Selection of time-to-failure model for computerized numerical control turning center based on the assessment of trends in maintenance data

2018 ◽  
Vol 233 (2) ◽  
pp. 105-117 ◽  
Author(s):  
Rajkumar Bhimgonda Patil ◽  
Basavraj S Kothavale ◽  
Laxman Yadu Waghmode
Keyword(s):  
Cooling System ◽  
Electronic System ◽  
Numerical Control ◽  
Time To Failure ◽  
Failure Model ◽  
Time Data ◽  
Failure Data ◽  
Turning Center ◽  
Computerized Numerical Control ◽  
Selection Of

This article provides a generalized framework for selection of time-to-failure model based on the assessment of trends in failure and repair time data. This framework is based on modifications of existing frameworks and can be applied for binary as well as multi-state systems. The proposed framework is applied for reliability analysis of a computerized numerical control turning center. For analysis purpose, the failure data are collected for 50 computerized numerical control turning center over a period of 7 years for three different working conditions, that is, when machining material is steel, aluminum and cast iron. The data collected are then processed using the proposed framework and the best-fit distribution is found for the time-to-failure data. Furthermore, the reliable life and reliabilities of the different sub-systems are estimated. From the analysis, it is found that spindle system, computerized numerical control system, electrical and electronic system, hydraulic system and cooling system are found to be critical from reliability and maintainability point of view. The analysis presented here is expected to help the users and manufacturers of computerized numerical control turning center to estimate the reliability in accurate manner.

Integrated reliability and maintainability analysis of Computerized Numerical Control Turning Center considering the effects of human and organizational factors

2019 ◽  
Vol 26 (1) ◽  
pp. 87-103
Author(s):  
Rajkumar Bhimgonda Patil
Keyword(s):  
Organizational Factors ◽  
Numerical Control ◽  
Content Type ◽  
Failure Data ◽  
Turning Center ◽  
Maintainability Analysis ◽  
Human And Organizational Factors ◽  
Mean Time ◽  
Best Fit ◽  
Field Failure

Purpose Reliability, maintainability and availability of modern complex engineered systems are significantly affected by four basic systems or elements: hardware, software, organizational and human. Computerized Numerical Control Turning Center (CNCTC) is one of the complex machine tools used in manufacturing industries. Several research studies have shown that the reliability and maintainability is greatly influenced by human and organizational factors (HOFs). The purpose of this paper is to identify critical HOFs and their effects on the reliability and maintainability of the CNCTC. Design/methodology/approach In this paper, 12 human performance influencing factors (PIFs) and 10 organizational factors (OFs) which affect the reliability and maintainability of the CNCTC are identified and prioritized according to their criticality. The opinions of experts in the fields are used for prioritizing, whereas the field failure and repair data are used for reliability and maintainability modeling. Findings Experience, training, and behavior are the three most critical human PIFs, and safety culture, problem solving resources, corrective action program and training program are the four most critical OFs which significantly affect the reliability and maintainability of the CNCTC. The reliability and maintainability analysis reveals that the Weibull is the best-fit distribution for time-between-failure data, whereas log-normal is the best-fit distribution for Time-To-Repair data. The failure rate of the CNCTC is nearly constant. Nearly 66 percent of the total failures and repairs are typically due to the hardware system. The percentage of failures and repairs influenced by HOFs is nearly only 16 percent; however, the failure and repair impact of HOFs is significant. The HOFs can increase the mean-time-to-repair and mean-time-between-failure of the CNCTC by nearly 65 and 33 percent, respectively. Originality/value The paper uses the field failure data and expert opinions for the analysis. The critical sub-systems of the CNCTC are identified using the judgment of the experts, and the trend of the results is verified with published results.

Failure Analysis Enhancement by Incorporating a Compact Scan Diagnosis System

2014 ◽  
Author(s):  
Rommel Estores ◽  
Pascal Vercruysse ◽  
Karl Villareal ◽  
Eric Barbian ◽  
Ralph Sanchez ◽  
...  
Keyword(s):  
Data Analysis ◽  
Failure Analysis ◽  
Real Analysis ◽  
Failure Data ◽  
Analysis Methodology ◽  
Efficiency And Effectiveness ◽  
Scan Chain ◽  
On Chip ◽  
Analysis Environment ◽  
Selection Of

Abstract The failure analysis community working on highly integrated mixed signal circuitry is entering an era where simultaneously System-On-Chip technologies, denser metallization schemes, on-chip dissipation techniques and intelligent packages are being introduced. These innovations bring a great deal of defect accessibility challenges to the failure analyst. To contend in this era while aiming for higher efficiency and effectiveness, the failure analysis environment must undergo a disruptive evolution. The success or failure of an analysis will be determined by the careful selection of tools, data and techniques in the applied analysis flow. A comprehensive approach is required where hardware, software, data analysis, traditional FA techniques and expertise are complementary combined [1]. This document demonstrates this through the incorporation of advanced scan diagnosis methods in the overall analysis flow for digital functionality failures and supporting the enhanced failure analysis methodology. For the testing and diagnosis of the presented cases, compact but powerful scan test FA Lab hardware with its diagnosis software was used [2]. It can therefore easily be combined with the traditional FA techniques to provide stimulus for dynamic fault localizations [3]. The system combines scan chain information, failure data and layout information into one viewing environment which provides real analysis power for the failure analyst. Comprehensive data analysis is performed to identify failing cells/nets, provide a better overview of the failure and the interactions to isolate the fault further to a smaller area, or to analyze subtle behavior patterns to find and rationalize possible faults that are otherwise not detected. Three sample cases will be discussed in this document to demonstrate specific strengths and advantages of this enhanced FA methodology.

Texture and Microstructure Effects on Electromigration Behavior of Aluminum Metallization

1991 ◽  
Vol 225 ◽  
Author(s):  
D. B. Knorr ◽  
K. P. Rodbell ◽  
D. P. Tracy
Keyword(s):  
Grain Size ◽  
Standard Deviation ◽  
Pure Aluminum ◽  
Time To Failure ◽  
X Ray Diffraction ◽  
Aluminum Films ◽  
Failure Data ◽  
Transmission Electron ◽  
Aluminum Metallization ◽  
Microstructure Effects

ABSTRACTPure aluminum films are deposited under a variety of conditions to vary the crystallographic texture. After patterning and annealing at 400°C for 1 hour, electromigration tests are performed at several temperatures. Failure data are compared on the basis of t50 and standard deviation. Microstructure is quantified by transmission electron microscopy for grain size and grain size distribution and by X-ray diffraction for texture. A strong (111) texture significantly improves the electromigration lifetime and decreases the standard deviation in time to failure. This improvement correlates with both the fraction and sharpness of the (111) texture component.

CASA: An Alternative Smartphone-Based ADAS

2021 ◽  
pp. 1-41
Author(s):  
Manolo Dulva Hina ◽  
Hongyu Guan ◽  
Assia Soukane ◽  
Amar Ramdane-Cherif
Keyword(s):  
Low Cost ◽  
Electronic System ◽  
Time Data ◽  
Case Scenario ◽  
Safe Driving ◽  
The Road ◽  
Driving Assistance ◽  
Alternative Means ◽  
On The Road ◽  
Driving Assistance System

Advanced driving assistance system (ADAS) is an electronic system that helps the driver navigate roads safely. A typical ADAS, however, is suited to specific brands of vehicle and, due to proprietary restrictions, has non-extendable features. Project CASA is an alternative, low-cost generic ADAS. It is an app deployable on smartphone or tablet. The real-time data needed by the app to make sense of its environment are stored in the vehicle or on the cloud, and are accessible as web services. They are used to determine the current driving context, and, if needed, decide actions to prevent an accident or keep road navigation safe. Project CASA is an undertaking of a consortium of industrial and academic partners. A use case scenario is tested in the laboratory (virtual) and on the road (actual) to validate the appropriateness of CASA. It is a contribution to safe driving. CASA’s contribution also lies in its approach in the semantic modeling of the context of the environment, the vehicle and the driver, and on the modeling of rules for fusion of data and fission process yielding an action to be implemented. In addition, CASA proposes a secured means of transmitting data using light, via light fidelity (LiFi), itself an alternative means of wireless vehicle–smartphone communication.

scholarly journals The Use of Statistical Inference in the Water Supply Network Managing Operation Process

2019 ◽  
Vol 49 (4) ◽  
pp. 221-244
Author(s):  
Izabela Piegdoń
Keyword(s):  
Water Supply ◽  
Time To Failure ◽  
Supply Network ◽  
Water Supply Network ◽  
Time Between Failures ◽  
Operation Process ◽  
Safety And Reliability ◽  
Mean Time ◽  
Operational Data ◽  
Selection Of

Abstract Based on operational data concerning the dates of failure of the water supply network, a mean time to failure was performed. The calculations were performed for the main network, distribution network and water supply connections. The hypothesis about exponential working time between failures was verified using the Pearson test (χ2). The presented analyses provide an attitude of further analyses related to modelling the work of renovation and repair teams, associated with the selection of their appropriate number, and also to ensure the required level of safety and reliability of water supply to the consumers.

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