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Quality management of products is an important part of manufacturing process. One way to manage and assure product quality is to use machine learning algorithms based on relationship among various process steps. The purpose of this paper is to integrate manufacturing, inspection and after-sales service data to make full use of machine learning algorithms for estimating the products’ quality in a supervised fashion. Proposed frameworks and methods are applied to actual data associated with heavy machinery engines.

By following Lenzerini’s formula, manufacturing, inspection and after-sales service data from various sources are integrated. The after-sales service data are used to label each engine as normal or abnormal. In this study, one-class classification algorithms are used due to class imbalance problem. To address multi-dimensionality of time series data, the symbolic aggregate approximation algorithm is used for data segmentation. Then, binary genetic algorithm-based wrapper approach is applied to segmented data to find the optimal feature subset.

By employing machine learning-based anomaly detection models, an anomaly score for each engine is calculated. Experimental results show that the proposed method can detect defective engines with a high probability before they are shipped.

Through data integration, the actual customer-perceived quality from after-sales service is linked to data from manufacturing and inspection process. In terms of business application, data integration and machine learning-based anomaly detection can help manufacturers establish quality management policies that reflect the actual customer-perceived quality by predicting defective engines.

This paper presents the second-generation estimates for the Italian engineering industry in 1911, a year documented both by the customary demographic census, and the first industrial census. The first part of this paper uses the census data to estimate the industry’s value added, sector by sector; the second further disaggregates each sector by activity, and estimates the value added, employment, physical product, and metal consumption of each one. A third, concluding section dwells on the dependence of cross-section estimates on time-series evidence. Three appendices detail the specific algorithms that generate the present estimates; a fourth, a useful sample of firm-specific data.

The purpose of this paper is to determine and describe the effect of oil degradation on the engine of a 20-ton class excavator operating in Latin America.

The research parameters include: a specific engine class and equipment, the John Deere PowerTech Plus 6068 Tier 3 diesel engine that powers the 20-ton class excavator; identical OSA3 oil analysis laboratory equipment in 11 target countries in Latin America was employed to analyze oil samples; and the same sampling scope and method were followed for each oil sample.

The research results indicated that at 500 h of use, 73.4 percent of the oil sample results indicated that soot accumulation was a significant problem. When associating the engine oil contamination with the environment risk drivers: altitude and diesel quality have the greatest impact on iron readings; bio-diesel impacts copper; and precipitation and poor diesel quality are associated with silicon levels.

Due to diverse machine operating conditions, research offers an accurate global representation. Because there is an exponential count of particles as oil use approaches 250 h, the interval of engine maintenance (oil change) for machinery operating under similar conditions should not exceed 250 h of use.

The main contribution of this paper will help machinery final users and manufacturers to implement mitigation strategies to improve engine durability in countries with similar operating conditions.

This study consists of an examination of productivity growth following three major technological breakthroughs: the steam power revolution, electrification and the ICT revolution. The distinction between sectors producing and sectors using the new technology is emphasized. A major finding for all breakthroughs is that there is a long lag from the time of the original invention until a substantial increase in the rate of productivity growth can be observed. There is also strong evidence of rapid price decreases for steam engines, electricity, electric motors and ICT products. However, there is no persuasive direct evidence that the steam engine producing industry and electric machinery had particularly high productivity growth rates. For the ICT revolution the highest productivity growth rates are found in the ICT-producing industries. We suggest that one explanation could be that hedonic price indexes are not used for the steam engine and the electric motor. Still, it is likely that the rate of technological development has been much more rapid during the ICT revolution compared to any of the previous breakthroughs.

Nanofluids exhibit enhanced heat transfer characteristics and are expected to be the future heat transfer fluids particularly the lubricants and transmission fluids used in heavy machinery. For studying the heat transfer behaviour of the nanofluids, precise values of their thermal conductivity are required. For predicting the correct value of thermal conductivity of a nanofluid, mathematical models are necessary. In this paper, the effective thermal conductivity of various nanofluids has been reported by using both experimental and mathematical modelling. The paper aims to discuss these issues.

Hamilton and Crosser equation was used for predicting the thermal conductivities of nanofluids, and the obtained values were compared with the experimental findings. Nanofluid studied in this paper are Al₂O₃ in base fluid water, Al₂O₃ in base fluid ethylene glycol, CuO in base fluid water, CuO in base fluid ethylene glycol, TiO₂ in base fluid ethylene glycol. In addition, studies have been made on nanofluids with CuO and Al₂O₃ in base fluid SAE 30 particularly for heavy machinery applications.

The study shows that increase in thermal conductivity of the nanofluid with particle concentration is in good agreement with that predicted by Hamilton and Crosser at typical lower concentrations.

It has been observed that deviation between experimental and theoretical results increases as the volume concentration of nanoparticles increases. Therefore, the mathematical model cannot be used for predicting thermal conductivity at high concentration values.

Studies on nanoparticles with a standard mineral oil as base fluid have not been considered extensively as per the previous literatures available.

THE development, in 1929, of a large volume of dredgeable gold‐bearing gravel in the Mandated Territory of New Guinea brought the Directors of Placer Development, Ltd., the exploration company which had proved the area and wished to equip it, face to face with an unusually difficult transport problem. The solution of this was so satisfactorily overcome by the use of aeroplanes, that the writer felt that a short paper on the subject would be of interest to members, and, at the same time, helpful to such engineers as may later have somewhat similar problems to surmount.

NOTWITHSTANDING the rapid industrial development that has taken place in Australia during the last decade, the economy of this country is still largely geared to our primary industries. Therefore, with one or two relatively recent exceptions, our requirements of such equipment as cars, trucks, tractors, earth‐moving machinery, etc. have to be imported from overseas. For this reason the protection of internal combustion engines against rusting and corrosion during shipping is a matter of vital importance to us; particularly so when we receive equipment on our wharves in especially poor condition, simply due to failure on the part of manufacturers to carry out adequate corrosion preventive and packaging procedures prior to despatching their goods. Most mechanical equipment used in primary production and contracting work is of a seasonal nature and because of this, protection of engines during shutdown and storage also constitutes a definite problem.

One of the common law duties owed by the employer is his duty to take reasonable care for the safety of his employee. This common law duty is an implied term in the contract of employment and is therefore contractual in nature. Because of the difficulties which may arise in bringing an action in contract for breach of the employer's duty of care, the employee who has sustained injuries during the course of his employment (although he may sue either in contract of tort will normally bring a tort action.