Quality Of Equipment Maintenance Research Articles

An Internet-of-Things-Based Dynamic Scheduling Optimization Method for Unreliable Flexible Manufacturing Systems under Complex Operational Conditions

The dynamic scheduling problem (DSP) in unreliable flexible manufacturing systems (UFMSs) with concurrency, conflicts, resource sharing, and sequential operations is a complex optimization problem that requires the use of efficient solution methodologies. The effectiveness of scheduling UFMSs relies on the quality of equipment maintenance. Currently, UFMSs with consistently large queues of parts awaiting service employ a repair-after-failure approach as a standard maintenance procedure. This method may require unexpected resources, incur costs, consume time, and potentially disrupt the operations of other UFMSs, either partially or fully. This study suggests using a predictive maintenance (PdM) strategy that utilizes the Internet of Things (IoT) to predict and avoid early mechanical equipment failures before they happen in UFMSs, thereby reducing unplanned downtime and enhancing reliability. Therefore, the objective of this paper is to construct timed Petri net (TPN) models using the IoT for the PdM configuration of mechanical equipment in the dynamic scheduling problem of UFMSs. This necessitates that users represent the specific problem using TPNs. The process of PN modeling requires the utilization of domain knowledge pertaining to the target problems as well as to machine information. However, it is important to note that the modeling rules for PNs are straightforward and limited in number. Consequently, the TPN model is applied to generate and formulate mixed-integer linear programming (MILP) instances accurately. This is done to identify the optimal production cycle time, which may be implemented in real-life scenarios. Several UFMS instances are used to demonstrate the applications and effectiveness of the proposed method. The computational results demonstrate that the proposed method shows superior solution quality, effectively solves instances for a total of 10 parts and 6 machines, and achieves a solution in a reasonable CPU time.

Methods of mining machine components reconditioning and hardening by means of concentrated energy fluxes

Introduction. The value of resources is becoming increasingly important to mining proprietors, since the maintenance of mining equipment is quite expensive. Increased scope and cost of repairs are largely determined by the quality of mining machines and equipment operation in production environment, as well as by their reliability and maintainability. The costs of preventive maintenance are over the limit by 40–50%, in most instances, due to equipment shutdowns caused by subsystem failures. Components with hidden defects as well as the methods of components reconditioning that do not ensure long-term operation cause a significant overrun of costs for breakdown maintenance. The quality of mining equipment maintenance is in direct relationship with the effective methods of components reconditioning, including the methods of components hardening both during their manufacture at machinebuilding plants and during their repairs at repair works that carry out complex, mainly major repairs of mining equipment. Adherence to the flow process of reconditioning/hardening of the component surface in contact with another component is of great importance. Therefore, to preserve fixed assets, in particular, mining and transport equipment, it is essential to find that reconditioning methods which allow to preserve consumer properties and operability of equipment for a sufficiently long time. Subject matter. The article provides an overview of methods of mining machine components reconditioning/hardening involving concentrated energy fluxes. In the authors’ opinion, these are the most effective methods to increase the resource and reliability of mining machine components by 2–3 times. The choice of components reconditioning/hardening method depends entirely on the service centre capacities, necessary technological equipment availability, personnel qualifications and, most importantly, economic feasibility of using a particular method of reconditioning/hardening. Research objective is to consider the most effective methods of mining machine components reconditioning/hardening. Methods of research include the interpretation of a number of experiments conducted at mining enterprises to obtain comparative characteristics of the most effective methods of mining machine components reconditioning/hardening. Research results. The most effective methods of components reconditioning/hardening are identified and recommended practices are provided. Conclusions. It has been established that the application of a particular components reconditioning/hardening method should be based on the data from tribological maps, as well as necessary equipment availability and economic feasibility.

Research on maintenance spare parts requirement prediction based on LSTM recurrent neural network

Abstract The aim of this study was to improve the low accuracy of equipment spare parts requirement predicting, which affects the quality and efficiency of maintenance support, based on the summary and analysis of the existing spare parts requirement predicting research. This article introduces the current latest popular long short-term memory (LSTM) algorithm which has the best effect on time series data processing to equipment spare parts requirement predicting, according to the time series characteristics of spare parts consumption data. A method for predicting the requirement for maintenance spare parts based on the LSTM recurrent neural network is proposed, and the network structure is designed in detail, the realization of network training and network prediction is given. The advantages of particle swarm algorithm are introduced to optimize the network parameters, and actual data of three types of equipment spare parts consumption are used for experiments. The performance comparison of predictive models such as BP neural network, generalized regression neural network, wavelet neural network, and squeeze-and-excitation network prove that the new method is effective and provides an effective method for scientifically predicting the requirement for maintenance spare parts and improving the quality of equipment maintenance.

Using telematics data to support effective solutions for tracking and monitoring the power system condition of unmanned vessels

The paper studies the prospects of using telematics data to support effective solutions for tracking and monitoring the condition of the power supply system (PSS) components of unmanned vessels (UV) through the determination of positioning and, accordingly, operating time of PSS components. The paper attempts to describe one of the modules of the proposed integrated telematics system for UV monitoring, diagnostics and control. For practical implementation of telematics for unmanned merchant vessels, an algorithm has been developed to diagnose the technical condition of PSS components based on the operating time and condition of the units and components of the UV PSS. The results obtained by the algorithm show the technical condition of the observed technical equipment, time of its operation, and justify the need for repair or its complete replacement. The block diagram presents the algorithm that employs a minimal set of data to determine the use of technical equipment for further planning of its preventive maintenance. The paper provides the graphical interpretation of data on the time of PSS components operation and an example of displaying the interface of the remote operator of the UV. It is proposed to use telematics for tracking and monitoring the UV PSS operation in order to improve the quality of equipment maintenance, provide rational use of resources, extend its service life, and plan the repair time. In the future, it is proposed to create an integrated intelligent system based on telematics data, which allows the UV control and monitoring of the technical condition of its equipment.

[Reliability Analysis of Magnetic Resonance Imaging Equipment Based on Non-homogeneous Poisson Process].

In order to evaluate the quality of different brands of magnetic resonance imaging system, optimize the quality of equipment repair and maintenance, and ensure the quality and safety of the equipment in clinical use. Meanwhile build the reliability evaluation model of magnetic resonance imaging equipment based on the large failure data collected by magnetic resonance repair system. In this paper, using the fault data of a certain brand of magnetic resonance in the past two years, applying the statistical judgment criterion, selecting the appropriate statistical distribution model, and finally fitting the equipment reliability evaluation model based on the non-homogeneous Poisson process, and then obtaining the magnetic resonance imaging equipment. Reliability evaluation indicators such as cumulative fault strength function, magnetic resonance imaging equipment fault density function, and mean time between failures. According to the calculated reliability index, on the one hand, it can evaluate the system reliability quality of a certain brand of magnetic resonance imaging equipment, and then evaluate the quality of different brands of magnetic resonance imaging equipment, on the other hand, it can help hospital equipment managers to carry out operational optimization, maintenance strategy development and safety management of magnetic resonance imaging equipment.

[Research on Quality Evaluation System of Ultrasound Diagnostic Equipment Maintenance].

In order to improve the quality of medical equipment after-sales service quality and improve the quality of medical equipment maintenance, this paper discusses the establishment of an evaluation index system to evaluate the quality of ultrasonic diagnostic equipment. From the three aspects of maintenance results, maintenance process and maintenance coverage, the quality of the post-maintenance quality of hospital ultrasound diagnostic equipment manufacturers is objectively evaluated.

Research on Core-Technology of Semi-Physical Maintenance Training System

For a long time, training work of army equipment maintenance crew mostly goes on real-equipment, which is organized by academies or relevant units later. In some extent, this kind of conventional maintenance ways decrease the efficiency and quality of weapon equipment maintenance. In face of more and more new equipment, it not only increases the difficulty of maintenance training but also brings a new challenge to conventional maintenance ways. Aiming at the lack of maintenance training ways of conventional land-battle equipment, we adopt new technology of virtual reality in recent years to create typical-type amphibious assault vehicle virtual maintenance training system, which provide new means for maintenance crew. This text is tend to analyze interactive desktop virtual maintenance training system, and then for instance, briefly introduce typical-type amphibious assault vehicle.

Methodologies for quality assessment of highway operators based on governance best practices with emphasis on toll collection ecosystem

Service quality and the user satisfaction are the main targets for highway operators to take into account in their business plan; moreover, healthy financial stability is critical to the harmony of this environment. In this sense, the toll collection system has a key role for the highway operation sustainability. The Toll Collection System is an ecosystem that involves the quality and maturity of operations, business processes, institutional aspects, equipment maintenance and infrastructure management. The creation of a methodology for quality assessment of the entire Toll Collection ecosystem allows establishing quantitative and qualitative parameters, which may be monitored and evaluated, therefore enabling useful tools for the operator’s decision-making process and government agencies assessments. The methodology was applied to nineteen highway operators from Brazilian concessions, which together manage more than 5400 kilometers.

Proactive approach to smart maintenance and logistics as a auxiliary and service processes in a company

The article describes a proactive approach to smart maintenance and smart logistics. It presents the areas through which all companies must pass. For its successful implementation it is necessary to introduce appropriate management practices also into the area of maintenance. Irrespective of the level of maintenance work in a particular organization, gradual development of maintenance management is needed. The goal is excellent quality of equipment maintenance. The logistics of tomorrow will be supported, to a high extent, by logistics assistance systems. The logistics world is changing - key terms such as Smart Logistics, digitization of the supply chain or Industry 4.0 are widely discussed and already mega trends.

Study on Aircraft Mechanics with Accessibility Appraisement of Aviation Equipment Based on Correlation Analysis Method

Accessibility is an important criterion that reflects the quality of aviation equipment maintenance, especially prominent to maintenance time. To obtain the better accessibility for maintenance efficiency and reducing maintenance costs, it is necessary to choose an optimal scheme in many accessibility designs. This requires the comprehensive appraisement for the parts accessibility of the entire functional system. This paper introduces the correlation analysis method to appraise the accessibility, and propose the mathematical model of the appraisement, which has practical application value to improve the maintenance of aviation equipment.

New high-efficiency low-waste technology at the Vyksa Metallurgical Plant for operating metallurgical equipment with the use of Kompaks® monitoring systems

Introduction of the BER™ KOMPAKS® automated system at the Vyksa Metallurgical Plant to safely and efficiently manage the operation of the plant’s equipment has allowed the facility to begin operating that equipment based on real-time evaluations of its actual physical condition. Introduction of the new system has also allowed better coordination of repair-scheduling with ongoing production operations, significantly improved the reliability and readiness of the equipment for operation at 100% capacity, completely eliminated the human factor from the process of monitoring the condition of equipment, and made it possible to check the quality and timeliness of equipment maintenance and repair work so as to ensure safe, efficient operation of the entire production complex.

Errors in level recorder data: Prevention and detection

The occurrence of errors in water-level recorder data can be reduced by both prevention and detection with subsequent correction. For effective prevention, the error sources should be known; for effective detection, knowledge of error symptoms and their relationship with error sources is essential. The effectiveness of both error prevention and detection depends on field precautions, the quality and frequency of field checks and field-check reports, on the quality of equipment maintenance and, as far as detection-correction is concerned, on the sampling interval. Errors in the data should be detected by a computer program, not manually. A computer-produced error report and field-check reports are necessary for errors in the data to be corrected.

Relationship Between Egg Shell Quality and Shell Breakage and Factors that Affect Shell Breakage in the Field–A Review

SummaryAbout 6 to 8% of the eggs annually produced are broken or cracked between the hen and the consumer's carton. The majority of this breakage is due to interrelationships between egg shell quality and the many biological, environmental and managerial factors which have been individually identified as affecting breakage. Some of the factors associated with shell damage discussed in this review include age of hens, temperature and humidity of the laying house, design of the cage systems and of the cage floors, type of material used to manufacture the cages, frequency of daily egg collection in the laying house and, probably most important, the frequency and quality of handling equipment maintenance. Age and genetic constitution of the hens, environmental temperature, and design and quality of equipment maintenance are the major factors that influence shell breakage. There is a curvilinear relationship between shell quality and shell breakage which explains why small changes in shell quality may be associated with large changes in the incidence of breakage. Published data indicate the incidence of breakage may range from as low as 1 to 2% to 35% or more for other egg producers.