COST ANALYSIS FOR EQUIPMENT REPLACEMENT.

Replacing equipment at the most economical time not only helps to save state transportation agencies (STAs) costs for operating the fleet but also keeps the fleet’s level of service at an optimal level. Prior research studies focused on developing alternative economic-oriented equipment replacement models rather than the equivalent annual cost (EAC) model to achieve better economic decisions. In addition, various optimization techniques were applied to equipment replacement problems with different objectives, constraints, and contexts. However, few studies examined the impact of depreciation estimation on the equipment replacement decision within STAs by minimizing total equipment cost over a finite study period using the dynamic programming optimization method. This study performed a case study of two class codes of equipment [1.5 m3 (2-yd) diesel engine front-end loaders and 0.453 t (half-ton) fleetside pickup trucks] to analyze the impact of different depreciation calculations on equipment replacement decisions. Using real-world data provided by the Oklahoma Department of Transportation, the study showed that the double-declining balance depreciation method substantially reduces the number of pieces of equipment recommended for replacement compared with the result of the straight-line depreciation method. This study contributes to the understanding of the impact of depreciation methods on equipment replacement decisions as well as the importance of properly estimating equipment depreciation to minimize the equipment costs over a designated study period among STA communities. The demonstrated manual calculation procedures of dynamic programming for cost optimization potentially may facilitate STA’s adoption of dynamic programming for equipment economic decisions.

Right-Sizing and Replacing the Right Equipment at the Right Time

Equipment selection is a key strategic decision in the design of a material handling system, because an improper one will lead to operational problems and unnecessary investment costs. It involves determining the number and combination of loaders and trucks which will move the material, fulfilling a specified production schedule. Previous works have addressed this problem with deterministic approaches, without considering the inter-dependent availability of trucks and loaders. In order to fill this gap, we developed a stochastic model that combines the selection and equipment replacement problems, subject to a stochastic production rate constraint. This is a new idea that will help decision-makers to decide faster and more reliable. The proposed model optimises the fleet by minimising the total life cycle costs. To solve it, we used a linearisation approach that reduces the computational effort. We tested our approach with a benchmark model, using a mining case study. Results indicate that the solutions ensure with a high probability a determined production target, producing good robust solutions compared to the deterministic counterpart.

The deposition pattern produced on the clothing of the operator during typical lawn and garden maintenance was identified in this study. The application was completed using water (for spray applications) and fertilizer (for granular applications) mixed with fluorescein dye as a tracer. Six types of application equipment were used to apply the dye mixtures to turf in timed and measured walks. The deposition patterns and the level of deposition on the operators clothing produced by each equipment type were determined. Fluorescein dye was used to provide visual evidence of exposure. The quantity of dye deposited at various body locations was measured, using an ultraviolet visible spectrophotometer. The deposition pattern and the total amount deposited were dependent on the type of equipment used for application. Overall, those pieces of equipment where a liquid spray was produced resulted in greater deposition levels than the equipment using a granular product. Contamination from the low volume application and the adjustable garden hose end sprayer equipment was significantly higher than all other pieces of equipment. The amount of contamination also varied by body area with the feet, lower legs, and upper legs receiving the greatest amount of deposition.

An input-output model for equipment replacement decisions

Markov chain optimization of repair and replacement decisions of medical equipment

Power equipment upgrade vs. replacement decisions are often encountered in the manufacturing environment. A systematic model can be used to aid in the decision-making process. Many variables must be analyzed in order to reach a wise decision. This framework for decision-making includes identifying objectives, indicators of success, alternative strategies, and an operational plan. A check list-type approach is useful for analyzing the suggested variables which should be considered when making an upgrade vs. replacement decision. >

Don't Be Shy and Retiring With Old Equipment

This paper addresses applications of modern technology, advanced feedback control schemes using wide area measurements, and wide-area visualization techniques to improve grid reliability in complex and multifaceted power system conditions. Reliability aspects of P&C systems such as methods to identify and correct hidden failures and methodologies for optimal testing are also described. As new technologies offer significant improvements, large numbers of legacy P&C systems are still in operation. Upgrading aging P&C systems with modern counterparts not only reduces possibilities for failure, but offers unprecedented capabilities for reliable and high quality data and flexibility in operations which are presently largely untapped. Possibility to monitor equipment performance and to identify failed parts or components helps with equipment life projections and replacement decisions. Integration of P&C systems into Enterprise Systems for improved Asset Management, including value of standardization, is also assessed. The goal of this paper is to provide a comprehensive and systematic approach to meeting the P&C challenges of the 21st century

The optimum terms of replacement of equipment subject to wear and tear and obsolescence with more advanced equipment with similar performance are investigated. To this end, the methodology of multi-criteria evaluation of equipment performance indicators when switching to a new type of equipment is proposed. The values of EAC (Equivalent Annual Cost), calculated for several equipment replacement cycles and for an infinite number of cycles are investigated. Estimates of the dispersion degree of EAC values depending on the service life of old and new equipment under conditions when the dynamics of operating costs is subject to random fluctuations are obtained. For this, covariance functions of random processes that describe the dynamics of the operating costs of old and new equipment were used. On the basis of covariance functions, estimates of the functions of standard deviations of EAC values are obtained. Using the obtained estimate of the degree of dispersion of equipment performance indicators, the multi-criteria optimization problem was investigated. This approach is of great practical interest, because for many enterprises, not only the average expected level of equipment performance indicators, but also the dispersion degree of the values of these indicators is of great importance. As a result of the research, the technique for planning the equipment replacement terms was developed. The proposed methodology allows justifying the terms of replacement of old equipment with new equipment, taking into account both the average expected EAC values and their level of fluctuations. The studies have shown that due to choosing the equipment renewal terms, it is possible to significantly reduce the degree of dispersion of equipment performance indicators, slightly sacrificing the average expected value.

The drainage pumping plants are the main facilities in flood control infrastructure. Many of them have deteriorated and their maintenance, especially replacement, has become a large issue in Japan. The plant consists of many different types of equipment. Each of them has its own lifespan. The lifespan has uncertainty. A method is proposed to schedule the replacement of equipment under uncertainty, considering the two properties of rationality and robustness. The rationality means that the schedule is logical and feasible. It is evaluated by the replacement cost in the scheduling period under the constraints of the reliability and annual cost. The robustness means that the schedule is hard to be affected by the uncertainty of the equipment lifespan. It is evaluated by the expected value of the time difference between the actual replacement and the scheduled replacement based on the probability distribution of equipment lifespan. The problem is modeled as a multi-objective optimization one on the rationality and the robustness of the schedule. Pareto optimal solutions are derived. The effectiveness of the proposed method is illustrated by case studies based on the practical conditions. The characteristics of Pareto optimal solutions are made clear by comparing non Pareto optimal ones. The contribution of this paper is to propose a method to design the replacement schedule which is hard to be affected by the uncertainty of the equipment lifespan.

Single-Use versus Reusable Endoscopes for Percutaneous Biliary Endoscopy with Lithotripsy: Technical Metrics, Clinical Outcomes, and Cost Comparison

Hand surgery under local anesthesia only has been used more frequently in recent years. The purpose of this study was to compare perioperative time and cost for carpal tunnel release performed under local anesthesia ("wide-awake local anesthesia no tourniquet," or WALANT) only to carpal tunnel release performed under intravenous sedation. A retrospective comparison of intraoperative (operating room) surgical time and postoperative (postanesthesia care unit) time for consecutive carpal tunnel release procedures performed under both intravenous sedation and wide-awake local anesthesia was undertaken. All operations were performed by the same surgeon using the same mini-open surgical technique. A cost analysis was performed by means of standardized anesthesia billing based on base units, time, and conversion rates. There were no significant differences between the two groups in terms of total operative time, 28 minutes in the intravenous sedation group versus 26 minutes in the wide-awake local anesthesia group. Postanesthesia care unit times were significantly longer in the intravenous sedation group (84 minutes) compared to the wide-awake local anesthesia group (7 minutes). Depending on conversion rates used, a total of $139 to $432 was saved in each case performed with wide-awake local anesthesia by not using anesthesia services. In addition, a range of $1320 to $1613 was saved for the full episode of care, including anesthesia costs, operating room time, and postanesthesia care unit time for each patient undergoing wide-awake local anesthesia carpal tunnel release. Carpal tunnel release surgery performed with the wide-awake local anesthesia technique offers significant reduction in cost for use of anesthesia and postanesthesia care unit resources.

5 - Equipment Selection

The full potential of geostatistical simulation as a tool for planning, designing and optimising production is only realised when it is integrated within the entire design and production cycle. In the planning and design stages this involves the simulation of components of the production cycle that depend on (simulated) grades and geology. In the production stage it involves integration with the mining method and the type and use of equipment. This paper explores the general concepts of integrated geostatistical simulation and illustrates them with particular reference to blast design, equipment selection and the associated quantification of ore loss, ore dilution and the ability to select ore on various scales. The critical component of most metalliferous open pit mining operations is ore selection, i.e. the minimisation of ore loss and ore dilution during extraction. In general, extraction comprises drilling, blasting and loading, all of which are planned and designed on the basis of uncertain models of geology and grade. The application describes the integration of geostatistically simulated grade, geological and geomechanical models with blast modelling to provide a link between the estimated in situ characteristics of the orebody and the locations of the same (displaced) characteristics following the blast. This approach provides a means of evaluating different types of selection and thereby enables planners to optimise the selection process in terms of blast design, type and size of loading equipment, maximisation of ore recovery and minimisation of ore loss and dilution. This conversion of the in situ/block model resource to a realistically recoverable reserve may, in many instances, be the most significant source of uncertainty in reserve estimation.