Maintenance Of Mechanical Systems Research Articles

Overview of the ASME Boiler and Pressure Vessels, U stamps Certification for Pressure Vessels

The American Society of Mechanical Engineers (ASME) Code and Sections are important for the design, manufacturing, and maintenance of mechanical systems and components. This paper will present importance of ASME U stamp certification which is crucial for ensuring Boiler and Pressure Vessels quality, safety, and compliance with industry standards. ASME U stamp certification which is accepted across the more than 100 nations. This paper also covers ASME U stamp requirements, Certificate duration, Certification processes, and application of U stamp and importance of Single Certification Mark for U stamp

Eciton: Very Low-power Recurrent Neural Network Accelerator for Real-time Inference at the Edge

This article presents Eciton, a very low-power recurrent neural network accelerator for time series data within low-power edge sensor nodes, achieving real-time inference with a power consumption of 17 mW under load. Eciton reduces memory and chip resource requirements via 8-bit quantization and hard sigmoid activation, allowing the accelerator as well as the recurrent neural network model parameters to fit in a low-cost, low-power Lattice iCE40 UP5K FPGA. We evaluate Eciton on multiple, established time-series classification applications including predictive maintenance of mechanical systems, sound classification, and intrusion detection for IoT nodes. Binary and multi-class classification edge models are explored, demonstrating that Eciton can adapt to a variety of deployable environments and remote use cases. Eciton demonstrates real-time processing at a very low power consumption with minimal loss of accuracy on multiple inference scenarios with differing characteristics, while achieving competitive power efficiency against the state-of-the-art of similar scale. We show that the addition of this accelerator actually reduces the power budget of the sensor node by reducing power-hungry wireless transmission. The resulting power budget of the sensor node is small enough to be powered by a power harvester, potentially allowing it to run indefinitely without a battery or periodic maintenance.

Global studies in waste management in mechanical workshops: evolution and future perspectives in the search for good practices

The environmental impacts that we are currently facing worldwide are due to a system that uses all available resources as if they were unlimited and therefore an uncontrolled amount of garbage has been generated that is causing damage to the environment and consequently to human health. . In search of solutions to these problems, new ways of managing waste have been implemented, which are often not applied due to lack of knowledge of them. Mechanical shops offer a variety of services, from tire repairs to collision services, whether for light or heavy vehicles, or promote maintenance of mechanical systems in general. These services generate several types of solid waste , including rags contaminated with oils or solvents, plastic containers, old tires, oil, transmission or air filters; plastic and metal body parts, batteries, glass and residual sludge, mostly hazardous waste. In this context, the objective of the article was to carry out a scientific mapping on waste management in mechanical workshops, and in search of good practices. For this, a quantitative and qualitative bibliometrics was carried out. The results indicate that life cycle analysis is the most appropriate tool to define the best use of the waste generated (co-products), followed by management systems and tools and cleaner production. Continuous staff training is essential; to maintain more efficient processes that present returns within each business. The adoption of environmental or management certifications is a big step within each business, but in small mechanical workshops, good waste management is quite sufficient and significant.

Data analytics in fleet operations: A systematic literature review and workflow proposal

Fleet operations have been one of the main concerns of a wide range of industries, particularly those industries in which transportation plays a pivotal role for operational continuity, such as logistics service providers and public transportation. In addition, accentuated by the social and economic globalization, new scenarios and higher requirements were introduced to the transportation sector and, therefore, the need for advanced techniques, such as optimization, traffic modeling, and machine learning, to improve fleet operations, is growing. As for machine learning, although an increasing number of data-driven methods are observed in manufacturing and mobility solutions, there is still a gap in terms of literature reviews related to machine learning applications in fleet operations. Based on this gap, a systematic literature review was conducted, and several applications related to machine learning in fleet operations were identified, most of them encompassing aspects related to predictive maintenance of mechanical systems and components. It was also identified that most of the studies were based on a single data source and did not approach aspects related to the deployment of the machine learning models and data analysis workflows. Therefore, based on the findings from this literature review, the present paper aims to present an overview of the main machine learning applications in fleet operations and propose a data analysis workflow for the connectivity monitoring of heavy vehicles based on multiple data sources.

Causes and Impact of Human Error in Maintenance of Mechanical Systems

The concept of minimizing human error in maintenance is progressively gaining attention in various industries. The incorporation of human factors when solving engineering problems, particularly in maintenance, can no longer be ignored where high standards of performance are expected. The journey of improving maintenance performance through the reduction of human error begins with the understanding of causes and impact of human error in maintenance. This paper evaluates previous scholarly writings on human errors, to specifically establish the causes and impact of human error in maintenance. This study relies predominantly on the existing literature on human error in maintenance derived from published and unpublished research. The primary findings emerging from the research exhibit a number of key factors that cause a human error in maintenance such as poor management and supervision, organizational culture, incompetence, poorly written procedures, poor communication, time pressure, plant and environmental conditions, poor work design and many more. The literature review also revealed that human errors have a negative impact on safety, reliability, productivity and efficiency of the equipment. It was further discovered that equipment failures leading to accidents, incidents, loss of life and economic losses are the major effects of human error. Human error in mechanical systems’ maintenance is a serious problem which needs adequate attention in order to develop corrective and preventive measures. This review paper serves as a basis for maintenance practitioners and interested parties to develop corrective and preventive measures for minimizing human error in the maintenance of mechanical systems.

High-resolution ultrasound camera with sparse array for machine diagnosis

Fault detection plays a crucial role in maintenance of mechanical systems. Ultrasound is known to be a prevalent feature of incipient fault. Industrial ultrasound detectors are widely used to find out initial malfunction of machinery. Especially, ultrasound camera can shows the fault by overlapping beamforming power distribution with optical camera image. One can easily observe where the faults are. Ultrasound transducer usually has larger size than the wavelength of its resonance frequency for highly sensitive measurement. It must be a useful approach to design sparse array that gets over the spatial aliasing problem. The aliased beamforming distribution contains high grating-lobe level due to rough spatial sampling beyond half wavenumber spacing. The sparse array is optimized to minimize maximum side-lobe level by genetic algorithm under given constraints. Being with the constraints of size and number of elements, a limitation on spatial resolution is inevitable. Functional beamforming is simple but effective to dramatically increase spatial resolution as well as reduce side-lobes. A high resolution imaging scheme based on functional beamforming with an optimal sparse array is introduced.

Mechanical Wastewater Facility Challenges in the Canadian Arctic

The consistent performance of wastewater treatment in the far north of Canada, in general, remains an elusive objective, and a frustration for engineers, communities, senior governments, and regulators. Lagoon systems suffer from performance inconsistencies, and a significant scientific effort has been underway by the Government of Nunavut to study and predict the performance of lagoon systems. It has been pointed out that those systems which are technologically simple, and engineered for sufficient capacity tend to perform well, however lagoon systems are ultimately at the mercy of the natural environment, which is extreme in the far north. Mechanical systems do offer the opportunity to reduce the influence of the natural environment, however a multitude of other factors affect the design, construction, operation and maintenance of mechanical systems in the far north. As an opportunity to mitigate the challenges associated with mechanical wastewater systems, a synopsis of the community mechanical treatment facilities in the north has been compiled. Lessons learned from the challenges with mechanical wastewater systems in the far north have been catalogued as a legacy document to future project stakeholders. This compilation is a first attempt to provide a documentation to serve as a reference for improving the development, execution, and operation of future mechanical wastewater treatment projects, where this technical option is deemed appropriate.

Parameterization of Masks for Tight Wavelet Frames and Multiple Pseudoframes and Applications in Mechanical Engineering

Mechanical engineering is a discipline of engineering that applies the principles of engine ering, physics and materials science for analysis, design, manufacturing, and maintenance of mecha nical systems. In this work, the construction of 4-band tight wavelet frames with symmetric proper-ties using symmetric extension and parameterization of the paraunitary matrix. The notion of an 4-band generalized multiresolution structure of subspace is proposed. The characteristics of affine pseudoframes for subspaces is investigated. The construction of a generalized multiresolution structure of Paley-Wiener subspace of is studied. The pyramid decomposition scheme is obta-ined based on such a generalized multiresolution structure and a sufficient condition for its exist-ence is presented. A constructive method for affine frames of based on a generalized multi-resolution structure is presented.

A Study of Vector-Valued Binary Scaling Functions and Parseval Frames with Integer Dilation Constant

Mechanical engineering is a discipline of engineering that applies the principles of physics and materials science for analysis, design, manufacturing, and maintenance of mechanical systems. It is the branch of engineering that involves the production and usage of heat and mechanical power for the design, production, and operation of machines and tools. It is one of the oldest and broadest engineering disciplines. The notion of orthogonal vector-valued binary wavelet packs is introduced. Their traits is investigated by virtue of time-frequency analysis method and finite group theory. Orthogonality formulas are established. Orthonormal wavelet pack bases are obtained. A novel method for constructing a kind of orthogonal shortly supported vector-valued wavelets is presented.

The Characteristics Concerning a Class of Orthogonal Multivariate Matrix-Valued Scaling Functions and Frame Packets

Mechanical engineering is a discipline of engineering that applies the principles of physics and materials science for analysis, design, manufacturing, and maintenance of mechanical systems. In this work, the notion of matrix-valued multiresolution analysis of space is introduced. A method for constructing orthogonal matrix-valued ternary wavelet packs is developed and their properties are discussed by means of time-frequency analysis method, matrix theory and functional analysis method. Three orthogonality formulas concerning these wavelet packets are provided. Finally, new orthonormal wavelet pack bases of space are obtained by constructing a series of subspaces of orthogonal matrix-valued wavelet packets.

Identification of Noise Emission in a Gear Unit

Today it is very important to ensure a stable production without unscheduled outages. To achieve this objective it is required to use advanced production technologies, to ensure adequate maintenance of mechanical systems and to monitor the condition of a device or machine. Reliable and accurate operation of machines and devices with as few outages as possible is desired. The significance of a life cycle design of machines and devices is growing. Possible damages in gear units can be defined by means of monitoring acoustic emission. A crack in the tooth root is usually indicated by significant changes in tooth stiffness. A difference in dynamic responses of an undamaged gear and of a damaged gear can be noted. The possibility of the use of an acoustic method in the field of condition diagostics is dealt with. The noises produced by a gear unit have been analysed, the noise sources within a gear unit have been determined and the corresponding time-frequency analysis of these sources have been performed, using an acoustic camera.

96/01532 Advance monitoring systems for the preventive maintenance of mechanical systems and components

96/01532 Advance monitoring systems for the preventive maintenance of mechanical systems and components