Equipment Downtime Research Articles

Modeling the Dynamics of Heavy Equipment Management Practices and Downtime in Large Highway Contractors

Machine downtime is invariably perceived as one of the most critical problems faced by highway contractors. Attempts to reduce downtime often result in failure due to the dynamic behaviors between equipment management practices and downtime. This paper is thus intended to highlight the dynamics of heavy equipment management practices and downtime in large highway contractors and utilizes them as a framework in constructing a simulation model using a system dynamics approach. Face-to-face interviews were conducted with equipment managers from five different large highway contractors in Thailand. The finding reveals that, to be successful in alleviating downtime, contractors must view their practices on equipment management as an integration of multiple feedback processes, which are interrelated and interdependent with downtime. Based on various validation tests, the simulation model is deemed appropriate in representing the equipment management system as related to downtime of large highway contractors. Th...

Bayesian statistics and production reliability assessments for mining operations

This article presents a novel application of structural reliability concepts to assess the reliability of mining operations. ‘Limit-states’ are defined to obtain the probability that the total productivity – measured in production time or economic gain – exceeds user-selected thresholds. Focus is on the impact of equipment downtime and other non-operating instances on the productivity and the economic costs of the operation. A comprehensive set of data gathered at a real-world mining facility is utilised to calibrate the probabilistic models. In particular, the utilisation of Bayesian inference facilitates the inclusion of data – and subsequent updating of the production probabilities – as more data become available. The article includes a description of the Bayesian approach, as well as the limit-state-based reliability methodology. A comprehensive numerical example demonstrates the methodology and the interpretation of the probabilistic results.

Quantitative determination of residual active pharmaceutical ingredients and intermediates on equipment surfaces by ion mobility spectrometry

Ion mobility spectrometry (IMS) is an analytical technique that separates ions based on their gas phase mobility at atmospheric pressure. Since gas phase ion mobility is a function of the shape and structure of the ion, this technique has the potential to provide unique specificity and selectivity. Furthermore, IMS is very sensitive (subnanogram detection limits for many small molecules), and a single analysis is typically completed within 1 min. In principle, these features of IMS should make it an ideal choice for use in cleaning verification analysis of pharmaceutical manufacturing equipment. This report describes the successful development and validation of three different equipment cleaning verification methods using IMS. The methods were developed for a specific intermediate (Compound A) in the synthetic route for a drug substance as well as for final drug substances (active pharmaceutical ingredients Compounds B and C). The cleaning verification methods were validated with respect to specificity, linearity, precision, accuracy, stability, and limit-of-quantitation. In all cases, the limits-of-quantitation were determined to be at the nanogram or sub-nanogram level. Both swab and rinse samples collected from the equipment surfaces were successfully analyzed and manufacturing equipment down-time was significantly minimized due to the reduction in cleaning verification analysis time (for example, the total analysis time for more than 30 samples using IMS was reduced to less than 2 h).

Optimizing Our PM Programs

Whether you call it planned maintenance or use the more traditional term of preventive maintenance (PM), you will certainly have noticed the still-current, somewhat obsessive emphasis on getting PMs done on time. A powerful mystique has grown up around the presumed “preventive” aspect of PM that is difficult to explain in simple, rational terms. Simple logic suggests that a well-designed and wellimplemented PM program does provide two benefits that can be important. The discussion below is intended to examine the extent to which PM can really improve equipment reliability, downtime, and level of safety. Yes—PM does have some impact on the reliability of some items and therefore it does have some beneficial impact on equipment uptime. It does this by preventing some equipment failures—specifically, those that would have occurred if certain degeneration-prone parts had not been replaced or restored to like-new condition. And the performance verification and safety testing that is now a part of many PM procedures does establish certain levels of confidence that the devices being tested are free from hidden failures in the sense that they are not already (between tests) in a degenerated and potentially unsafe condition. Again, however, we need to keep in mind that only some equipment items benefit from this statistical assurance about safety—specifically those prone to developing hidden failures (those that will not be obvious to the typical equipment users) and that could have serious adverse consequences (see sidebar on hidden failures). In addition to these measurable benefits, well-executed PM programs do offer a few less tangible benefits. These include: • Searching the facility for items when they are due for PM sometimes leads to the discovery of other pieces of equipment that have been pushed aside and abandoned without being reported as either damaged or completely non-functional. • Periodically hunting down equipment to perform scheduled maintenance helps validate the accuracy of the facility’s inventory. • Providing the facility’s medical devices with some periodic care and attention generates a certain level of comfort and security in the minds of the clinical staff that everything possible is being done to ensure the safety of their equipment. The fact that PM provides a demonstrable benefit for only a relatively few devices is very important. As maintenance managers responsible for maximizing the return on the resources that our facilities devote to equipment maintenance, we need to be very clear about this for our own management decision-making. We should also make the facts on the somewhat limited value of PM known to the facility managers and equipment users we serve, as well as to those who currently set the compliance rules for our maintenance programs. Data collected from the repair call “cause coding” that we implemented at Masterplan some time ago (described later in this paper) clearly document that even well-implemented PM programs cannot, and do not, prevent the vast majority Optimizing Our PM Programs

Probabilistic approach to the condition monitoring of aerospace engines

The provision of TotalCare® styled service offerings by original equipment manufacture (OEM) suppliers of high-integrity assets is intended to provide improved levels of system availability to the operator. A key element of such service offerings is the ability to minimize unplanned equipment downtime, and the utilization of advanced diagnostic and prognostic monitoring tools is a significant component in achieving this. Monitoring methods, founded on novelty detection technologies, are now a well-established condition monitoring technique. This approach is particularly appropriate for monitoring high-integrity plant where fault conditions arise with extremely low levels of probability. The approach described in this article is to establish empirically based models of normality that are guided by engineering knowledge and utilize key features normally used by expert engineers. However, rather than consider generic modelling approaches, it is proposed that application of models that adapt their sensitivity to the operation of individual assets offer greater prognostic efficiency. This article demonstrates how this can be achieved by considering asset-specific models that adapt the threshold of alerting in accordance with the observed normal running of the plant.

Study of Factors Influencing the Efficient Management and Downtime Consequences of Highway Construction Equipment in Thailand

Downtime resulting from machine breakdown invariably has a considerable impact on the performance of construction projects and companies as a whole, especially to contractors with heavy investment in equipment. Attempts to investigate the causes and consequences of downtime are rarely found. The aim of this paper is to characterize and quantify factors that influence downtime consequences (consequential problems resulting from downtime) of highway construction equipment based on the structural equation modeling (SEM) approach. A questionnaire survey was conducted to collect data on equipment management practices and downtime consequences among highway contractors in Thailand. The SEM model proposed is of value for both researchers and practitioners to facilitate a better understanding of the relationships among acquisition condition, operational practice, maintenance quality, disposal practice, and downtime consequence of heavy equipment. The model also helps contractors to manage equipment more efficiently by concentrating on several practices that can convey the greatest benefit in minimizing downtime consequences at each particular stage of a machine's life cycle, rather than considering all practices simultaneously where the benefits gained are perhaps not proportional to the effort.

System dynamics modelling of machine downtime for small to medium highway contractors

PurposeDowntime resulting from equipment failure is a major problem consistently faced in highway construction. Since managing construction equipment is tightly connected to various activities and parties inside as well as outside of the firm, failure to account for this fact invariably causes downtime to be even more severe. Variation in equipment management practices is thus, indeed, a root cause of the dynamics of machine downtime. This study is intended to address key dynamic features of heavy equipment management practices and downtime in small to medium highway contracting firms and propose policies for equipment performance improvement.Design/methodology/approachFace‐to‐face interviews with equipment managers from five different small to medium highway construction companies in Thailand were conducted. Data were analysed using a system dynamics (SD) simulation approach.FindingsTo overcome downtime problems, contractors need to understand the dynamics of downtime as well as its influential factors, and thus manage their equipment as a dynamic process rather than one that is static. Based on the simulation, various policies are proposed to improve the performance of heavy equipment for small to medium highway contractors.Originality/valueThe research is of value in facilitating better understanding on the dynamics of equipment management practices and downtime as well as their interdependency.

Evaluation of control configurations for a depropaniser

Distillation columns are highly coupled and non-linear, and have major impact on the utilities consumption and product quality. By proper design of their controls, energy consumption, product variability, operator intervention and equipment downtime can be reduced. Thus, selection of proper controls for distillation columns is both challenging and critical. Although extensive literature have been published on various aspects of distillation control, viz., level controller tuning, ratioing manipulated variables and turndown operation, there is no comprehensive study on control evaluation considering all aspects and rigorous simulation. In particular, turndown operation has received little attention in control research. This work deals with the composition control of distillation columns considering depropaniser as an example and using rigorous simulation. Effect of level controller tuning, ratioing the manipulated variable and turndown operation on the performance of several control structures to reject step disturbances in feed flow rate and composition, and sinusoidal disturbance in feed composition, is studied. Both single- and dual-ended composition control of the depropaniser are considered. Results of this study show the need and importance of a comprehensive and rigorous analysis including column operation far away from the design conditions, for optimal design of column control.

Planning and optimizing the maintenance of paper production systems in a paper plant

Manufacturing and production plants operate physical assets that deteriorate with usage and time, thus, maintenance actions are required to restore the assets back to their original predetermined operational conditions. But since, organizational resources are limited and scarce. The objective of an effective maintenance program is to minimize total cost of inspection and repair, and equipment downtime. In this paper, we describe a new multi-criteria optimization framework for deriving optimal maintenance schedules for preventive maintenance which considers availability, maintenance cost and life cycle costs as the criteria for optimization. The Simulink toolbox of the Matlab has been interfaced with Genetic algorithm for optimization. After getting solution, Stochastic Petri nets has been used to model the system and find out the effect of optimized maintenance schedules on system performance. The application of the proposed framework has been discussed on a practical case of a paper plant.

Prioritizing equipments for preventive maintenance (PM) activities using fuzzy rules

Maintenance, as a support function in businesses, plays an important role in backing up any emerging business and operation strategies. It is required to maximize the reliability of equipment and systems. Among them, preventive maintenance (PM) involves the repair, replacement, and maintenance of equipment in order to avoid unexpected failure during use. The objective of any PM program is the minimization of the total cost of inspection and repair, and equipment downtime (measured in terms of lost production capacity or reduced product quality). Maintenance activities have been regarded as a necessary expense that belongs to the operating budget. But since, organizational resources are limited and scarce, prioritizing equipments for assigning resources is essential. In this paper, fuzzy rules used to interpret linguistic variables for determination of priorities. Using this approach, such verbal expressions, which cannot be explicitly analyzed or statistically expressed, are herein quantified and used in decision making.

Solving the Puzzle How to Cut Costs and Improve Service

Solving the Puzzle How to Cut Costs and Improve Service

On-line determination and control of the water content in a continuous conversion reactor using NIR spectroscopy

On-line near infrared spectroscopy was used to determine the water content in a continuous conversion reactor. The NIR predictions were incorporated into the distributed control system (DCS) which then controlled the addition of water to the reactor. The conversion reaction utilizes methanol, water, sodium carbonate and a reactant. Control of the water content is important for a number of reasons. At elevated water levels, a competing hydrolysis reaction increases along with the product solubility in the mother liquor leading to product losses. At reduced water levels, the product becomes anhydrous and the reaction mixture becomes gelatinous, necessitating a shutdown of the reactor for cleaning. The previous procedure for monitoring water was to remove a sample once per hour, transfer the sample to the laboratory, and run a Karl Fisher assay. Upon obtaining results from the lab, an operator would manually adjust the water inlet valve to the reactor. NIR spectroscopy in an on-line mode allows spectra to be collected every 200 s markedly increasing the frequency of results. A partial least squares model was constructed, validated and successfully implemented to predict the water content of the reactor. Further, by feeding the results to the process DCS, water additions to the reactor were fully automated. The increased frequency of sampling by NIR led to an improvement in the control of the water content and decreased the normal amount of equipment downtime. These factors improved process stability and recovery thereby generating an estimated $500,000 in savings over the course of the campaign.

Remaining life estimation of used components in consumer products: Life cycle data analysis by Weibull and artificial neural networks

Environmental awareness and legislative pressures have made manufacturers responsible for the take-back and end-of-life treatment of their products. To competitively exploit these products, one option is to incorporate used components in “new” or remanufactured products. However, this option is partly limited by a firm's ability to assess the reliability of used components. A comprehensive two-step approach is proposed. The first stage phase statistically analyzes the behavior of components for reuse. A well-known reliability assessment method, the Weibull analysis, is applied to the time-to-failure data to assess the mean life of components. In the second phase, the degradation and condition monitoring data are analyzed by developing an artificial neural network (ANN) model. The advantages of this approach over traditional approaches employing multiple regression analysis are highlighted with empirical data from a consumer product. Finally, the Weibull analysis and the ANN model are then integrated to assess the remaining useful life of components for reuse. This is a critical advance in sustainable management of supply chains since it allows for a better understanding of not only service requirements of product, but the remaining life in a product and hence its suitability for reuse or remanufacture. Future work should assess: (1) reduction in downtime of process equipment through the implementation of this technique as a means to better manage preventative maintenance; (2) reduce field failure of remanufactured product; (3) selling-service strategy through implementation of the proposed methodology.

MAINTENANCE MODELS AND SERVICES – A SURVEY REGARDING COST ASPECTS

Minimizing the downtime of machines and equipment and thereby enhancing the overall performance of a production system is a challenge to researchers and practioners. Maintenance strategies consider Cost, Reliability, Availability, Maintainability, and Productivity, i.e. the performance, of any equipment and associated applications. It necessitates a holistic approach for integrating views and evaluations, not only of the systems themselves, but also for their mutual interactions and their interactions with the environment. Advanced maintenance models and services are candidates for cost savings. They integrate information processing and the processing of physical objects. After reviewing classical maintenance approaches next – generation maintenance strategies are presented.

Comparative Study for Stresses in Nozzle and Flange Welds Generated During Conventional Pressure Testing and Local Pressure Testing Using Bolted Devices

Weld repairs and alterations of pressure vessels and piping built to ASME codes may require pressure testing to prove the integrity of the weld and/or design. Conventional hydrostatic pressure testing requires filling an entire vessel or piping system with water and pressurizing it to the test pressure. In recent years, several designs were developed to employ bolted devices to perform local pressure testing of flange-to-nozzle, flange-to-pipe, and nozzle-to-shell attachment welds. Due to the cost and equipment downtime associated with performing a full conventional pressure test and the desire to reduce repair costs, several petrochemical companies adopted the use of such devices. The purpose of this paper is to compare the stress values and stress distribution associated with conventional and local pressure testing techniques. The advantages and disadvantages of both approaches are discussed and the conclusions are supported by a practical example.

Run-to-Run Failure Detection and Diagnosis Using Neural Networks and Dempster–Shafer Theory: An Application to Excimer Laser Ablation

The formation of microvias in multilayer substrates is a critical factor in microelectronic packaging manufacturing. Such microstructures can be produced efficiently by excimer laser ablation. Thus, laser ablation systems are evolving to a level where the need to offset high capital equipment investment and lower equipment downtime are imminent. This paper presents a methodology for inline failure detection and diagnosis of the excimer laser ablation process. The methodology employs response data originating directly from the equipment and characterization of microvias formed by the ablation process. Neural network (NN) models are trained and validated based on this data to generate evidential belief for potential sources of deviations in the responses. Dempster-Shafer (D-S) theory is adopted for evidential reasoning. Successful failure detection is achieved in 100% of 19 possible failure scenarios. Moreover, successful failure diagnosis is also achieved with only a single false alarm occurring in the 19 failure scenarios.

Design for maintenance: basic concepts and review of literature

This paper endeavours to present basic concepts and an outline of current research in the field of designing products/systems to enable ease of maintenance. The process of product maintenance is often a necessary evil since it ensures smooth performance of equipment, often at the cost of equipment downtime. Products that are easy to maintain entail less downtime. This means that they can be maintained at less expense, in less time and with less effort. There is a considerable amount of mathematical research conducted on this topic. Researchers have tended to focus on evolving mathematical models to predict maintenance schedules, downtime, etc. Much of that research is reactive in nature and is not useful as far as design is concerned. A methodology that enables product design for maintenance is conspicuous by its absence. This paper focuses on research efforts that can be directly helpful in the evolution of such a methodology.

INFOTRONIC TECHNOLOGIES FOR E-MAINTENANCE REGARDING THE COST ASPECTS

The most costly and not yet solved problem is to avoid the downtime of machines and equipment and thereby enhancing the overall performance of a production system. To minimize disturbances and breakdowns, e-maintenance and process supervisory control systems are being developed and introduced. The implementation of advanced e-maintenance technologies considers Cost, Reliability, Availability, Maintainability, and Productivity, i.e. the performance, for any equipment and associated applications. It necessitates a holistic approach for integrating views and evaluations, not only of the systems themselves, but also for their mutual interactions and their interactions with the environment. Infotronics technologies integrate information processing and the processing of physical objects. Intelligent maintenance systems are means for next – generation maintenance strategies.

Systems of multiple cluster tools: configuration, reliability, and performance

The migration of semiconductor processes to single-wafer vacuum cluster tools has rendered configuration an important decision variable in fab operation and heightened the impact of reliability on fab performance. We address these closely linked issues by deriving the optimal configuration and operation of systems of cluster tools in the presence of scheduled maintenance. The two extremes in the spectrum of possible configurations are the serial configuration, in which the modules in a tool are all different, each representing a step in a process sequence, and the parallel configuration, in which each tool is assigned only one process step. We predict that the latter can offer higher throughputs. However, this advantage may be slight when equipment downtime is relatively schedulable and infrequent, in which the case the serial configuration may be preferable because of its superior cycle times. We also derive optimal lot sizing and release policies for systems of cluster tools. We conclude that fabs will gradually migrate from parallel configurations to serial as cluster tools become more reliable and cycle time becomes more important.

Lean Sigma [production and supply chain management

Lean strategy brings a set of proven tools and techniques to reduce times, inventories, set up times, equipment downtime, scrap, rework and other wastes of the hidden factory. The focus is on value from a customer perspective and flowing this through the entire supply chain. The statistically based problem solving methodology of Six Sigma delivers data to drive solutions, delivering dramatic bottom-line results. In the Six Sigma school of study, a problem is tackled by a black or green belt, depending on the nature of the problem and the degree of complexity involved in the determination of solutions. The authors compare and contrast the lean and Six Sigma approaches, and find that greater benefits can be reaped by blending the best of each.