Development of New Measurement System of Errors in the Multiaxial Machine Tool for an Active Compensation

Error compensation techniques have been widely applied to improve multiaxis machine accuracy. However, due to the lack of reliable instrumentation for direct and overall measurements, all the compensation methods are based on offline measurements of each error component separately. The results of these measurements are static in nature and can only reflect the conditions at the moment of measurement. These results are not representative under real working conditions because of disturbances from load deformations, thermal distortions, and dynamic perturbations. This present approach involves the development of a new measurement system capable of dynamically evaluating the errors according to the six degrees of freedom. The developed system allows the generation of useful data that cover all machine states regardless of the operating conditions. The obtained measurements can be used to evaluate the performance of the machine, calibration, and real time compensation of errors. This system is able to perform dynamic measurements reflecting the global accuracy of the machine tool without a long and expensive analysis of various error sources contribution. Finally, the system exhibits compatible metrological characteristics with high precision applications.

Physicochemical Characterization of Alginate Beads Containing Sugars and Biopolymers

Alginate hydrogels are suitable for the encapsulation of a great variety of biomolecules. Several alternatives to the conventional alginate formulation are being studied for a broad range of biotechnological applications; among them the addition of sugars and biopolymers arises as a good and economic strategy. Sugars (trehalose and β-cyclodextrin), a cationic biopolymer (chitosan), an anionic biopolymer (pectin), and neutral gums (Arabic, guar, espina corona, and vinal gums) provided different characteristics to the beads. Here we discuss the influence of beads composition on several physicochemical properties, such as size and shape, analyzed through digital image analysis besides both water content and activity. The results showed that the addition of a second biopolymer, β-CD, or trehalose provoked more compact beads, but the fact that they were compact not necessarily implies a concomitant increase in their circularity. Espina corona beads showed the highest circularity value, being useful for applications which require a controlled and high circularity, assuring quality control. Beads with trehalose showed lower water content than the rest of the system, followed by those containing galactomannans (espina corona, vinal, and guar gums), revealing polymer structure effects. A complete characterization of the beads was performed by FT-IR, assigning the characteristics bands to each individual component.

Preventive Maintenance Optimization in Healthcare Domain: Status of Research and Perspective

Although medical equipment maintenance has been carefully managed for years, very few in-depth studies have been conducted to evaluate the effectiveness and efficiency of these implemented preventive maintenance strategies, especially after the debate about the credibility of manufacturer’s recommendations has increased in the clinical engineering community. Facing the dilemma of merely following manufactures maintenance manual or establishing an evidence-based maintenance, medical equipment maintenance could have exploited an advanced area in operations research which is maintenance optimization research. In this paper, we review and examine carefully the status of application oriented research on preventive maintenance optimization of medical devices. This study addresses preventive healthcare maintenance with a focus on factors influencing the maintenance decision making. The analysis is structured by defining different aspects necessary to construct a maintenance optimization model. We conclusively propose directions to develop suitable tools for better healthcare maintenance management.

Multicriteria FMECA Based Decision-Making for Aluminium Wire Process Rolling Mill through COPRAS-G

This paper presents a multifactor decision-making approach based on “grey-complex proportional assessment (COPRAS-G) method” in a view to overcome the limitations of Failure Mode Effect and Criticality Analysis (FMECA). In this model, the scores against each failure mode are expressed in grey number instead of crisp values to evaluate the criticalities of the failure modes without uncertainty. The suggested study is carried out to identify the weights of major failure causes for bearings, gears, and shafts of aluminium wire rolling mill plant. The primary findings of the paper are that sudden impact on the rolls seems to be most critical failure cause and loss of power seems to be least critical failure cause. It is suggested to modify the current control practices with proper maintenance strategy based on achieved maintainability criticality index (MCI) for different failure causes. The outcome of study will be helpful in deriving optimized maintenance plan to maximize the performance of process industry.

Consecutive-Type Reliability Systems: An Overview and Some Applications

The family of consecutive-type reliability systems is under investigation. More specifically, an up-to-date presentation of almost all generalizations of the well-known consecutive k-out-of-n: F system that have been proposed in the literature is displayed, while several recent and fundamental results for each member of the aforementioned family are stated.

Variable Selection Methods for Right-Censored Time-to-Event Data with High-Dimensional Covariates

Advancement in technology has led to greater accessibility of massive and complex data in many fields such as quality and reliability. The proper management and utilization of valuable data could significantly increase knowledge and reduce cost by preventive actions, whereas erroneous and misinterpreted data could lead to poor inference and decision making. On the other side, it has become more difficult to process the streaming high-dimensional time-to-event data in traditional application approaches, specifically in the presence of censored observations. This paper presents a multipurpose analytic model and practical nonparametric methods to analyze right-censored time-to-event data with high-dimensional covariates. In order to reduce redundant information and to facilitate practical interpretation, variable inefficiency in failure time is determined for the specific field of application. To investigate the performance of the proposed methods, these methods are compared with recent relevant approaches through numerical experiments and simulations.

Planning for Reliable Coal Quality Delivery Considering Geological Variability: A Case Study in Polish Lignite Mining

The aim of coal quality control in coal mines is to supply power plants daily with extracted raw material within certain coal quality constraints. On the example of a selected part of a lignite deposit, the problem of quality control for the run-of-mine lignite stream is discussed. The main goal is to understand potential fluctuations and deviations from production targets dependent on design options before an investment is done. A single quality parameter of the deposit is selected for this analysis—the calorific value of raw lignite. The approach requires an integrated analysis of deposit inherent variability, the extraction sequence, and the blending option during material transportation. Based on drill-hole data models capturing of spatial variability of the attribute of consideration are generated. An analysis based on two modelling approaches, Kriging and sequential Gaussian simulation, reveals advantages and disadvantages lead to conclusions about their suitability for the control of raw material quality. In a second step, based on a production schedule, the variability of the calorific value in the lignite stream has been analysed. In a third step the effect of different design options, multiple excavators and a blending bed, was investigated.

Stochastic Analysis of a Two-Unit Cold Standby System Wherein Both Units May Become Operative Depending upon the Demand

The present paper analyzes a two-unit cold standby system wherein both units may become operative depending upon the demand. Initially, one of the units is operative while the other is kept as cold standby. If the operative unit fails or the demand increases to the extent that one operative unit is not capable of meeting the demand, the standby unit becomes operative instantaneously. Thus, both units may become operative simultaneously to meet the increased demand. Availability in three types of upstates is as follows: (i) when the demand is less than or equal to production manufactured by one unit; (ii) when the demand is greater than whatever produced by one unit but less than or equal to production made by two units; and (iii) when the demand is greater than the produces by two units. Other measures of the system effectiveness have also been obtained in general case as well as for a particular case. Techniques of semi-Markov processes and regenerative processes have been used to obtain various measures of the system effectiveness.

Design for Reliability of Complex System: Case Study of Horizontal Drilling Equipment with Limited Failure Data

Reliability is an important phase in durable system designs, specifically in the early phase of the product development. In this paper, a new methodology is proposed for complex systems’ design for reliability. Specific test and field failure data scarcity is evaluated here as a challenge to implement design for reliability of a new product. In the developed approach, modeling and simulation of the system are accomplished by using reliability block diagram (RBD) method. The generic data are corrected to account for the design and environment effects on the application. The integral methodology evaluates reliability of the system and assesses the importance of each component. In addition, the availability of the system was evaluated using Monte Carlo simulation. Available design alternatives with different components are analyzed for reliability optimization. Evaluating reliability of complex systems in competitive design attempts is one of the applications of this method. The advantage of this method is that it is applicable in early design phase where there is only limited failure data available. As a case study, horizontal drilling equipment is used for assessment of the proposed method. Benchmarking of the results with a system with more available failure and maintenance data verifies the effectiveness and performance quality of presented method.

Interval Estimation of Stress-Strength Reliability Based on Lower Record Values from Inverse Rayleigh Distribution

We consider the estimation of stress-strength reliability based on lower record values when X and Y are independently but not identically inverse Rayleigh distributed random variables. The maximum likelihood, Bayes, and empirical Bayes estimators of R are obtained and their properties are studied. Confidence intervals, exact and approximate, as well as the Bayesian credible sets for R are obtained. A real example is presented in order to illustrate the inferences discussed in the previous sections. A simulation study is conducted to investigate and compare the performance of the intervals presented in this paper and some bootstrap intervals.