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Most of the mechanical systems consist of common tribo components such as gear, bearing, seal, pump, etc. During operation, the failure of such a component may lead to failure of the system or any other components depending on the system structure or its connections. The transformation of functional quantities or parameters within and various components make these vulnerable to failures and breakdowns. The main purpose of this paper is to evaluate the reliability of a tribo‐pair during operation based on the operational parameters which takes into account the deviation in functional objective and considers the component structure explicitly.

Failure representation using digraph models have mainly been limited to chemical systems and processes but have been applied to a limited extent to mechanical systems. Researchers have considered the operating parameters such as pressure, temperature; feed rate, flow, etc. as the input/output operational parameter for failure cause identification of tribo mechanical system. However, these are not true in case of components like gear, bearing, etc. Therefore, this methodology has been refined in this paper, and is extended to a tribo‐pair by considering its functions along with operating parameters for reliability assessment. The tribo‐pair considered for the development of model is a gear pair, which is a common and important example of mechanical components.

Understanding of the failure modes helps the designer in identifying the root cause of failure and the operational parameters whose increase/decrease affects the functional objective. Consideration of the input and output parameters and their interrelations are used to develop input‐output model of a gear pair called gear pair model. This requires consideration of the input and output parameters, which are based on the gear pair functionality. These parameters have been identified. Four input parameters; five output parameters and one condition monitoring parameter are considered to model the gear pair. In addition to input and output parameters condition monitoring parameters are also considered to develop the gear pair model.

Reliability assessment of a tribo‐pair during operation will help the practicing engineers to take corrective action and minimize the occurrence of undesired failure symptom during operation. The decrease in possibility of undesired failure symptom will enhance the reliability of mechanical system.

Plant failures are often not fully investigated, owing to the pressures of restoring production so as to avoid delays and consequent losses. Instead, problems are overcome by quick solutions. Such solutions, however, may not eliminate the underlying cause of trouble and additional costly failures may occur.

This study provides a unique integrated diagnosis system to investigate the causes of low productivity, profitability, machinery health conditions and wear severity of medium-size biscuit industry assets in Taiz, Yemen.

The evaluation is based on an integrating of the overall equipment effectiveness (OEE) and oil-based maintenance (OBM) approaches. The data are collected using the company's operational records, interviews and observations, while the used lubricating oil samples are also collected from production lines' machineries. Scanning electron microscope (SEM) is used to study the wear debris particle features and wear mechanism. Different other analysis tools such as fishbone, 5 whys and Pareto charts are also used to investigate the root causes and plausible recovery solutions of machinery failures.

This study demonstrated that a large proportion of machinery failures and production loss are of management concerns. Also, this study inferred that the analysis of wear debris is unique and informative for determining machinery wear severity and useful life. Finally, the current conditions of production lines are clarified and suggestions to use a mixed preventive/predictive maintenance management approach are also elucidated.

This work implemented an integrated OEE/OBM diagnostic maintenance system to investigate the root causes of low productivity and machine failures in real production lines and suggested robust decisions on the maintenance duties.

The purpose of this paper is to outline and document the failure root cause of a carbide cutting tool during machining of a hardened tool steel under automatic machining conditions.

Optical metallography and SEM/energy dispersive spectroscopy analysis, together with optical profilometry were employed for failure investigation. The use of an alternative cutting tool and modification of machining conditions are proposed as a failure preventive action.

Severe abrasive wear and adhesion of machining chips are observed in the flank zone, causing blunting of the cutting edge. The revision of cutting conditions, together with the use CBN-based tool insert leads to an overall improvement of the stability of the process and tool lifetime.

This paper places emphasis on a failure analysis case history following a structured approach in industrial machining problem solving, highlighting suggestions for process improvement.

Downtime is a process parameter that substantially impacts on the operating hours and results in production losses, thus motivating maintenance engineers to control process plants. Notwithstanding, the impacting nature of process equipment failure on the operating hours in bottling plants remains inadequately examined. In this paper, the cause-and-effect analysis was used to establish the root cause of the downtime problem and Pareto analysis employed to justify the greatest opportunities for improvement in reducing downtime and increasing reliability levels. Weibull analysis is then conducted on the industrial setting. Novel aspect ratios are proposed.

Using the Weibull failure function of machines as a principal facilitator to produce failure predictions, the downtime behaviour of a process plant was modelled and tested with practical data from a bottling process plant. This research was conducted in a Nigerian process bottling plant where historical data were examined.

The analysis of the results shows the following principal outcome: First, the machines with the highest and least downtime values are 2 and 5, respectively, with correspondingly mean values of 22.83 and 4.39 h monthly. Second, the total downtime 92.05 and 142.14 h for the observed and target downtime, with a coefficient of determination of 0.5848 was recorded. Third, as month 1 was taken as the base period (target), all the machines, except M5 had accepted performance, indicating proper preventive maintenance plan execution for the bottling process plant. Availability shows a direct relationship between the failure and uptime of the machines and the downtime impacts on production. Two machines had random failure pattern and five machines exhibited a wear-out failure pattern and probably due to old age and wear of components in the machines.

The major contribution of the paper is the Weibull modelling in a unique application to a bottling plant to avoid current practices that use reliability software that is not easily accessible.

Fretting wear takes place when two contacting solid surfaces are subjected to relatively small amplitude oscillatory motion in the order of a few microns. The purpose of this paper is the design and manufacture of a fretting wear test rig that can analyze fretting wear on journal bearings.

This study included the manufacturing and operating principles of the test rig. In the test rig, the shaft was fixed and vibrational motion was given to the bearing housing. Vibration motion the amplitude of which could be adjusted was used on the test rig. The vibration motion was applied to a two-piece journal bearing on a fixed shaft supported from both ends.

Vibration amplitude was provided by a micro vibration engine (motor) to be under 100 μm.

Also, scanning electron microscopy, energy dispersive X-ray and X-ray diffraction analyses of the samples were investigated.

The aim of this study is to determine the variation of the different oil analysis instruments in terms of standard deviation and CV‐values, when measuring samples of fully formulated hydraulic and gear oils taken from working systems.

In this investigation, two different spectrometric techniques, inductively coupled plasma‐optical emission spectrometers (ICP‐OES) and rotating disk electrode‐optical emission spectrometers (RDE‐OES), have been studied to determine the instruments' precision of measurement and ability to measure the absolute level of contamination. The study was based on a series of measurements using artificial contamination mixed with oil.

The ICP has better precision of measurement of the two instruments, but cannot predict the absolute values of contamination when oil samples are only treated by organic solvent dilution if the samples include large or dense particles. It is therefore not too good, with the sample pre‐treatment method used, at detecting wear processes that produce dense/large particles, such as pitting failure. For instance, microwave‐assisted acid digestion could be used for sample pre‐treating to obtain accurate results in that case. It should, however, be able to detect wear mechanisms that produce small particles such as abrasive wear in any case. The ICP has a repeatability value of r=3 percent and a reproducibility value of R=12 percent for contamination levels of between 50 and 400 ppm and r=0.6  and R=2 ppm, respectively, at values below 50 ppm. The RDE cannot predict the absolute value of contamination if this includes large or dense particles if proper sample pre‐treatment is not used. It is therefore not good at detecting wear mechanisms that produces dense/large particles (if the oil samples are not pre‐treated properly) such as pitting but should be able to detect abrasive wear and similar processes that produce small particles in any case. The RDE's precision of measurement is not as good as the ICP, with a reproducibility variation of R=r=25 percent for contamination levels between 20 and 500 ppm and R=r=6 ppm for contamination level below 20 ppm.

Only the effects from lubricating oils are studied.

This study will significantly increase the industrial knowledge concerning measurement precision in particle contamination measurement systems.

No similar study is found.

Summarizes briefly the dramatic advances made in the reliability of mechanical seals for rotating shafts in the process chemical and petrochemical industries over the last 30 years. Shows that expected mean time before failure has improved from tens of days to years over that time.

To demonstrate the theory and effectiveness of reliability‐improvement countermeasures for line equipment, specifically industrial robots for automotive production engineering.

Suggests an efficient method of life‐cycle maintenance. The defects of industrial robots are analysed using Weibull analysis.

From the analysis, a strategy of countermeasures is framed for component screening, reliability design and lifetime estimation.

This method has been implemented worldwide in Toyota's factories, and has produced a better operating life cycle for industrial robots.

The purpose of this study is to investigate the effects of load and rotation speed on dry sliding of silicon nitride, including a series of tribological behaviors (friction coefficient, wear rate, temperature rise, etc.) and wear mechanism. Through the analysis of the above characteristics, the influence law of load and speed on them and the internal relationship between them are determined, and then the best comprehensive performance parameters of silicon nitride full-ceramic spherical plain bearings in dry sliding are predicted, which can provide guidance for the operation condition of silicon nitride full-ceramic spherical plain bearings in dry sliding.

The experimental study of different loads and rotation speeds under dry friction conditions was carried out by the using ball-disk sliding test method.

With the increase of load, the friction coefficient of silicon nitride friction pair and the wear rate of silicon nitride ball decrease continuously. With the increase of rotation speed, the friction coefficient of silicon nitride friction pair first increases and then decreases, and the wear of silicon nitride ball first increases and then decreases. With the increase of load and rotation speed, the wear mechanism eventually changes to adhesive wear.

Because of the low timeliness and inefficiency of bearing experiments, this work adopts a simple ball-disk model to comprehensively explore the influence rules of different conditions, which provides a theoretical basis for the subsequent practical application of silicon nitride full-ceramic spherical plain bearings.