Diagnosis and Predictive Maintenance of Machinery and Equipment, by Measuring Vibration

2013 ◽  
Vol 325-326 ◽  
pp. 186-191
Author(s):  
Dan Florin Niculescu ◽  
Adrian Ghionea ◽  
Adrian Olaru
Keyword(s):  
Preventive Maintenance ◽  
Kinematic Chain ◽  
Predictive Maintenance ◽  
Maintenance Management ◽  
Machine Precision ◽  
Predictive Diagnosis ◽  
Maintenance Program ◽  
Automatic Machinery ◽  
A Company ◽  
Made In

The paper presents results of analysis of the dynamic behavior of rotating mechanisms and couplings of the main structure of a kinematic chain sharpening machine precision Cugir normal UAS 200. The ultimate goal is to establish diagnostic and maintenance program the car UAS 200. Diagnosis by measurement of vibration and noise, allow a company to monitor faults and machines and equipment, through a system of preventive maintenance, predictive. Diagnosis automatic machinery and equipment is made in order to ensure a higher reliability of these and how to obtain a more extended life cycle without the occurrence of defects. The application of preventive and predictive maintenance management supports enterprise, because it proves effective, the information you provide in making decisions.

scholarly journals Sistemas de gestión en mantenimiento: propuesta de un TPM en una empresa productora de marcos y molduras de la región

2020 ◽  
pp. 11-17
Author(s):  
René Daniel Fornés-Rivera ◽  
Marco Antonio Conant-Pablos ◽  
Adolfo Cano-Carrasco ◽  
Roberto Carlos Gutiérrez-Beltrán
Keyword(s):  
Preventive Maintenance ◽  
Maintenance Scheduling ◽  
Total Productive Maintenance ◽  
Maintenance Costs ◽  
Monthly Average ◽  
Maintenance Program ◽  
Maintenance Activities ◽  
A Company ◽  
And Training

This research is carried out in a company that produces frames and moldings and addresses the need to develop a Total Productive Maintenance (TPM) program, as a result of the unavailability of machinery and equipment; and training that affects maintenance operations, which are not performed correctly causing costs. Currently there is a 76% availability of machinery; 78% in equipment; 42% in training and monthly average costs in machinery of $ 15,260 pesos; and in equipment of $ 1,860 pesos, in terms of maintenance costs there are no globales records. The objective was to carry out a proposal for maintenance activities, through the TPM methodology; to have an updated maintenance program. The procedure was: Describe the area under study; describe the situation of the area under study; establish TPM policies and goals; identify failures in machinery and equipment; and develop the maintenance program. It was contributed with the contribution of a maintenance program composed of: calendar, records of equipment in stock, corrective and preventive maintenance, maintenance scheduling, records of maintenance costs and catalog. Thus fulfilling the objective of this investigation.

Establishing the State of Operation on Vibration Behavior of the Industrial Robot

2012 ◽  
Vol 186 ◽  
pp. 247-253 ◽  
Author(s):  
Dan Niculescu ◽  
Marek Vagaš ◽  
Adrian Olaru ◽  
Mikuláš Hajduk ◽  
Adrian Ghionea
Keyword(s):  
Fourier Transform ◽  
Life Cycle ◽  
Fast Fourier Transform ◽  
Frequency Domain ◽  
Time Domain ◽  
Preventive Maintenance ◽  
Industrial Robot ◽  
Maintenance Management ◽  
Automatic Diagnosis ◽  
Made In

Diagnosis measurement of vibration and noise, should allow monitoring of equipment defects, through a system of preventive maintenance, predictive. Automatic diagnosis of machinery and equipment was made in order to ensure a higher reliability of these and how to obtain a more extended life cycle without the occurrence of defects. Vibrations are always measured in analog format (time domain) and must be transformed into the frequency domain. Therefore Fast Fourier Transform (FFT) method is used to evaluate vibration Almega AX-V6 robot. The application of preventive and predictive maintenance management supports enterprise, because it proves effective, the information you provide in making decisions.

scholarly journals Automobile Predictive Maintenance using Deep Learning

2021 ◽  
Vol 11 (2) ◽  
pp. 0-0
Keyword(s):  
Preventive Maintenance ◽  
Binary Classification ◽  
Decision Rules ◽  
Complete Information ◽  
Predictive Maintenance ◽  
Maintenance Management ◽  
Classification Model ◽  
Management Policy ◽  
Maintenance Cycle ◽  
Maintenance Schedules

There are three types of maintenance management policy Run-tofailure (R2F), Preventive Maintenance (PvM) and Predictive Maintenance (PdM). In both R2F and PdM we have the data related to the maintenance cycle. In case of Preventive Maintenance (PvM) complete information about maintenance cycle is not available. Among these three maintenance policies, predictive Maintenance (PdM) is becoming a very important strategy as it can help us to minimize the repair time and the associated cost with it. In this paper we have proposed PdM, which allows the dynamic decision rules for the maintenance management. PdM is achieved by training the machine learning model with the datasets. It also helps in planning of maintenance schedules. We specially focused on two models that are Binary Classification and Recurrent Neural Network. In Binary Classification we classify whether our data belongs to the failure class or the non failure class. In Binary Classification the number of cycles is entered and classification model predicts whether it belongs to the failure/non failure class.

scholarly journals SIGNIFICANCE OF BUILDING MAINTENANCE MANAGEMENT SYSTEM TOWARDS SUSTAINABLE DEVELOPMENT: A REVIEW

2016 ◽  
Vol 21 (1) ◽  
Author(s):  
MD AZREE OTHUMAN MYDIN
Keyword(s):  
Sustainable Development ◽  
Preventive Maintenance ◽  
Management System ◽  
Early Stage ◽  
Major Elements ◽  
Predictive Maintenance ◽  
Maintenance Management ◽  
Sustainable Building ◽  
Building Maintenance ◽  
Maintenance Work

<p>The notion of building maintenance is separated into two elements specifically building maintenance management and building maintenance technology. Building maintenance management should accurately be considered as unfolding how a system of maintenance endeavor might be prearranged to deal with a problem of building maintenance. It distinguishes that, aside from locating and remedying the building deficiency an effective programme to restrain overall cost of maintenance but also in an effort to maximize the gain and benefits of the savings. There are a few factors that influence the decision to accomplish the maintenance work. There are the maintenance needs that is the principal aspire of maintenance is to protect a building in its early stage and some major rationale for maintaining building are retaining its significance and value of investments, maintaining the building in a condition that it persists to accomplish its purpose and presenting a good outer shell. Besides that, the efficient maintenance management system embraces many skills and efforts that include identifying maintenance needs and the accurate and spot on remedies. In general, there have four types of maintenance which are breakdown or corrective maintenance, scheduled maintenance, preventive maintenance and also predictive maintenance. This paper will review and discuss some of the major elements of building maintenance towards achieving sustainable building.</p>

scholarly journals Two Different Maintenance Strategies in the Hospital Environment: Preventive Maintenance for Older Technology Devices and Predictive Maintenance for Newer High-Tech Devices

2016 ◽  
Vol 2016 ◽  
pp. 1-16 ◽  
Author(s):  
Mana Sezdi
Keyword(s):  
Preventive Maintenance ◽  
Predictive Maintenance ◽  
Hospital Environment ◽  
High Tech ◽  
Device Management ◽  
Maintenance Strategies ◽  
Safety Testing ◽  
Maintenance Program ◽  
Device Reliability ◽  
Different Characteristics

A maintenance program generated through the consideration of characteristics and failures of medical equipment is an important component of technology management. However, older technology devices and newer high-tech devices cannot be efficiently managed using the same strategies because of their different characteristics. This study aimed to generate a maintenance program comprising two different strategies to increase the efficiency of device management: preventive maintenance for older technology devices and predictive maintenance for newer high-tech devices. For preventive maintenance development, 589 older technology devices were subjected to performance verification and safety testing (PVST). For predictive maintenance development, the manufacturers’ recommendations were used for 134 high-tech devices. These strategies were evaluated in terms of device reliability. This study recommends the use of two different maintenance strategies for old and new devices at hospitals in developing countries. Thus, older technology devices that applied only corrective maintenance will be included in maintenance like high-tech devices.

scholarly journals Automobile Predictive Maintenance Using Deep Learning

2021 ◽  
Vol 11 (2) ◽  
pp. 1-12
Author(s):  
Sanjit Kumar Dash ◽  
Satyam Raj ◽  
Rahul Agarwal ◽  
Jibitesh Mishra
Keyword(s):  
Preventive Maintenance ◽  
Binary Classification ◽  
Decision Rules ◽  
Complete Information ◽  
Predictive Maintenance ◽  
Maintenance Management ◽  
Classification Model ◽  
Management Policy ◽  
Maintenance Cycle ◽  
Maintenance Schedules

There are three types of maintenance management policy Run-tofailure (R2F), Preventive Maintenance (PvM) and Predictive Maintenance (PdM). In both R2F and PdM we have the data related to the maintenance cycle. In case of Preventive Maintenance (PvM) complete information about maintenance cycle is not available. Among these three maintenance policies, predictive Maintenance (PdM) is becoming a very important strategy as it can help us to minimize the repair time and the associated cost with it. In this paper we have proposed PdM, which allows the dynamic decision rules for the maintenance management. PdM is achieved by training the machine learning model with the datasets. It also helps in planning of maintenance schedules. We specially focused on two models that are Binary Classification and Recurrent Neural Network. In Binary Classification we classify whether our data belongs to the failure class or the non failure class. In Binary Classification the number of cycles is entered and classification model predicts whether it belongs to the failure/non failure class.

ASPECTS IN BUILDING A COMPANY WEB-SITE AND ITS ROLE FOR THE DEVELOPMENT OF BUSINESS

2018 ◽  
pp. 117-124
Author(s):  
Petar Halachev ◽  
Victoria Radeva ◽  
Albena Nikiforova ◽  
Miglena Veneva
Keyword(s):  
Life Cycle ◽  
Web Site ◽  
The Internet ◽  
A Company ◽  
The Web ◽  
Design Construction ◽  
Made In ◽  
Site Types

This report is dedicated to the role of the web site as an important tool for presenting business on the Internet. Classification of site types has been made in terms of their application in the business and the types of structures in their construction. The Models of the Life Cycle for designing business websites are analyzed and are outlined their strengths and weaknesses. The stages in the design, construction, commissioning, and maintenance of a business website are distinguished and the activities and requirements of each stage are specified.

Sign in / Sign up

Export Citation Format

Share Document