping preventive or corrective maintenance, or opportunistic grouping) and the optimization approach used (heuristic, policy classes or exact algorithms). Finally, we pay attention to the applications of the models.literature review;economic dependence;failure interaction;maintenance policies;grouping maintenance;multi-component systems;opportunistic maintenance;maintencance optimization;structural dependence

A Quantitative Analysis for Improving Harvest Productivity for Biomass Crops

Harvest cost is a major concern for making biomass a viable option. Unproductive time in-field significantly contributes to this cost. Variability of harvest timeliness is largely due to maneuvering equipment in-field, operator experience, equipment failures, and field and crop conditions, among other reasons. These are particularly important for farm management to know how to best handle interruptions during harvest. Consequently, there is a serious need to better account for harvest untimeliness. For this research, the crops of interest are Miscanthus and shrub willow. These crops are attractive for several reasons. They do not compete with cash crops because they grow on marginal land and have the potential normalize feedstock qualities. In general, three aspects of harvest productivity will be focused on, which include: equipment maneuverability at the headlands, operator performance, and equipment reliability. More specifically, maneuvering equipment during harvest operations can have a significant impact on production cost; therefore, the fieldwork pattern is critical for optimal productivity and a cost-efficient harvest. Harvest pattern influences time wasted due to excessive unproductive time and distances traveled during operational tasks. Equipment is maneuvered at the skill of the operator. Often, operator experience is a bottleneck for operations and a key factor influencing productivity. In addition, unproductive times are largely due to repair and maintenance on the equipment caused by unexpected harvest complications. The uncertainty of these factors cause inconsistency in productivity. It is crucial to achieve optimum harvest efficiency for the feasibility of the biomass supply chain. Evaluating these aspects will allow us to better understand and model for these limitations

A study in joint maintenance scheduling and production planning

Master'sMASTER OF ENGINEERIN

Optimal maintenance of multi-component systems: a review

In this article we give an overview of the literature on multi-component maintenance optimization. We focus on work appearing since the 1991 survey "A survey of maintenance models for multi-unit systems" by Cho and Parlar. This paper builds forth on the review article by Dekker et al. (1996), which focusses on economic dependence, and the survey of maintenance policies by Wang (2002), in which some group maintenance and some opportunistic maintenance policies are considered. Our classification scheme is primarily based on the dependence between components (stochastic, structural or economic). Next, we also classify the papers on the basis of the planning aspect (short-term vs long-term), the grouping of maintenance activities (either grouping preventive or corrective maintenance, or opportunistic grouping) and the optimization approach used (heuristic, policy classes or exact algorithms). Finally, we pay attention to the applications of the models

Optimization of maintenance performance for offshore production facilities

Master's thesis in Offshore technologyNew technologies are becoming advanced and complex for offshore production facilities. However this advancement and complexity in technology creates a more complicated and time consuming forensic processes for finding causes of failure, or diagnostic processes to identify events that reduce performance. As a result, micro-sensors, efficient signaling and communication technologies for collecting data efficiently, advanced software tools (such as fuzzy logic, neural networks, and simulation based optimization) have been developed, in parallel, to manage such complex assets. Given the nature and scale of ongoing changes on complexities, there are emerging concerns that increasing complexities, ill-defined interfaces, unforeseen events can easily lead to serious performance failures and major risks. To avoid such undesirable circumstances, „just-in-time‟ measures of performance to ensure fully functional is absolutely necessary. The increasing trend in complexity creates a motivation to develop an integrated maintenance management framework to get real-time information to solve problems quickly and hence to increase functional performance (help the asset to perform its required function effectively and efficiently while safeguarding life and the environment). Establishing “just-in-time” maintenance and repairs based on true machine condition maximizes critical asset useful life and eliminates premature replacement of functional components. This thesis focuses on developing an integrated maintenance management framework to establish „just-in-time‟ maintenance and to ensure continuous improvements based on maintenance domain experts as well as operational and historic data. To do this, true degradation of components must be identified. True level of degradation often cannot be inferred by the mere trending of condition indicator‟s level (CBM), because condition indicator levels are modulated under the influence of the diverse operating context. Besides, the maintenance domain expert does not have a precise knowledge about the correlation of the diverse operating context and level of degradation for a given level of condition indicator on specific equipment. Efforts have been made in here to identify the true degradation pattern of a component by analyzing these vagueness and imprecise knowledge. Key words: effective and efficient maintenance strategy, ‘just-in-time’ maintenance, condition based maintenance, P-F interval

Manufacturing lot size and product distribution problem with rework, outsourcing and discontinuous inventory distribution policy

Product quality, timely delivery, and lower cost are critical operational goals to nowadays manufacturers, and company managements constantly seek different approaches to achieve these goals in order to stay competitive in turbulent global markets. This study investigates a practical manufacturing lot size and distribution problem with rework, outsourcing, and discontinuous inventory distribution policy. In real manufacturing environments, due to different controllable and/or uncontrollable factors, production of the nonconforming products is inevitable. Careful inspection into identifying nonconforming items and instant correction of the defects are considered in the proposed study. In additions, due to the limited production capacity in real manufacturing environments, sometimes, outsourcing can be used to cope with occasional unsteady demands, or running short of in-house capacity, to allow the management to maintain a smooth operation and/or shorten the production cycle length. Furthermore, in vendor-buyer integrated supply chains, multi-delivery policy is often considered for distributing finished products to customers. Motivated by the aforementioned practical situations, this study develops a mathematical model to explicitly investigate such a manufacturing lot-size and product distribution problem. Optimization techniques are employed to solve the problem and a numerical example is provided to show the applicability of our research results

A Simulation Based Approach for Determining Maintenance Strategies

Manufacturing organizations are continuously in the mode of identifying and implementing mechanisms to achieve a competitive edge. To this point manufacturers have recognized the critical role of equipment in the productivity of manufacturing operations. With the current trend of manufacturers attempting to lean out their production processes, primary and auxiliary equipment have become even more important to manufacturers as measured by productivity, quality, delivery, and cost metrics. As a result of the focus on lean manufacturing, maintenance management has found a new vigor and purpose to increase equipment capacity and capability. However, the most proactive maintenance strategy is not always the most effective utilization of resources. It is typical for manufacturers to integrate both reactive and proactive maintenance to define a cost effective maintenance strategy. A simulation-based approach is presented that allows an end user to develop such a maintenance strategy

Perspectives on trading cost and availability for corrective maintenance at the equipment type level

Characterising maintenance costs has always been challenging due to a lack of accurate prior cost data and the uncertainties around equipment usage and reliability. Since preventive maintenance does not completely prevent corrective repairs in demanding environments, any unscheduled maintenance can have a large impact on the overall maintenance costs. This introduces the requirement to set up support contracts with minimum baseline solutions that warrant the target demand within certain costs and risks. This article investigates a process that has been developed to estimate performance based support contract costs attributed to corrective maintenance. These can play a dominant role in the through-life support of high values assets. The case context for the paper is the UK Ministry of Defence. The developed approach allows benchmarking support contract solutions, and enabling efficient planning decisions. Emphasis is placed on learning from feedback, testing and validating current methodologies for estimating corrective maintenance costs and availability at the Equipment Type level. These are interacting sub-equipment's that have unique availability requirements and hence have a much larger impact on the capital maintenance expenditure. The presented case studies demonstrate the applicability of the approach towards adequate savings and improved availability estimates